@article{lin_lin_chu_2024, title={A Low-Overhead Dynamic Formation Method for LEO Satellite Swarm Using Imperfect CSI}, volume={73}, ISSN={["1939-9359"]}, DOI={10.1109/TVT.2023.3347077}, abstractNote={In 6G systems, non-terrestrial networks (NTNs) are poised to address the limitations of terrestrial systems, particularly in unserved or underserved areas, by providing infrastructure with mobility that enhances reliability, availability, and responsiveness. Among various types of mobile infrastructures, low earth orbit (LEO) satellite communication (SATCOM) has the potential to offer extended coverage that supports numerous devices simultaneously with low latency. Consequently, LEO SATCOM attracts significant attention from academia, government, and industry. The dynamic formation problem must be solved to form a swarm connecting to the ground station with the most appropriate satellites to achieve LEO SATCOM systems with higher throughput. Existing solutions use computationally demanding methods to solve the NP-hard problem and cannot be employed for SATCOM systems with short coherence time. Furthermore, precise channel state information (CSI) between the ground station and all candidate satellites is required for formation designs, resulting in significant signaling overheads. To overcome these drawbacks, we propose a learning-based dynamic formation method for real-time dynamic formation capability. Specifically, motivated by the channel features of LEO SATCOM, we develop a CSI estimation method to provide coarse CSI (i.e., imperfect CSI) solely based on available geometrical information of LEO SATCOM and without any signaling overhead. Then, our approach can utilize the obtained coarse CSI as inputs and provide valuable guidelines as priorities to access specific satellites for fine-grained CSI (i.e., precise CSI). The prediction results are validated using a small-scale brute force method to determine the final formation. Our intensive simulation results suggest that the proposed method can aid current LEO SATCOM by providing real-time formation results, particularly in low-transmit power regions. Specifically, the proposed method can achieve 90% of full capacity with only 32% signaling overhead to build high-throughput LEO SATCOM.}, number={5}, journal={IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY}, author={Lin, Chia-Hung and Lin, Shih-Chun and Chu, Liang C.}, year={2024}, month={May}, pages={6923–6936} }
 @article{pervej_jin_lin_dai_2024, title={Efficient Content Delivery in User-Centric and Cache-Enabled Vehicular Edge Networks with Deadline-Constrained Heterogeneous Demands}, volume={73}, ISSN={["1939-9359"]}, DOI={10.1109/TVT.2023.3300954}, abstractNote={Modern connected vehicles (CVs) frequently require diverse types of content for mission-critical decision-making and onboard users' entertainment. These contents are required to be fully delivered to the requester CVs within stringent deadlines that the existing radio access technology (RAT) solutions may fail to ensure. Motivated by the above consideration, this paper exploits content caching in vehicular edge networks (VENs) with a software-defined user-centric virtual cell (VC) based RAT solution for delivering the requested contents from a proximity edge server. Moreover, to capture the heterogeneous demands of the CVs, we introduce a preference-popularity tradeoff in their content request model. To that end, we formulate a joint optimization problem for content placement, CV scheduling, VC configuration, VC-CV association and radio resource allocation to minimize long-term content delivery delay. However, the joint problem is highly complex and cannot be solved efficiently in polynomial time. As such, we decompose the original problem into a cache placement problem and a content delivery delay minimization problem given the cache placement policy. We use deep reinforcement learning (DRL) as a learning solution for the first sub-problem. Furthermore, we transform the delay minimization problem into a priority-based weighted sum rate (WSR) maximization problem, which is solved leveraging maximum bipartite matching (MWBM) and a simple linear search algorithm. Our extensive simulation results demonstrate the effectiveness of the proposed method compared to existing baselines in terms of cache hit ratio (CHR), deadline violation and content delivery delay.}, number={1}, journal={IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY}, author={Pervej, Md Ferdous and Jin, Richeng and Lin, Shih-Chun and Dai, Huaiyu}, year={2024}, month={Jan}, pages={1129–1145} }
 @article{lin_lin_lee_2024, title={Privacy-Preserving Serverless Edge Learning With Decentralized Small-Scale Mobile Data}, volume={38}, ISSN={["1558-156X"]}, DOI={10.1109/MNET.135.2200611}, abstractNote={In next-generation (i.e., 6G) networking systems, the data-driven approach will play an essential role, being an efficient tool for networking system management and bringing popular user applications. With those unprecedented and novel usages, existing frameworks fail to consider the complex nature of the next-generation networking system and consequently fail to be applied to future communication systems directly. Moreover, existing frameworks also fail to support popular privacy-preserving learning strategies efficiently by presenting special designs to respond to the resource-demanding nature of the aforementioned strategies. To fill this gap, this paper extends conventional serverless platforms with serverless edge learning architectures, providing a mature and efficient distributed training framework by fully exploiting limited wireless communication and edge computation resources in the considered networking system with the following three features. Firstly, this framework dynamically orchestrates resources among heterogeneous physical units to efficiently fulfill privacy-preserving learning objectives. The design jointly considers learning task requests and underlying infrastructure heterogeneity, including last-mile transmissions, computation abilities of edge and cloud computing centers, and loading status of infrastructure. Secondly, the proposed framework can easily work with data-driven approaches to improve network management efficiency, realizing AI for network promise of next-generation networking systems to provide efficient network automation. Lastly, to significantly reduce distributed training overheads, small-scale data training is proposed by integrating with a general, simple data classifier. This low-load enhancement can seamlessly work with various distributed deep models in the proposed framework to improve communications and computation efficiencies during the training phase. Based on the above innovations, open challenges, and future research directions encourage the research community to develop efficient privacy-preserving learning techniques.}, number={2}, journal={IEEE NETWORK}, author={Lin, Shih-Chun and Lin, Chia-Hung and Lee, Myungjin}, year={2024}, month={Mar}, pages={264–271} }
 @article{lien_huang_tseng_lin_chih-lin_xu_deng_2024, title={Universal Vertical Application Adaptation for O-RAN: Low-Latency RIC and Autonomous Intelligent xAPP Generation}, volume={62}, ISSN={["1558-1896"]}, DOI={10.1109/MCOM.001.2200907}, abstractNote={To support manifold vertical applications in any deployment environments, the fifth generation (5G) radio access network (RAN) may exploit artificial intelligent (AI) and machine learning (ML) for intelligent RAN configuration. With the Open RAN (O-RAN) architecture supporting the Near-Real-Time (Near-RT) RAN Intelligent Controller (RIC), various AI/ML algorithms can be designed in the form of "xAPPs" to optimize the performance for different vertical applications. To this end, a low-latency Near-RT RIC platform is of crucial importance. The lack of an effective design for the autonomous intelligent xAPP generation for all vertical applications also obstructs the zerotouch operations of the O-RAN. In this article, the new designs to enhance the existing standards and platform of Near-RT RIC, and the new design flow for autonomous intelligent xAPP generation are therefore presented. Experimental results demonstrate the practicability to support various vertical applications.}, number={5}, journal={IEEE COMMUNICATIONS MAGAZINE}, author={Lien, Shao-Yu and Huang, Yi-Cheng and Tseng, Chih-Cheng and Lin, Shih-Chun and Chih-Lin, I and Xu, Xiaofei and Deng, Der-Jiunn}, year={2024}, month={May}, pages={80–86} }
 @article{kuno_ochiai_higuchi_satake_cruzado_munakata_mori_lin_matsuura_subramaniam_et al._2023, title={4.71-Pbps-Throughput Multiband OXC Based on Space- and Wavelength-Granular Hybrid Switching}, ISSN={["2155-8515"]}, DOI={10.1109/PSC57974.2023.10297168}, abstractNote={We numerically and experimentally demonstrate a high-throughput and high-port-count OXC architecture based on space and wavelength-granular hybrid switching. Numerical simulations of several network topologies show the good routing performance of our OXC. Its transmission performance is evaluated through an experiment using C- and L-bands. The net OXC throughput of 4.17 Pbps and the OXC port count of 128 are demonstrated.}, journal={2023 INTERNATIONAL CONFERENCE ON PHOTONICS IN SWITCHING AND COMPUTING, PSC}, author={Kuno, Takuma and Ochiai, Takuro and Higuchi, Reiji and Satake, Kazato and Cruzado, Kenji and Munakata, Ryuji and Mori, Yojiro and Lin, Shih-Chun and Matsuura, Motoharu and Subramaniam, Suresh and et al.}, year={2023} }
 @article{lin_rohit_lin_chu_2023, title={6G-AUTOR: Autonomic Transceiver via Realtime On-Device Signal Analytics}, volume={5}, ISSN={["1939-8115"]}, DOI={10.1007/s11265-023-01858-8}, journal={JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY}, author={Lin, Chia-Hung and Rohit, K. V. S. and Lin, Shih-Chun and Chu, Liang C.}, year={2023}, month={May} }
 @article{kantheti_lin_lin_chu_2023, title={Anti-Jamming Resilient LEO Satellite Swarms}, ISSN={["2155-7578"]}, DOI={10.1109/MILCOM58377.2023.10356296}, abstractNote={Advancements in wireless communication and electronics in the past decade have propelled the incorporation of non-terrestrial platforms into mainstream communication networks, opening avenues for several new frontier applications. Notably, low earth orbit (LEO) satellite deployments are being proposed for ubiquitous connectivity, both in commercial and military applications, owing to the possibility of rapid prototyping and deployment. This paper introduces an LEO satellite orchestration framework that provides a satellite swarm system with innovative multi-node coordination designs, namely d-MRC and d-LMMSE, to enhance communication capacity while preserving robustness against jamming adversaries. A hardware-in-the-loop testbed has been built with universal software radio peripheral radios and over-the-air transmissions, which closely emulate real-world satellite communications channels. Experimental results with real-time transmissions validate the effectiveness of our designs as compared to single LEO satellite operations.}, journal={MILCOM 2023 - 2023 IEEE MILITARY COMMUNICATIONS CONFERENCE}, author={Kantheti, Venkata Srirama Rohit and Lin, Chia-Hung and Lin, Shih-Chun and Chu, Liang C.}, year={2023} }
 @article{islam_newaz_song_lartey_lin_fan_hajbabaie_khan_partovi_phuapaiboon_et al._2023, title={Connected autonomous vehicles: State of practice}, volume={5}, ISSN={["1526-4025"]}, DOI={10.1002/asmb.2772}, abstractNote={Abstract}, journal={APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY}, author={Islam, Muhammad Mobaidul and Newaz, Abdullah Al Redwan and Song, Li and Lartey, Benjamin and Lin, Shih-Chun and Fan, Wei and Hajbabaie, Ali and Khan, Mubbashar Altaf and Partovi, Alireza and Phuapaiboon, Tienake and et al.}, year={2023}, month={May} }
 @article{cruzado_mori_lin_matsuura_subramaniam_hasegawa_2023, title={Effective Capacity Estimation Based on Cut-Set Load Analysis in Optical Path Networks}, ISSN={["2155-8515"]}, DOI={10.1109/PSC57974.2023.10297165}, abstractNote={We propose a simple cut-set analysis based method that estimates the capacity bounds of optical networks. The method relies on investigating the wavelength utilization of the cut-sets that are likely to be heavily utilized, so it is simple and efficient. A novel cut-set load aware routing and wavelength assignment algorithm is then proposed. Numerical simulations elucidate that the performance of a conventional heuristics, k-shortest path first-fit, often used as a benchmarking alternative, is quite poor. Moreover, the further capacity improvement over the proposed method is limited to just 5-15%. Hence, even if we use a sophisticated algorithm for network design and control, the capacity improvement over best-performing heuristics approaches the capacity bounds.}, journal={2023 INTERNATIONAL CONFERENCE ON PHOTONICS IN SWITCHING AND COMPUTING, PSC}, author={Cruzado, Kenji and Mori, Yojiro and Lin, Shih-Chun and Matsuura, Motoharu and Subramaniam, Suresh and Hasegawa, Hiroshi}, year={2023} }
 @article{lin_lin_wang_chase_2021, title={A C-V2X Platform Using Transportation Data and Spectrum-Aware Sidelink Access}, ISSN={["1062-922X"]}, DOI={10.1109/SMC52423.2021.9659109}, abstractNote={Intelligent transportation systems and autonomous vehicles are expected to bring new experiences with enhanced efficiency and safety to road users in the near future. However, an efficient and robust vehicular communication system should act as a strong backbone to offer the needed infrastructure connectivity. Deep learning (DL)-based algorithms are widely adopted recently in various vehicular communication applications due to their achieved low latency and fast reconfiguration properties. Yet, collecting actual and sufficient transportation data to train DL-based vehicular communication models is costly and complex. This paper introduces a cellular vehicle-to-everything (C-V2X) verification platform based on an actual traffic simulator and spectrum-aware access. This integrated platform can generate realistic transportation and communication data, benefiting the development and adaptivity of DL-based solutions. Accordingly, vehicular spectrum recognition and management are further investigated to demonstrate the potentials of dynamic slidelink access. Numerical results show that our platform can effectively train and realize DL-based C-V2X algorithms. The developed slidelink communication scheme can adopt different operating bands with remarkable spectrum detection performance, validating its practicality in real-world vehicular environments.}, journal={2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)}, author={Lin, Chia-Hung and Lin, Shih-Chun and Wang, Chien-Yuan and Chase, Thomas}, year={2021}, pages={1293–1298} }
 @article{alshehri_martins_lin_akyildiz_schmidt_2021, title={FracBot Technology for Mapping Hydraulic Fractures}, volume={26}, ISSN={["1930-0220"]}, DOI={10.2118/187196-PA}, abstractNote={Summary}, number={2}, journal={SPE JOURNAL}, author={Alshehri, Abdallah A. and Martins, Carlos H. and Lin, Shih-Chun and Akyildiz, Ian F. and Schmidt, Howard K.}, year={2021}, month={Apr}, pages={610–626} }
 @article{lin_fang_chang_lin_chung_lin_lee_2021, title={GCN-CNVPS: Novel Method for Cooperative Neighboring Vehicle Positioning System Based on Graph Convolution Network}, volume={9}, ISSN={["2169-3536"]}, DOI={10.1109/ACCESS.2021.3127914}, abstractNote={To provide coordinate information for the use of intelligent transportation systems (ITSs) and autonomous vehicles (AVs), the global positioning system (GPS) is commonly used in vehicle localization as a cheap and easily accessible solution for global positioning. However, several factors contribute to GPS errors, decreasing the safety and precision of AV and ITS applications, respectively. Extensive research has been conducted to address this problem. More specifically, several optimization-based cooperative vehicle localization algorithms have been developed to improve the localization results by exchanging information with neighboring vehicles to acquire additional information. Nevertheless, existing optimization-based algorithms still suffer from an unacceptable performance and poor scalability. In this study, we investigated the development of deep learning (DL) based cooperative vehicle localization algorithms to provide GPS refinement solutions with low complexity, high performance, and flexibility. Specifically, we propose three DL models to address the problem of interest by emphasizing the temporal and spatial correlations of the extra given information. The simulation results confirm that the developed algorithms outperform existing optimization-based algorithms in terms of refined error statistics. Moreover, a comparison of the three proposed algorithms also demonstrates that the proposed graph convolution network-based cooperative vehicle localization algorithm can effectively utilize temporal and spatial correlations in the extra information, leading to a better performance and lower training overhead.}, journal={IEEE ACCESS}, author={Lin, Chia-Hung and Fang, Yo-Hui and Chang, Hsin-Yuan and Lin, Yu-Chien and Chung, Wei-Ho and Lin, Shih-Chun and Lee, Ta-Sung}, year={2021}, pages={153429–153441} }
 @article{lin_chen_karimoddini_2021, title={SDVEC: Software-Defined Vehicular Edge Computing with Ultra-Low Latency}, volume={59}, ISSN={["1558-1896"]}, DOI={10.1109/MCOM.004.2001124}, abstractNote={New paradigm shifts and 6G technological rev-olution in vehicular services have emerged toward unmanned driving, automated transportation, and self-driving vehicles. As the technology for autonomous cars becomes mature, real challeng-es come from reliable, safe, real-time connected transportation operations to achieve ubiquitous and prompt information exchanges with massive connected and autonomous vehicles. This article introduces novel wireless distributed architectures that embed the edge computing capability inside software-defined vehicular networking infrastructure. Such edge networks consist of open-loop grant-free communications and computing-based control frameworks, which enable dynamic eco-routing with ultra-low latency and mobile data-driven orchestration. Thus, this work advanc-es the frontiers of machine learning potential and next-generation mobile systems in vehicular net-working applications.}, number={12}, journal={IEEE COMMUNICATIONS MAGAZINE}, author={Lin, Shih-Chun and Chen, Kwang-Cheng and Karimoddini, Ali}, year={2021}, month={Dec}, pages={66–72} }
 @article{lin_lin_blasch_2021, title={TULVCAN: Terahertz Ultra-broadband Learning Vehicular Channel-Aware Networking}, ISSN={["2159-4228"]}, DOI={10.1109/INFOCOMWKSHPS51825.2021.9484613}, abstractNote={Due to spectrum scarcity and increasing wireless capacity demands, terahertz (THz) communications at 0.1-10THz and the corresponding spectrum characterization have emerged to meet diverse service requirements in future 5G and 6G wireless systems. However, conventional compressed sensing techniques to reconstruct the original wideband spectrum with under-sampled measurements become inefficient as local spectral correlation is deliberately omitted. Recent works extend communication methods with deep learning-based algorithms but lack strong ties to THz channel properties. This paper introduces novel THz channel-aware spectrum learning solutions that fully disclose the uniqueness of THz channels when performing such ultra-broadband sensing in vehicular environments. Specifically, a joint design of spectrum compression and reconstruction is proposed through a structured sensing matrix and two-phase reconstruction based on high spreading loss and molecular absorption at THz frequencies. An end-to-end learning framework, namely compression and reconstruction network (CRNet), is further developed with the mean-square-error loss function to improve sensing accuracy while significantly reducing computational complexity. Numerical results show that the CRNet solutions outperform the latest generative adversarial network (GAN) realization with a much higher cosine and structure similarity measures, smaller learning errors, and 56\% less required training overheads. This THz Ultra-broadband Learning Vehicular Channel-Aware Networking (TULVCAN) work successfully achieves effective THz spectrum learning and hence allows frequency-agile access.}, journal={IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM WKSHPS 2021)}, author={Lin, Chia-Hung and Lin, Shih-Chun and Blasch, Erik}, year={2021} }
 @article{chen_lin_hsiao_liu_molisch_fettweis_2021, title={Wireless Networked Multirobot Systems in Smart Factories}, volume={109}, ISSN={["1558-2256"]}, DOI={10.1109/JPROC.2020.3033753}, abstractNote={Smart manufacturing based on artificial intelligence and information communication technology will become the main contributor to the digital economy of the upcoming decades. In order to execute flexible production, smart manufacturing must holistically integrate wireless networking, computing, and automatic control technologies. This article discusses the challenges of this complex system engineering from a wireless networking perspective. Starting from enabling flexible reconfiguration of a smart factory, we discuss existing wireless technology and the trends of wireless networking evolution to facilitate multirobot smart factories. Furthermore, the special sequential decision-making of a multirobot manufacturing system is examined. Social learning can be used to extend the resilience of precision operation in a multirobot system by taking network topology into consideration, which also introduces a new vision for the cybersecurity of smart factories. A summary of highlights of technological opportunities for holistic facilitation of wireless networked multirobot smart factories rounds off this article.}, number={4}, journal={PROCEEDINGS OF THE IEEE}, author={Chen, Kwang-Cheng and Lin, Shih-Chun and Hsiao, Jen-Hao and Liu, Chun-Hung and Molisch, Andreas F. and Fettweis, Gerhard P.}, year={2021}, month={Apr}, pages={468–494} }
 @article{pervej_lin_2020, title={Eco-Vehicular Edge Networks for Connected Transportation: A Distributed Multi-Agent Reinforcement Learning Approach}, DOI={10.1109/VTC2020-Fall49728.2020.9348507}, abstractNote={This paper introduces an energy-efficient, software-defined vehicular edge network for the growing intelligent connected transportation system. A joint user-centric virtual cell formation and resource allocation problem is investigated to bring eco-solutions at the edge. This joint problem aims to combat against the power-hungry edge nodes while maintaining assured reliability and data rate. More specifically, by prioritizing the downlink communication of dynamic eco-routing, highly mobile autonomous vehicles are served with multiple low-powered access points (APs) simultaneously for ubiquitous connectivity and guaranteed reliability of the network. The formulated optimization is exceptionally troublesome to solve within a polynomial time, due to its complicated combinatorial structure. Hence, a distributed multi-agent reinforcement learning (D-MARL) algorithm is proposed for eco-vehicular edges, where multiple agents cooperatively learn to receive the best reward. First, the algorithm segments the centralized action space into multiple smaller groups. Based on the model-free distributed Q learner, each edge agent takes its actions from the respective group. Also, in each learning state, a software-defined controller chooses the global best action from individual bests of the distributed agents. Numerical results validate that our learning solution achieves near-optimal performances within a small number of training episodes as compared with existing baselines.}, journal={2020 IEEE 92ND VEHICULAR TECHNOLOGY CONFERENCE (VTC2020-FALL)}, publisher={IEEE}, author={Pervej, Md Ferdous and Lin, Shih-Chun}, year={2020} }
 @article{lin_lee_chung_lin_lee_2020, title={Unsupervised ResNet-Inspired Beamforming Design Using Deep Unfolding Technique}, ISSN={["2576-6813"]}, DOI={10.1109/GLOBECOM42002.2020.9322638}, abstractNote={Beamforming is a key technology in communication systems of the fifth generation and beyond. However, traditional optimization-based algorithms are often computationally prohibited from performing in a real-time manner. On the other hand, the performance of existing deep learning (DL)-based algorithms can be further improved. As an alternative, we propose an unsupervised ResNet-inspired beamforming (RI-BF) algorithm in this paper that inherits the advantages of both pure optimization-based and DL-based beamforming for efficiency. In particular, a deep unfolding technique is introduced to reference the optimization process of the gradient ascent beamforming algorithm for the design of our neural network (NN) architecture. Moreover, the proposed RI-BF has three features. First, unlike the existing DL-based beamforming method, which employs a regularization term for the loss function or an output scaling mechanism to satisfy system power constraints, a novel NN architecture is introduced in RI-BF to generate initial beamforming with a promising performance. Second, inspired by the success of residual neural network (ResNet)-based DL models, a deep unfolding module is constructed to mimic the residual block of the ResNet-based model, further improving the performance of RI-BF based on the initial beamforming. Third, the entire RI-BF is trained in an unsupervised manner; as a result, labelling efforts are unnecessary. The simulation results demonstrate that the performance and computational complexity of our RI-BF improves significantly compared to the existing DL-based and optimization-based algorithms.}, journal={2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)}, author={Lin, Chia-Hung and Lee, Yen-Ting and Chung, Wei-Ho and Lin, Shih-Chun and Lee, Ta-Sung}, year={2020} }
 @article{tello-oquendo_lin_akyildiz_pla_2019, title={Software-Defined architecture for QoS-Aware IoT deployments in 5G systems}, volume={93}, ISSN={["1570-8713"]}, DOI={10.1016/j.adhoc.2019.101911}, abstractNote={Internet of Things (IoT), a ubiquitous network of interconnected objects, harvests information from the environments, interacts with the physical world, and uses the existing Internet infrastructure to provide services for information transfer and emerging applications. However, the scalability and Internet access fundamentally challenge the realization of a wide range of IoT applications. Based on recent developments of 5G system architecture, namely SoftAir, this paper introduces a new software-defined platform that enables dynamic and flexible infrastructure for 5G IoT communication. A corresponding sum-rate analysis is also carried out via an optimization approach for efficient data transmissions. First, the SoftAir decouples control plane and data plane for a software-defined wireless architecture and enables effective coordination among remote radio heads (RRHs), equipped with millimeter-wave (mmWave) frontend, for IoT access. Next, by introducing an innovative design of software-defined gateways (SD-GWs) as local IoT controllers in SoftAir, the wide diversity of IoT applications and the heterogeneity of IoT devices are easily accommodated. These SD-GWs aggregate the traffic from heterogeneous IoT devices and perform protocol conversions between IoT networks and radio access networks. Moreover, a cross-domain optimization framework is proposed in this extended SoftAir architecture concerning both upstream and downstream communication, where the respective sum-rates are maximized and system-level constraints are guaranteed, including (i) quality-of-service requirements of IoT transmissions, (ii) total power limit of mmWave RRHs, and (iii) fronthaul network capacities. Simulation results validate the efficacy of our solutions, where the extended SoftAir solution surpasses existing IoT schemes in spectral efficiency and achieves optimal data rates for next-generation IoT communication.}, journal={AD HOC NETWORKS}, author={Tello-Oquendo, Luis and Lin, Shih-Chun and Akyildiz, Ian F. and Pla, Vicent}, year={2019}, month={Oct} }
 @inproceedings{tello-oquendo_akyildiz_lin_pla_2018, place={Podgorica, Montenegro}, title={A Software-Defined Networking based Architecture for QoS-Aware IoT Communication in 5G Systems}, author={Tello-Oquendo, L. and Akyildiz, I.F. and Lin, S.-C. and Pla, V.}, year={2018}, month={Jun} }
 @inproceedings{lee_wang_lin_akyildiz_luo_2018, title={Dynamic bandwidth allocation in SDN based next generation virtual networks}, ISBN={9781450358859}, url={http://dx.doi.org/10.1145/3264746.3264754}, DOI={10.1145/3264746.3264754}, abstractNote={Software-defined networking (SDN), recognized as next-generation paradigm, decouples the network control plane from the data forwarding plane for a logically centralized controller, allowing rapid networking technology innovations to serve great varieties of users' applications. SDN empowers the evolution of Internet with Open-Flow (OF) and taking advantages of Network Virtualization (NV) to provide efficient service slicing strategies. One of key research issues in both SDN and NV environments is a lack of resource scheduling mechanisms in the physical infrastructure. The resource scheduling mechanisms should be highly capable of ensuring network stability to add further benefits to SDN based next generation virtual networks. We propose a service discipline of dynamic bandwidth scheduling (DBS) within OF switches that dynamically allocates data rates to flows regarding QoS and flow dynamics. Furthermore, we formulate a coherent analysis framework of scheduling disciplines as a mathematical model based on the deterministic network calculus to provide a fast characterization of deterministic service guarantees in SDN. Finally, simulations validate derived theoretical bounds from the analysis framework and confirm that the DBS discipline guarantees QoS of all flows through dynamic bandwidth allocation and ensures an efficient allocation of system bandwidth.}, booktitle={Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems  - RACS '18}, publisher={ACM Press}, author={Lee, Ahyoung and Wang, Pu and Lin, Shih-Chun and Akyildiz, Ian F. and Luo, Min}, year={2018} }
 @inproceedings{lin_2018, title={End-to-End Network Slicing for 5G&B Wireless Software-Defined Systems}, ISBN={9781538647271}, url={http://dx.doi.org/10.1109/glocom.2018.8647514}, DOI={10.1109/glocom.2018.8647514}, abstractNote={As a key enabling technology for 5G&B systems, network virtualization allows multiple service providers to simultaneously and independently serve their users via virtualized network slices. However, this innovative technology cannot slice wireless resources without a paradigm shift in existing hardware-based architectures. In this paper, end-to-end network slicing is treated from a perspective of wireless software-defined networking architectures. It jointly optimizes all communication functionalities in both radio access and core networks to ensure optimal data throughput and congestion-free systems. First, based on software- defined cellular architectures, the idea of end- to-end (across access and core network domains) virtualization is introduced with dedicated control units, including high-level controllers and local baseband servers. Next, a stochastic utility-optimal virtualization problem is formulated, which jointly optimizes congestion control, flow routing, and power slicing to maximize the total incoming rates of wireless/wired flows, while satisfying the flow- queue stability and system-level constraints. After transforming the virtualization problem into a tractable form, an iterative network slicing algorithm is proposed that employs a primal-dual Newton method with quadratic convergence and achieves resource-efficient virtualization via control-unit coordination. Numerical results validate the efficacy of our solution, facilitating the 5G&B infrastructure-as-a-service.}, booktitle={2018 IEEE Global Communications Conference (GLOBECOM)}, publisher={IEEE}, author={Lin, Shih-Chun}, year={2018}, month={Dec} }
 @inproceedings{tello-oquendo_akyildiz_lin_pla_2018, title={SDN-based architecture for providing reliable Internet of Things connectivity in 5G systems}, ISBN={9783903176058}, url={http://dx.doi.org/10.23919/medhocnet.2018.8407080}, DOI={10.23919/medhocnet.2018.8407080}, abstractNote={Sheer number of devices in Internet of Things (IoTs) fundamentally challenge the ubiquitous information transmissions through the backbone networks, such as cellular systems. The heterogeneity of IoT devices and the hardware-based, inflexi-ble cellular architectures impose even greater challenges to enable efficient communication. To address these challenges, this paper introduces the so-called SoftAir architecture on wireless software-defined networking and proposes software-defined gateways (SD-GWs) that jointly optimize cross-layer communication functionalities between heterogeneous IoT devices and cellular systems. First, the SoftAir architecture is proposed to support a unified software-defined platform for quality-of-service aware IoT systems and software-defined radio access networks (SD-RANs) with millimeter-wave transmissions. Next, the SD-GWs are designed in SoftAir to explore the interactions between two-types of networks (i.e., IoTs and SD-RANs) and enable cross-layer solutions that simultaneously achieve optimal energy savings and throughput gain in IoTs and maximum sum-rates in SD-RANs. Simulation results validate that our SoftAir solutions surpass classical IoT schemes by jointly optimizing communication functionalities for both IoTs and SD-RANs and bring significant system synergies for reliable 5G IoT communication.}, booktitle={2018 17th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net)}, publisher={IEEE}, author={Tello-Oquendo, Luis and Akyildiz, Ian F. and Lin, Shih-Chun and Pla, Vicent}, year={2018}, month={Jun} }
 @article{lin_wang_akyildiz_luo_2018, title={Towards Optimal Network Planning for Software-Defined Networks}, volume={17}, ISSN={["1558-0660"]}, DOI={10.1109/TMC.2018.2815691}, abstractNote={Supporting on-line and adaptive traffic engineering in software-defined networks entails the fast, robust control message forwarding from software-defined switches to the controller(s). In-band control using the existing infrastructure is cost-efficient, but imposes a substantial barrier to timely transmissions of control messages. Also, due to the limited computational capability of a single controller, only the use of multiple controllers is practically viable for large-scaled networks. Therefore, in this paper, the optimal software-defined network planning is investigated with multi-controllers. First, the network planning problem is formulated as a nonlinear multi-objective optimization, which aims to simultaneously minimize the number of controllers and the control traffic delay for each switch. This planning problem is then partitioned into two sub-problems, i.e., multi-controller placement and control traffic balancing, which are respectively solved by the proposed fast-convergent algorithms. Furthermore, an adaptive feedback control mechanism is proposed to iteratively work out the two sub-problems and enable the dynamic network replanning, subject to the time-varying traffic volume and network topology. Simulations validate the adaptivity of our control scheme, which significantly reduces delay with maximum throughput for control flows, brings minimal impact to normal data flows, and requires the minimum controllers.}, number={12}, journal={IEEE TRANSACTIONS ON MOBILE COMPUTING}, author={Lin, Shih-Chun and Wang, Pu and Akyildiz, Ian F. and Luo, Min}, year={2018}, month={Dec}, pages={2953–2967} }
 @inproceedings{lin_narasimhan_2018, title={Towards Software-Defined Massive MIMO for 5G&B Spectral-Efficient Networks}, ISBN={9781538631805}, url={http://dx.doi.org/10.1109/icc.2018.8422150}, DOI={10.1109/icc.2018.8422150}, abstractNote={As a key enabling technology for 5G&B systems, massive multi-input multi-output (MIMO) allows the system capacity to be theoretically increased by simply installing additional antennas to remote radio heads (RRHs). However, this innovative technology cannot support higher data capacity without accurate channel state information and interference handling, especially for multi-cell scenarios. In this paper, the dynamic macro- diversity (i.e., network) massive MIMO is treated from the perspective of software-defined cellular architecture. The so-called software-defined massive MIMO is introduced, which dynamically coordinates highly-deployed RRHs equipped with massive antennas so that the maximum spectral efficiency is achieved. First, the software- defined cellular architecture is presented, where distributed massive antenna systems with centralized control and time-division duplexing massive MIMO are investigated. Next, in this considered architecture, a rigid analysis of achievable ergodic user sum-rates is given for macro-diversity massive MIMO schemes. An optimization framework of software-defined massive MIMO is further proposed that optimizes RRH clustering pattern and RRH-user associations while satisfying system-level constraints. To address the NP-complete problem of the optimal framework design, an iterative, global search algorithm is developed that exploits genetic algorithms and yields satisfactory solutions in only few rounds. Performance evaluation validates the efficacy of our solution which facilitates universal frequency reuse for 5G&B wireless networks.}, booktitle={2018 IEEE International Conference on Communications (ICC)}, publisher={IEEE}, author={Lin, Shih-Chun and Narasimhan, Harini}, year={2018}, month={May} }
 @article{lin_wang_akyildiz_luo_2017, title={Delay-Based Maximum Power-Weight Scheduling With Heavy-Tailed Traffic}, volume={25}, ISSN={["1558-2566"]}, DOI={10.1109/tnet.2017.2706743}, abstractNote={Heavy-tailed (HT) traffic (e.g., the Internet and multimedia traffic) fundamentally challenges the validity of classic scheduling algorithms, designed under conventional light-tailed (LT) assumptions. To address such a challenge, this paper investigates the impact of HT traffic on delay-based maximum weight scheduling (DMWS) algorithms, which have been proven to be throughput-optimal with enhanced delay performance under the LT traffic assumption. First, it is proven that the DMWS policy is not throughput-optimal anymore in the presence of hybrid LT and HT traffic by inducing unbounded queuing delay for LT traffic. Then, to solve the unbounded delay problem, a delay-based maximum power-weight scheduling (DMPWS) policy is proposed that makes scheduling decisions based on queuing delay raised to a certain power. It is shown by the fluid model analysis that DMPWS is throughput-optimal with respect to moment stability by admitting the largest set of traffic rates supportable by the network, while guaranteeing bounded queuing delay for LT traffic. Moreover, a variant of the DMPWS algorithm, namely the IU-DMPWS policy, is proposed, which operates with infrequent queue state updates. It is also shown that compared with DMPWS, the IU-DMPWS policy preserves the throughput optimality with much less signaling overhead, thus expediting its practical implementation.}, number={4}, journal={IEEE-ACM TRANSACTIONS ON NETWORKING}, author={Lin, Shih-Chun and Wang, Pu and Akyildiz, Ian F. and Luo, Min}, year={2017}, month={Aug}, pages={2540–2555} }
 @inproceedings{lin_akyildiz_2017, title={Dynamic base station formation for solving NLOS problem in 5G millimeter-wave communication}, ISBN={9781509053360}, url={http://dx.doi.org/10.1109/infocom.2017.8057227}, DOI={10.1109/infocom.2017.8057227}, abstractNote={Millimeter-wave communication is one of the enabling technologies to meet high data-rate requirements of 5G wireless systems. Millimeter-wave systems due large available bandwidth enable gigabit-per-second data rates for line-of-sight (LOS) transmissions in short distances. However, for non-line-of-sight (NLOS) transmissions, millimeter-wave systems suffers performance degradation because the received signal strengths at user equipments (UEs) are not satisfactory. In this paper, the NLOS problem in millimeter-wave systems is treated from SoftAir (a wireless software-defined networking architecture) perspective. In particular, a so-called dynamic base station (BS) formation is introduced, which adaptively coordinates BSs and their multiple antennas to always satisfy UEs' quality-of-service (QoS) requirements in NLOS cases. First, the architecture for software-defined millimeter-wave system is introduced, where remote radio heads (RRHs) coordination is explained and millimeter-wave channel model between RRHs and UEs is analyzed. A ubiquitous millimeter-wave coverage problem is formulated, which jointly optimizes RRH-UE associations and beamforming weights of RRHs to maximize the UE sum-rate while guaranteeing QoS and system-level constraints. After proving the np-hardness of the coverage optimization problem with non-convex constraints, an iterative algorithm is developed for dynamic BS formation that achieves ubiquitous coverage with high data rates in LOS and NLOS cases. Through successive convex approximations, the proposed dynamic BS formation algorithm transforms the original mixed-integer nonlinear programming into a mixed-integer second-order cone programming, which is efficiently solved by convex tools. Simulations validate the efficacy of our solution that completely solves NLOS problem by facilitating ubiquitous coverage in 5G millimeter-wave systems.}, booktitle={IEEE INFOCOM 2017 - IEEE Conference on Computer Communications}, publisher={IEEE}, author={Lin, Shih-Chun and Akyildiz, Ian F.}, year={2017}, month={May} }
 @article{lin_alshehri_wang_akyildiz_2017, title={Magnetic Induction-Based Localization in Randomly Deployed Wireless Underground Sensor Networks}, volume={4}, ISSN={["2327-4662"]}, DOI={10.1109/jiot.2017.2729887}, abstractNote={Wireless underground sensor networks enable many applications, such as mine and tunnel disaster prevention, oil upstream monitoring, earthquake prediction and landslide detection, and intelligent farming and irrigation among many others. Most applications are location-dependent, so they require precise sensor positions. However, classical localization solutions based on the propagation properties of electromagnetic waves do not function well in underground environments. This paper proposes a magnetic induction (MI)-based localization that accurately and efficiently locates randomly deployed sensors in underground environments by leveraging the multipath fading free nature of MI signals. Specifically, the MI-based localization framework is first proposed based on underground MI channel modeling with additive white Gaussian noise, the designated error function, and semidefinite programming relaxation. Next, this paper proposes a two-step positioning mechanism for obtaining fast and accurate localization results by: first, developing the fast-initial positioning through an alternating direction augmented Lagrangian method for rough sensor locations within a short processing time, and then proposing fine-grained positioning for performing powerful search for optimal location estimations via the conjugate gradient algorithm. Simulations confirm that our solution yields accurate sensor locations with both low and high noise and reveals the fundamental impact of underground environments on the localization performance.}, number={5}, journal={IEEE INTERNET OF THINGS JOURNAL}, author={Lin, Shih-Chun and Alshehri, Abdallah Awadh and Wang, Pu and Akyildiz, Ian F.}, year={2017}, month={Oct}, pages={1454–1465} }
 @inproceedings{alshehri_lin_akyildiz_2017, title={Optimal energy planning for wireless self-contained sensor networks in oil reservoirs}, ISBN={9781467389990}, url={http://dx.doi.org/10.1109/icc.2017.7996850}, DOI={10.1109/icc.2017.7996850}, abstractNote={In-situ monitoring of oil reservoirs is crucial for determining the sweet spot of oil and natural gas reserves. Wireless sensor nodes are a promising technology to collect data from oil reservoirs in real time, such nodes are not sufficient for transmitting the required data within a power budget because of limitations caused by the very small size of sensors and the environment. To overcome limitations caused by harsh environmental conditions and power constraints, this paper proposes an accurate energy model framework of a linear oil sensor network topology that gives feasible sensors' transmission rates and sensor network topology while always guarantees enough energy. Since the magnetic induction communication channels is employed, we first examine the non-flat MI fading channels to obtain the accurate received signal qualities. Then, we design MI-based modulation and error control coding schemes and evaluate the energy consumption for MI transmissions to determine optimal sensors' transmissions rate and number of sensors while sensors' packet error rate and energy constraints are satisfied at the same time. we confirm the accuracy of our model via theoretical and simulation evaluations.}, booktitle={2017 IEEE International Conference on Communications (ICC)}, publisher={IEEE}, author={Alshehri, Abdallah A. and Lin, Shih-Chun and Akyildiz, Ian F.}, year={2017}, month={May} }
 @inproceedings{gran_lin_akyildiz_2017, title={Towards wireless infrastructure-as-a-service (WlaaS) for 5G software-defined cellular systems}, ISBN={9781467389990}, url={http://dx.doi.org/10.1109/icc.2017.7996597}, DOI={10.1109/icc.2017.7996597}, abstractNote={As a key enabling technology for 5G cellular systems, wireless virtualization allows multiple service providers to simultaneously and independently serve their users via virtualized network slices. However, differently from wired network virtualization that has been studied for many years, the research of wireless resource slicing is still at a very early stage. In this paper, based on the proposed 5G software-defined systems, novel wireless infrastructure-as-a-service (WIaaS) is introduced, which enables mobile virtual network operators to provide distinguished services to their subscribed users while sharing a common physical infrastructure. Specifically, through software-defined networking and fine-grained base station designs, a throughput-efficient resource allocation is proposed, by which, at the same time, (1) the data-rate requirements of traffic flows in virtual networks are fulfilled, (2) the isolation among applications and deployed protocols in networks is guarded, and (3) the global resource utilization is maximized. Simulations confirm that the proposed solution outperforms state-of-the-art schemes with greater system throughput and fairness support. Moreover, the performance improvement becomes significant when transmitted data has real-time requirements or the flow density and diversity are increased. Thus, WIaaS facilitates wireless resource slicing upon software-defined architectures and has opened a new research area of virtualization in next-generation cellular systems.}, booktitle={2017 IEEE International Conference on Communications (ICC)}, publisher={IEEE}, author={Gran, Albert and Lin, Shih-Chun and Akyildiz, Ian F.}, year={2017}, month={May} }
 @article{akyildiz_nie_lin_chandrasekaran_2016, title={5G roadmap: 10 key enabling technologies}, volume={106}, ISSN={1389-1286}, url={http://dx.doi.org/10.1016/j.comnet.2016.06.010}, DOI={10.1016/j.comnet.2016.06.010}, abstractNote={The fifth generation (5G) mobile communication networks will require a major paradigm shift to satisfy the increasing demand for higher data rates, lower network latencies, better energy efficiency, and reliable ubiquitous connectivity. With prediction of the advent of 5G systems in the near future, many efforts and revolutionary ideas have been proposed and explored around the world. The major technological breakthroughs that will bring renaissance to wireless communication networks include (1) a wireless software-defined network, (2) network function virtualization, (3) millimeter wave spectrum, (4) massive MIMO, (5) network ultra-densification, (6) big data and mobile cloud computing, (7) scalable Internet of Things, (8) device-to-device connectivity with high mobility, (9) green communications, and (10) new radio access techniques. In this paper, the state-of-the-art and the potentials of these ten enabling technologies are extensively surveyed. Furthermore, the challenges and limitations for each technology are treated in depth, while the possible solutions are highlighted.}, journal={Computer Networks}, publisher={Elsevier BV}, author={Akyildiz, Ian F. and Nie, Shuai and Lin, Shih-Chun and Chandrasekaran, Manoj}, year={2016}, month={Sep}, pages={17–48} }
 @inproceedings{wang_lin_luo_2016, title={A Framework for QoS-aware Traffic Classification Using Semi-supervised Machine Learning in SDNs}, ISBN={9781509026289}, url={http://dx.doi.org/10.1109/scc.2016.133}, DOI={10.1109/scc.2016.133}, abstractNote={In this paper, a QoS-aware traffic classification framework for software defined networks is proposed. Instead of identifying specific applications in most of the previous work of traffic classification, our approach classifies the network traffic into different classes according to the QoS requirements, which provide the crucial information to enable the fine-grained and QoS-aware traffic engineering. The proposed framework is fully located in the network controller so that the real-time, adaptive, and accurate traffic classification can be realized by exploiting the superior computation capacity, the global visibility, and the inherent programmability of the network controller. More specifically, the proposed framework jointly exploits deep packet inspection (DPI) and semi-supervised machine learning so that accurate traffic classification can be realized, while requiring minimal communications between the network controller and the SDN switches. Based on the real Internet data set, the simulation results show the proposed classification framework can provide good performance in terms of classification accuracy and communication costs.}, booktitle={2016 IEEE International Conference on Services Computing (SCC)}, publisher={IEEE}, author={Wang, Pu and Lin, Shih-Chun and Luo, Min}, year={2016}, month={Jun} }
 @article{lin_chen_2016, title={Cognitive and Opportunistic Relay for QoS Guarantees in Machine-to-Machine Communications}, volume={15}, ISSN={1536-1233}, url={http://dx.doi.org/10.1109/tmc.2015.2421931}, DOI={10.1109/tmc.2015.2421931}, abstractNote={Deploying spectrum sharing machine-to-machine (M2M) communications with the existing wireless networks achieves ubiquitous data transportation among objects and the surrounding environment to benefit our daily life. However, the lack of schemes to completely characterize M2M network topology, to efficiently share radio resource, and to provide quality-of-service (QoS) guarantee regarding end-to-end delay creates challenges to practically facilitate M2M communications. Via mathematical derivations, the network connectivity, degree distribution, and average distance are provided for large M2M networks. To achieve reliable communications upon such M2M networks, inspired by cognitive radio technology and cooperative communications, a cognitive and opportunistic relay (COR) scheme is proposed. Specifically, machines with the proposed COR autonomously sense the primary systems' spectrum usage so as to mitigate detractive interference and adopt opportunistic forwarder selection for lower link delay of packet transmissions. Furthermore, by analytical deriving the effective capacity of the COR over connected M2M networks, the throughput under statistical QoS guarantee and the corresponding delay violation probability are proposed to specify the QoS guarantee capability of the networks and thus suggest the conditions of dependable end-to-end transmissions. Simulation results confirm that the proposed COR effectively achieves the delay guarantee performance, to yield a novel framework for facilitating reliable M2M communications in large machine networks.}, number={3}, journal={IEEE Transactions on Mobile Computing}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2016}, month={Mar}, pages={599–609} }
 @article{lin_wang_luo_2016, title={Control traffic balancing in software defined networks}, volume={106}, ISSN={1389-1286}, url={http://dx.doi.org/10.1016/j.comnet.2015.08.004}, DOI={10.1016/j.comnet.2015.08.004}, abstractNote={To promise on-line and adaptive traffic engineering in software defined networks (SDNs), the control messages, e.g., the first packet of every new flow and network traffic statistics, should be forwarded from software defined switches to the controller(s) in a fast and robust manner. As many signaling events and control plane operations are required in SDNs, they could easily generate a significant amount of control traffic that must be addressed together with the data traffic. However, the usage of in-band control channel imposes a great challenge into timely and reliable transmissions of control traffic, while out-band control is usually cost-prohibitive. To counter this, in this paper, the control traffic balancing problem is first formulated as a nonlinear optimization framework with an objective to find the optimal control traffic forwarding paths for each switch in such a way the average control traffic delay in the whole network is minimized. This problem is extremely critical in SDNs because the timely delivery of control traffic initiated by Openflow switches directly impacts the effectiveness of the routing strategies. Specifically, the fundamental mathematical structures of the formulated nonlinear problem and solution set are provided and accordingly, an efficient algorithm, called polynomial-time approximation algorithm (PTAA), is proposed to yield the fast convergence to a near optimal solution by employing the alternating direction method of multipliers (ADMM). Furthermore, the optimal controller placement problem in in-band mode is examined, which aims to find the optimal switch location where the controller can be collocated by minimizing the control message delay. While it is not widely researched except quantitative or heuristic results, a simple and efficient algorithm is proposed to guarantee the optimum placement with regards of traffic statistics. Simulation results confirm that the proposed PTAA achieves considerable delay reduction, greatly facilitating controller’s traffic engineering in large-scale SDNs.}, journal={Computer Networks}, publisher={Elsevier BV}, author={Lin, Shih-Chun and Wang, Pu and Luo, Min}, year={2016}, month={Sep}, pages={260–271} }
 @article{lin_wang_luo_2016, title={Jointly optimized QoS-aware virtualization and routing in software defined networks}, volume={96}, ISSN={1389-1286}, url={http://dx.doi.org/10.1016/j.comnet.2015.08.003}, DOI={10.1016/j.comnet.2015.08.003}, abstractNote={Software Defined Networks (SDNs) have been recognized as the next-generation networking paradigm that decouples the network control plane from the data forwarding plane. A logically centralized controller is responsible for all the control decisions and communication among the forwarding switches. However, current traffic engineering techniques and state-of-the-art routing algorithms do not effectively use the merits of SDNs, such as global centralized visibility, control and data plane decoupling, network management simplification and great computation capability. In this paper, a multi-tenancy management framework is proposed to enable the jointly optimized design of quality-of-services (QoSs)-aware virtualization and routing by tenant isolation and prioritization as well as flow allocation, fulfilling QoS requirements of tenants’ applications. Specifically, a fine-grained network virtualization is first proposed to isolate and prioritize tenants through the design of network and switch hypervisors. Furthermore, a QoS-aware dynamic flow allocation is proposed to enable optimal flow routes selection upon the given network slicing with QoS provisioning. Finally, an adaptive feedback management tool, called QoS-aware Virtualization-enabled Routing (QVR), is proposed to combine virtualization with flow allocation and supports reliable and efficient transmissions with regards of time-varying QoS requirements, network topologies, and traffic statistics. Simulations confirm that QVR achieves much less shared edges, congestion latency, and traffic delay for multiple tenants, thus facilitating virtualization-enabled traffic engineering for multi-tenancy SDNs.}, journal={Computer Networks}, publisher={Elsevier BV}, author={Lin, Shih-Chun and Wang, Pu and Luo, Min}, year={2016}, month={Feb}, pages={69–78} }
 @article{gu_lin_2016, title={Practical timing synchronization for network dynamics in large machine-to-machine networks}, volume={13}, ISSN={1673-5447}, url={http://dx.doi.org/10.1109/cc.2016.7733041}, DOI={10.1109/cc.2016.7733041}, abstractNote={Efficient multi-machine cooperation and network dynamics still remain open that jeopardize great applications in large-scale machine-to-machine (M2M) networks. Among all possible machine cooperation controls, to synchronize tremendous machines in a timing-efficient brings one of the greatest challenge and serves as the foundation for any other network control policies. In this paper, we propose a linear-time synchronization protocol in large M2M networks. Specifically, a closed-form of synchronization rate is provided by developing the statistical bounds of the second smallest eigenvalue of the graph Laplacian matrix. These bounds enable the efficient control of network dynamics, facilitating the timing synchronization in networks. Through a practical study in Metropolis, simulation results confirm our theoretical analysis and provide effective selection of wireless technologies, including Zigbee, Wi-Fi, and cellular systems, with respect to the deployed density of machines. Therefore, this paper successfully demonstrates a practical timing synchronization, to make a breakthrough of network dynamic control in real-world machine systems, such as Internet of Things.}, number={10}, journal={China Communications}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Gu, Lei and Lin, Shih-Chun}, year={2016}, month={Oct}, pages={160–168} }
 @inproceedings{lin_akyildiz_wang_luo_2016, title={QoS-Aware Adaptive Routing in Multi-layer Hierarchical Software Defined Networks: A Reinforcement Learning Approach}, ISBN={9781509026289}, url={http://dx.doi.org/10.1109/scc.2016.12}, DOI={10.1109/scc.2016.12}, abstractNote={Software-defined networks (SDNs) have been recognized as the next-generation networking paradigm that decouples the data forwarding from the centralized control. To realize the merits of dedicated QoS provisioning and fast route (re-)configuration services over the decoupled SDNs, various QoS requirements in packet delay, loss, and throughput should be supported by an efficient transportation with respect to each specific application. In this paper, a QoS-aware adaptive routing (QAR) is proposed in the designed multi-layer hierarchical SDNs. Specifically, the distributed hierarchical control plane architecture is employed to minimize signaling delay in large SDNs via three-levels design of controllers, i.e., the super, domain (or master), and slave controllers. Furthermore, QAR algorithm is proposed with the aid of reinforcement learning and QoS-aware reward function, achieving a time-efficient, adaptive, QoS-provisioning packet forwarding. Simulation results confirm that QAR outperforms the existing learning solution and provides fast convergence with QoS provisioning, facilitating the practical implementations in large-scale software service-defined networks.}, booktitle={2016 IEEE International Conference on Services Computing (SCC)}, publisher={IEEE}, author={Lin, Shih-Chun and Akyildiz, Ian F. and Wang, Pu and Luo, Min}, year={2016}, month={Jun} }
 @article{akyildiz_wang_lin_2016, title={SoftWater: Software-defined networking for next-generation underwater communication systems}, volume={46}, ISSN={1570-8705}, url={http://dx.doi.org/10.1016/j.adhoc.2016.02.016}, DOI={10.1016/j.adhoc.2016.02.016}, abstractNote={Underwater communication systems have drawn the attention of the research community in the last 15 years. This growing interest can largely be attributed to new civil and military applications enabled by large-scale networks of underwater devices (e.g., underwater static sensors, unmanned autonomous vehicles (AUVs), and autonomous robots), which can retrieve information from the aquatic and marine environment, perform in-network processing on the extracted data, and transmit the collected information to remote locations. Currently underwater communication systems are inherently hardware-based and rely on closed and inflexible architectural design. This imposes significant challenges into adopting new underwater communication and networking technologies, prevent the provision of truly-differentiated services to highly diverse underwater applications, and induce great barriers to integrate heterogeneous underwater devices. Software-defined networking (SDN), recognized as the next-generation networking paradigm, relies on the highly flexible, programmable, and virtualizable network architecture to dramatically improve network resource utilization, simplify network management, reduce operating cost, and promote innovation and evolution. In this paper, a software-defined architecture, namely SoftWater, is first introduced to facilitate the development of the next-generation underwater communication systems. More specifically, by exploiting the network function virtualization (NFV) and network virtualization concepts, SoftWater architecture can easily incorporate new underwater communication solutions, accordingly maximize the network capacity, can achieve the network robustness and energy efficiency, as well as can provide truly differentiated and scalable networking services. Consequently, the SoftWater architecture can simultaneously support a variety of different underwater applications, and can enable the interoperability of underwater devices from different manufacturers that operate on different underwater communication technologies based on acoustic, optical, or radio waves. Moreover, the essential network management tools of SoftWater are discussed, including reconfigurable multi-controller placement, hybrid in-band and out-of-band control traffic balancing, and utility-optimal network virtualization. Furthermore, the major benefits of SoftWater architecture are demonstrated by introducing software-defined underwater networking solutions, including the throughput-optimal underwater routing, SDN-enhanced fault recovery, and software-defined underwater mobility management. The research challenges to realize the SoftWater are also discussed in detail.}, journal={Ad Hoc Networks}, publisher={Elsevier BV}, author={Akyildiz, Ian F. and Wang, Pu and Lin, Shih-Chun}, year={2016}, month={Aug}, pages={1–11} }
 @article{lin_chen_2016, title={Statistical QoS Control of Network Coded Multipath Routing in Large Cognitive Machine-to-Machine Networks}, volume={3}, ISSN={2327-4662}, url={http://dx.doi.org/10.1109/jiot.2015.2478435}, DOI={10.1109/jiot.2015.2478435}, abstractNote={Machine-to-machine (M2M) communication enables many applications such as smart grid, vehicular safety, and health care among many others. To achieve ubiquitous data transportation among objects and the surrounding environment, deploying spectrum sharing M2M communications with existing wireless networks is a must. A general large-scale cognitive M2M network (CM2MN), adopting cognitive radio technology, consists of multiradio systems, the primary system (PS), and secondary system(s) with tremendous cooperative cognitive machines, under heterogeneous wireless architecture. For these CM2MNs, due to dynamic spectrum access (DSA) nature, there exists possibly unidirectional opportunistic wireless fading links and thus traditional flow control mechanisms at link level do not fit anymore. Furthermore, effective end-to-end quality-of-service (QoS) control is still required to provide a reliable transportation for such multihop CM2M communications. Facing the above challenges, we propose a novel statistical QoS control mechanism through cooperative relaying, realizing virtual multiple-input and multiple-output (MIMO) communications at session level. In particular, a probabilistic network coded routing algorithm and the statistical QoS guarantee are first proposed to coordinate and cooperate tremendous machines. Next, based on the proposed guarantee and routing algorithm, the statistical QoS control mechanism is designed to enable MIMO communications for the session traffic. Specifically, the diversity mode is used to deal with PS's opportunistic nature and wireless fading, and the spatial multiplexing mode is employed to obtain the maximum end-to-end throughput. Simulation results confirm that under our control solution, the great improvements of end-to-end delay violation probability are obtained, thus practically facilitating network coded multipath routing in large CM2MNs.}, number={4}, journal={IEEE Internet of Things Journal}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2016}, month={Aug}, pages={619–627} }
 @inproceedings{lin_wang_akyildiz_luo_2016, title={Throughput-Optimal LIFO Policy for Bounded Delay in the Presence of Heavy-Tailed Traffic}, ISBN={9781509013289}, url={http://dx.doi.org/10.1109/glocom.2016.7842330}, DOI={10.1109/glocom.2016.7842330}, abstractNote={Scheduling is one of the most important resource allocation for networked systems. Conventional scheduling policies are primarily developed under light-tailed (LT) traffic assumptions. However, recent empirical studies show that heavy-tailed (HT) traffic flows have emerged in a variety of networked systems, such as cellular networks, the Internet, and data centers. The highly bursty nature of HT traffic fundamentally challenges the applicability of the conventional scheduling policies. This paper aims to develop novel throughput-optimal scheduling algorithms under hybrid HT and LT traffic flows, where classic optimal policies (e.g., maximum-weight/backpressure schemes), developed under LT assumption, are not throughput-optimal anymore. To counter this problem, a delay-based maximum-weight scheduling policy with the last-in first-out (LIFO) service discipline, namely LIFO-DMWS, is proposed with the proved throughput optimality under hybrid HT and LT traffic. The throughput optimality of LIFO-DMWS gives that a networked system can support the largest set of incoming traffic flows, while guaranteeing bounded queueing delay to each queue, no matter the queue has HT or LT traffic arrival. Specifically, by exploiting asymptotic queueing analysis, LIFO-DMWS is proved to achieve throughout optimality without requiring any knowledge of traffic statistic information (e.g., the tailness or burstiness of traffic flows). Simulation results validate the derived theories and confirm that LIFO-DMWS achieves bounded delay for all flows under challenging HT environments.}, booktitle={2016 IEEE Global Communications Conference (GLOBECOM)}, publisher={IEEE}, author={Lin, Shih-Chun and Wang, Pu and Akyildiz, Ian F. and Luo, Min}, year={2016}, month={Dec} }
 @article{lin_akyildiz_wang_sun_2015, title={Distributed Cross-Layer Protocol Design for Magnetic Induction Communication in Wireless Underground Sensor Networks}, volume={14}, ISSN={1536-1276}, url={http://dx.doi.org/10.1109/twc.2015.2415812}, DOI={10.1109/twc.2015.2415812}, abstractNote={Wireless underground sensor networks (WUSNs) enable many applications such as underground pipeline monitoring, power grid maintenance, mine disaster prevention, and oil upstream monitoring among many others. While the classical electromagnetic waves do not work well in WUSNs, the magnetic induction (MI) propagation technique provides constant channel conditions via small size of antenna coils in the underground environments. In this paper, instead of adopting currently layered protocols approach, a distributed cross-layer protocol design is proposed for MI-based WUSNs. First, a detailed overview is given for different communication functionalities from physical to network layers as well as the QoS requirements of applications. Utilizing the interactions of different layer functionalities, a distributed environment-aware protocol, called DEAP, is then developed to satisfy statistical QoS guarantees and achieve both optimal energy savings and throughput gain concurrently. Simulations confirm that the proposed cross-layer protocol achieves significant energy savings, high throughput efficiency and dependable MI communication for WUSNs.}, number={7}, journal={IEEE Transactions on Wireless Communications}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lin, Shih-Chun and Akyildiz, Ian F. and Wang, Pu and Sun, Zhi}, year={2015}, month={Jul}, pages={4006–4019} }
 @inproceedings{lin_gu_2015, title={Diversity-Multiplexing Tradeoff in Cognitive Machine-to-Machine Networks}, ISBN={9781479959525}, url={http://dx.doi.org/10.1109/glocom.2015.7417283}, DOI={10.1109/glocom.2015.7417283}, abstractNote={Machine-to-Machine (M2M) communication enables many applications, which require ubiquitous wireless connections among objects and the surrounding environment. A general cognitive M2M network (CM2M) consists of multi-radio systems, involving primary system (PS) and secondary system(s) of cognitive machines under heterogeneous wireless architecture. However, inherited from dynamic spectrum access (DSA) ability of cognitive radio technology, uni- directional opportunistic wireless fading links exist in multi-hop CM2M network and the conventional flow control mechanisms at link level cannot be applied anymore. In many cases, effective end-to-end quality-of-service (QoS) control is also needed to provide reliable data transportation. In addition, emerging multi- user multiple input multiple output (MU-MIMO) technology coherently coordinates the transmission and reception among multiple base stations, leveraging the advantage of MIMO communications based on one-hop physical layer transmission. In this paper, through the exploitation of network coding and MU-MIMO, we develop a novel opportunistic QoS control (OQC) scheme for multi-hop CM2M network. OQC control utilizes the cooperative relaying at session level with the proposed Qos guarantees, realizing diversity-multiplexing tradeoff for session traffic. In particular, the statistical QoS guarantee is first proposed to work with our prior routing design, called SAOR. Furthermore, overlaying the proposed guarantees with the routing algorithm, OQC scheme employs the diversity mode to deal with PS's opportunistic nature and wireless fading, and utilizes the spatial multiplexing mode to obtain the maximum end-to-end throughput. Performance evaluations show the remarkable improvement of end-to-end delay violation probability for cognitive machines' traffic in multi-hop CM2M networks, thus enabling great M2M applications.}, booktitle={2015 IEEE Global Communications Conference (GLOBECOM)}, publisher={IEEE}, author={Lin, Shih-Chun and Gu, Lei}, year={2015}, month={Dec} }
 @inproceedings{xifra porxas_lin_luo_2015, title={QoS-aware virtualization-enabled routing in Software-Defined Networks}, ISBN={9781467364324}, url={http://dx.doi.org/10.1109/icc.2015.7249242}, DOI={10.1109/icc.2015.7249242}, abstractNote={Software-Defined Networking (SDN) has been recognized as the next-generation networking paradigm. It is a fast-evolving technology that decouples the network control plane from the data forwarding plane. A logically centralized controller is responsible for all the control decisions and communication among the forwarding elements. However, current traffic engineering techniques and state-of-the-art routing algorithms do not effectively use the merits of SDNs, such as global centralized visibility, control and data plane decoupling, network management simplification and portability. In this paper, a multi-tenancy management framework is proposed to fulfill the quality-of-services (QoSs) requirements through tenant isolation, prioritization and flow allocation. First, a network virtualization algorithm is provided to isolate and prioritize tenants from different clients. Second, a novel routing scheme, called QoS-aware Virtualization-enabled Routing (QVR), is presented. It combines the proposed virtualization technique and a QoS-aware framework to enable flow allocation with respect to different tenant applications. Simulation results confirm that the proposed QVR algorithm surpasses the conventional algorithms with less traffic congestion and packet delay. This facilitates reliable and efficient data transportation in generalized SDNs. Therefore, it yields to service performance improvement for numerous applications and enhancement of client isolation.}, booktitle={2015 IEEE International Conference on Communications (ICC)}, publisher={IEEE}, author={Xifra Porxas, Alba and Lin, Shih-Chun and Luo, Min}, year={2015}, month={Jun} }
 @article{akyildiz_wang_lin_2015, title={SoftAir: A software defined networking architecture for 5G wireless systems}, volume={85}, ISSN={1389-1286}, url={http://dx.doi.org/10.1016/j.comnet.2015.05.007}, DOI={10.1016/j.comnet.2015.05.007}, abstractNote={One of the main building blocks and major challenges for 5G cellular systems is the design of flexible network architectures which can be realized by the software defined networking paradigm. Existing commercial cellular systems rely on closed and inflexible hardware-based architectures both at the radio frontend and in the core network. These problems significantly delay the adoption and deployment of new standards, impose significant challenges in implementing and innovation of new techniques to maximize the network capacity and accordingly the coverage, and prevent provisioning of truly- differentiated services which are able to adapt to growing and uneven and highly variable traffic patterns. In this paper, a new software-defined architecture, called SoftAir, for next generation (5G) wireless systems, is introduced. Specifically, the novel ideas of network function cloudification and network virtualization are exploited to provide a scalable, flexible and resilient network architecture. Moreover, the essential enabling technologies to support and manage the proposed architecture are discussed in details, including fine-grained base station decomposition, seamless incorporation of Openflow, mobility- aware control traffic balancing, resource-efficient network virtualization, and distributed and collaborative traffic classification. Furthermore, the major benefits of SoftAir architecture with its enabling technologies are showcased by introducing software- defined traffic engineering solutions. The challenging issues for realizing SoftAir are also discussed in details.}, journal={Computer Networks}, publisher={Elsevier BV}, author={Akyildiz, Ian F. and Wang, Pu and Lin, Shih-Chun}, year={2015}, month={Jul}, pages={1–18} }
 @article{lin_gu_chen_2015, title={Statistical Dissemination Control in Large Machine-to-Machine Communication Networks}, volume={14}, ISSN={1536-1276}, url={http://dx.doi.org/10.1109/twc.2014.2376952}, DOI={10.1109/twc.2014.2376952}, abstractNote={Cloud based machine-to-machine (M2M) communications have emerged to achieve ubiquitous and autonomous data transportation for future daily life in the cyber-physical world. In light of the need of network characterizations, we analyze the connected M2M network in the machine swarm of geometric random graph topology, including degree distribution, network diameter, and average distance (i.e., hops). Without the need of end-to-end information to escape catastrophic complexity, information dissemination appears an effective way in machine swarm. To fully understand practical data transportation, G/G/1 queuing network model is exploited to obtain average end-to-end delay and maximum achievable system throughput. Furthermore, as real applications may require dependable networking performance across the swarm, quality of service (QoS) along with large network diameter creates a new intellectual challenge. We extend the concept of small-world network to form shortcuts among data aggregators as infrastructure-swarm two-tier heterogeneous network architecture, then leverage the statistical concept of network control instead of precise network optimization, to innovatively achieve QoS guarantees. Simulation results further confirm the proposed heterogeneous network architecture to effectively control delay guarantees in a statistical way and to facilitate a new design paradigm in reliable M2M communications.}, number={4}, journal={IEEE Transactions on Wireless Communications}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lin, Shih-Chun and Gu, Lei and Chen, Kwang-Cheng}, year={2015}, month={Apr}, pages={1897–1910} }
 @article{akyildiz_lin_wang_2015, title={Wireless Software-defined Networks (W-SDNs) and Network Function Virtualization (NFV) for 5G Cellular Systems: An Overview and Qualitative Evaluation}, volume={93}, journal={Computer Network (Elsevier) Journal}, author={Akyildiz, I.F. and Lin, S.-C. and Wang, P.}, year={2015}, month={Dec}, pages={66–79} }
 @article{lin_chen_2014, title={Improving Spectrum Efficiency via In-Network Computations in Cognitive Radio Sensor Networks}, volume={13}, ISSN={1536-1276}, url={http://dx.doi.org/10.1109/twc.2014.011514.121905}, DOI={10.1109/twc.2014.011514.121905}, abstractNote={To alleviate the spectrum shortage for sensor networks with tremendous sensors, cognitive radio technology enabling multi-hop opportunistic networking and concurrent transmissions overlaying the primary system suggests an attractive facilitation of large-scale wireless sensor networks (WSNs) and machine-to-machine communications. However, subsequent significant end-to-end delay in large WSN can prohibit practical applications. Leveraging the nature of traffic in sensor networks, we develop in-network computation to reduce requisite transmissions and to accommodate more concurrent transmissions under a given spectrum. Specifically, distributed source coding and broadcasting in wireless communication are exploited to build the computational framework and the achievable network capacity is examined. Furthermore, a greedy networking algorithm is adopted to justify significant improvement on end-to-end delay and further statistical QoS guarantee, while yielding considerable system throughput gain for practical deployment of WSNs. Performance evaluations confirm that we successfully demonstrate communication efficiency from in-network computations and facilitate a new paradigm for spectrum efficient cognitive radio networks, which shall be applicable in general multi-hop wireless networks and spectrum-sharing WSNs.}, number={3}, journal={IEEE Transactions on Wireless Communications}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2014}, month={Mar}, pages={1222–1234} }
 @inproceedings{lin_akyildiz_wang_sun_2014, title={Optimal energy-throughput efficiency for magneto-inductive underground sensor networks}, ISBN={9781479940677}, url={http://dx.doi.org/10.1109/blackseacom.2014.6848997}, DOI={10.1109/blackseacom.2014.6848997}, abstractNote={To provide constant channel conditions for a great deal of distributed wireless sensors, magneto-inductive (MI) propagation technique suggests an attractive facilitation of underground sensor networks (USNs) for MI-USNs. However, to put this MI method into practice, a reliable and efficient data transportation is a must to fulfill a pre-defined level of quality of service (QoS). In this paper, a complete study is first given for the different communication functionalities from physical to network layers as well as the QoS requirements of applications. Rather than adopting the currently layered approach, a two-phase cross-layer protocol, called Xlayer, is then proposed to deliver statistical QoS guarantees and obtain both optimal energy savings and throughput gain concurrently. Simulation results conform that Xlayer achieves significant energy savings, high throughput efficiency, and dependable MI communication, thus facilitating a new design paradigm for MI-USNs.}, booktitle={2014 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)}, publisher={IEEE}, author={Lin, Shih-Chun and Akyildiz, Ian F. and Wang, Pu and Sun, Zhi}, year={2014}, month={May} }
 @article{lin_chen_2014, title={Spectrum-Map-Empowered Opportunistic Routing for Cognitive Radio Ad Hoc Networks}, volume={63}, ISSN={0018-9545 1939-9359}, url={http://dx.doi.org/10.1109/tvt.2013.2296597}, DOI={10.1109/tvt.2013.2296597}, abstractNote={Cognitive radio (CR) has emerged as a key technology for enhancing spectrum efficiency by creating opportunistic transmission links. Supporting the routing function on top of opportunistic links is a must for transporting packets in a CR ad hoc network (CRAHN) consisting of cooperative relay multi-radio systems. However, there lacks a thorough understanding of these highly dynamic opportunistic links and a reliable end-to-end transportation mechanism over the network. Aspiring to meet this need, with innovative establishment of the spectrum map from local sensing information, we first provide a mathematical analysis to deal with transmission delay over such opportunistic links. Benefitting from the theoretical derivations, we then propose spectrum-map-empowered opportunistic routing protocols for regular and large-scale CRAHNs with wireless fading channels, employing a cooperative networking scheme to enable multipath transmissions. Simulations confirm that our solutions enjoy significant reduction of end-to-end delay and achieve dependable communications for CRAHNs, without commonly needed feedback information from nodes in a CRAHN to significantly save the communication overhead at the same time.}, number={6}, journal={IEEE Transactions on Vehicular Technology}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2014}, month={Jul}, pages={2848–2861} }
 @inproceedings{lin_2013, title={End-to-end delay reduction via in-network computation in cognitive radio sensor networks}, ISBN={9781479913534}, url={http://dx.doi.org/10.1109/glocom.2013.6831105}, DOI={10.1109/glocom.2013.6831105}, abstractNote={To potentially alleviate the spectrum shortage for sensor networks of tremendous number of nodes, cognitive radio technology, and thus multi-hop opportunistic and concurrent transmissions overlaying with the primary system suggest an attractive facilitation of large-scale sensor networks. However, it is shown to result in significant end-to-end delay to prohibit practical applications. Noting the nature of traffic in sensor networks, with the aid of distributed source coding and broadcasting in wireless communication, we develop in-network computation to reduce requisite transmissions and to accommodate more concurrent transmissions within given spectrum. Without end-to-end table to significantly save control signaling, a greedy networking algorithm schedules traffic among cooperative relay paths and achieves great delay reduction under various communication scenarios. Such in-network computation further suggests a new design paradigm of communication-computation tradeoff in multi-hop cognitive sensor networks and thus machine-to-machine communications.}, booktitle={2013 IEEE Global Communications Conference (GLOBECOM)}, publisher={IEEE}, author={Lin, Shih-Chun}, year={2013}, month={Dec} }
 @inproceedings{gu_lin_chen_2013, title={Small-world networks empowered large machine-to-machine communications}, ISBN={9781467359399 9781467359382 9781467359375}, url={http://dx.doi.org/10.1109/wcnc.2013.6554795}, DOI={10.1109/wcnc.2013.6554795}, abstractNote={Cloud-based machine-to-machine communications emerge to facilitate services through linkage between cyber and physical worlds. In addition to great challenges in a large network of machine/sensor swarm, effective network architecture involving interconnection of wireless infrastructure and multi-hop ad hoc networking in the machine swarm remains open. Inspired by the small-world phenomenon in social networks, we may establish a short-cut path under a heterogeneous network architecture through wireless infrastructure and cloud, by connecting to data aggregators or access points in the machine swarm, such that end-to-end delay can be significantly reduced. Our mathematical analysis on network diameter and average delay, along with verifications by simulations, demonstrate spectral and energy efficiency of our proposed heterogeneous network architecture in large machine-to-machine communication networks.}, booktitle={2013 IEEE Wireless Communications and Networking Conference (WCNC)}, publisher={IEEE}, author={Gu, Lei and Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2013}, month={Apr} }
 @inproceedings{lin_gu_chen_2012, title={Providing statistical QoS guarantees in large cognitive machine-to-machine networks}, ISBN={9781467349413 9781467349420 9781467349406}, url={http://dx.doi.org/10.1109/glocomw.2012.6477841}, DOI={10.1109/glocomw.2012.6477841}, abstractNote={Promising machine-to-machine (M2M) communication emerges to achieve ubiquitous communications among objects and the surrounding environment in everyday life. For a large M2M network to support scrupulous connections among abundant devices, sharing radio resource efficiently with the existing wireless networks while maintaining sufficient quality-of-service (QoS) for reliable communications becomes an essential and challenging requirement. Via social network analysis, we provide mathematical examination on network connectivity and network diameter. Upon such connected M2M networks, an opportunistic transmission protocol is proposed for spectrum-efficient communications by leveraging cognitive radio technology with cooperative communication. Specifically, the cognitive machines can autonomously sense the radio resource usage to mitigate interference and exploit opportunistic relay selection with lower link delay for packet transmissions. Under this protocol, analytical bound of end-to-end delay is derived and the corresponding QoS guaranteed throughput is examined for practical applications. Simulation results confirm that the proposed protocol successfully accommodates statistical QoS guarantees, to facilitate a new paradigm for dependable data transportation in large M2M communication networks.}, booktitle={2012 IEEE Globecom Workshops}, publisher={IEEE}, author={Lin, Shih-Chun and Gu, Lei and Chen, Kwang-Cheng}, year={2012}, month={Dec} }
 @inproceedings{chen_ao_lin_chen_2011, title={Reciprocal spectrum sharing game and mechanism in cellular systems with Cognitive Radio users}, ISBN={9781467300407 9781467300391 9781467300384}, url={http://dx.doi.org/10.1109/glocomw.2011.6162603}, DOI={10.1109/glocomw.2011.6162603}, abstractNote={To fully exploit Cognitive Radio (CR) techniques as secondary transmissions in exiting primary systems (PSs), especially cellular systems, we propose a cooperative spectrum sharing mechanism where CR users serve as relay nodes to enhance PS's performance, and PS leases some portion of resources for CR users' networking services by granting them radio access. Moreover, for CR users exposed to multiple licensed wireless service providers (WSPs), a further complicated spectrum sharing market is formed because not only WSPs compete for relay nodes, but also CR users compete for the released resources. We formulate such reciprocal behaviors as a three-tier game and specify the additional configurations of control channel protocol to achieve the game equilibrium, where WSPs and CR users focus on maximizing their own utility functions. The results show a win-win solution that CR users are able to acquire radio access while enhancing PS's performance, which offers the opportunities and incentive for CR deployments.}, booktitle={2011 IEEE GLOBECOM Workshops (GC Wkshps)}, publisher={IEEE}, author={Chen, Pin-Yu and Ao, Weng Chon and Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2011}, month={Dec} }
 @inproceedings{lin_chen_2010, title={Spectrum Aware Opportunistic Routing in Cognitive Radio Networks}, ISBN={9781424456369}, url={http://dx.doi.org/10.1109/glocom.2010.5683924}, DOI={10.1109/glocom.2010.5683924}, abstractNote={Cognitive radio (CR) emerges as a key technology to enhance spectrum efficiency and thus creates opportunistic transmissions over links. Supporting the routing function on top of numerous opportunistic links is a must to route packets in a general cognitive radio network (CRN) consisting of multi-radio systems. However, there lacks complete understanding of these highly dynamic available links and a reliable end-to-end transportation mechanism over CRN. Aspiring to meet this need, we propose novel spectrum aware opportunistic routing (SAOR) algorithm suited for the CRN under wireless fading channels. With innovative establishment of the spectrum map from local sensing information and the derivation of the routing metric for opportunistic links known as opportunistic link transmission (OLT), the opportunistic path metrics, and the CR node metrics, the promising SAOR employs a cooperative scheme to enable multi-path transmissions and maintains the statistical QoS guaranteed throughput for practical applications. Numerical results confirm that SAOR enjoys less delay with guaranteed throughput, not only in CRN, but also in general wireless network.}, booktitle={2010 IEEE Global Telecommunications Conference GLOBECOM 2010}, publisher={IEEE}, author={Lin, Shih-Chun and Chen, Kwang-Cheng}, year={2010}, month={Dec} }