@article{shukla_an_chakrabortty_duel-hallen_2022, title={A Robust Stackelberg Game for Cyber-Security Investment in Networked Control Systems}, volume={9}, ISSN={["1558-0865"]}, url={https://doi.org/10.1109/TCST.2022.3207671}, DOI={10.1109/TCST.2022.3207671}, abstractNote={We present a resource-planning game for cyber-security of networked control systems (NCSs). The NCS is assumed to be operating in closed loop using a linear state feedback $\mathcal {H}_{2}$ -controller. A zero-sum, two-player Stackelberg game (SG) is developed between an attacker and a defender for this NCS. The attacker aims to disable communication of selected nodes and thereby render the feedback gain matrix to be sparse, leading to degradation of closed-loop performance, while the defender aims to prevent this loss by investing in the protection of targeted nodes. Both the players trade their $\mathcal {H}_{2}$ -performance objectives for the costs of their actions. The standard backward induction (BI) method is modified to determine a cost-based Stackelberg equilibrium (CBSE) that saves the players’ costs without degrading the control performance. We analyze the dependence of a CBSE on the relative budgets of the players and on the node “importance” order. Moreover, a robust defense (RD) method is developed for the realistic case when the defender is not informed about the attacker’s resources. The proposed algorithms are validated using examples from wide-area control of electric power systems. It is demonstrated that reliable and RD is feasible unless the defender’s resources are severely limited relative to the attacker’s resources. We also show that the proposed methods are robust to time-varying model uncertainties and thus are suitable for long-term security investment in realistic NCSs. Finally, we use computationally efficient genetic algorithms (GAs) to compute the optimal strategies of the attacker and the defender in realistic large power systems.}, journal={IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY}, author={Shukla, Pratishtha and An, Lu and Chakrabortty, Aranya and Duel-Hallen, Alexandra}, year={2022}, month={Sep} }
 @inproceedings{an_tu_liu_akkiraju_2022, title={Real-time Statistical Log Anomaly Detection with Continuous AIOps Learning}, url={http://dx.doi.org/10.5220/0011069200003200}, DOI={10.5220/0011069200003200}, abstractNote={: Anomaly detection from logs is a fundamental Information Technology Operations (ITOps) management task. It aims to detect anomalous system behaviours and find signals that can provide clues to the reasons and the anatomy of a system’s failure. Applying advanced, explainable Artificial Intelligence (AI) models throughout the entire ITOps is critical to confidently assess, diagnose and resolve such system failures. In this paper, we describe a new online log anomaly detection algorithm which helps significantly reduce the time-to-value of Log Anomaly Detection. This algorithm is able to continuously update the Log Anomaly Detection model at run-time and automatically avoid potential biased model caused by contaminated log data. The methods described here have shown 60% improvement on average F1-scores from experiments for multiple datasets comparing to the existing method in the product pipeline, which demonstrates the efficacy of our proposed methods.}, booktitle={Proceedings of the 12th International Conference on Cloud Computing and Services Science}, publisher={SCITEPRESS - Science and Technology Publications}, author={An, Lu and Tu, An-Jie and Liu, Xiaotong and Akkiraju, Rama}, year={2022}, month={Apr} }
 @inproceedings{an_chakrabortty_duel-hallen_2020, title={A Stackelberg Security Investment Game for Voltage Stability of Power Systems}, url={http://dx.doi.org/10.1109/cdc42340.2020.9304301}, DOI={10.1109/cdc42340.2020.9304301}, abstractNote={We formulate a Stackelberg game between an attacker and a defender of a power system. The attacker attempts to alter the load setpoints of the power system covertly and intelligently, so that the voltage stability margin of the grid is reduced, driving the entire system towards a voltage collapse. The defender, or the system operator, aims to compensate for this reduction by retuning the reactive power injection to the grid by switching on control devices, such as a bank of shunt capacitors. A modified Backward Induction method is proposed to find a cost-based Stackelberg equilibrium (CBSE) of the game, which saves the players’ costs while providing the optimal allocation of both players’ investment resources under budget and covertness constraints. We analyze the proposed game extensively for the IEEE 9-bus power system model and present an example of its performance for the IEEE 39-bus power system model. It is demonstrated that the defender is able to maintain system stability unless its security budget is much lower than the attacker’s budget.}, booktitle={2020 59th IEEE Conference on Decision and Control (CDC)}, publisher={IEEE}, author={An, Lu and Chakrabortty, Aranya and Duel-Hallen, Alexandra}, year={2020}, month={Dec}, pages={3359–3364,} }
 @article{an_duan_chow_duel-hallen_2019, title={A Distributed and Resilient Bargaining Game for Weather-Predictive Microgrid Energy Cooperation}, volume={15}, ISSN={["1941-0050"]}, url={https://doi.org/10.1109/TII.2019.2907380}, DOI={10.1109/TII.2019.2907380}, abstractNote={A bargaining game is investigated for cooperative energy management in microgrids. This game incorporates a fully distributed and realistic cooperative power scheduling algorithm [cooperative and distributed energy scheduling (CoDES)] as well as a distributed Nash bargaining solution based method of allocating the overall power bill resulting from CoDES. A novel weather-based stochastic renewable generation (RG) prediction method is incorporated in the power scheduling. We demonstrate the proposed game using a four-user grid-connected microgrid model with diverse user demands, storage, and RG profiles and examine the effect of weather prediction on day-ahead power scheduling and cost/profit allocation. Finally, the impact of users’ ambivalence about cooperation and /or dishonesty on the bargaining outcome is investigated, and it is shown that the proposed game is resilient to malicious users’ attempts to avoid payment of their fair share of the overall bill.}, number={8}, journal={IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={An, Lu and Duan, Jie and Chow, Mo-Yuen and Duel-Hallen, Alexandra}, year={2019}, month={Aug}, pages={4721–4730} }
 @inproceedings{an_duan_zhang_chow_duel-hallen_2017, title={Distributed multi-step power scheduling and cost allocation for cooperative microgrids}, url={http://dx.doi.org/10.1109/pesgm.2017.8273909}, DOI={10.1109/pesgm.2017.8273909}, abstractNote={Microgrids are self-sufficient small-scale power grid systems that can employ renewable generation sources and energy storage devices and can connect to the main grid or operate in a stand-alone mode. Most research on energy-storage management in microgrids does not take into account the dynamic nature of the problem and the need for fully-distributed, multi-step scheduling. First, we address these requirements by extending our previously proposed multi-step cooperative distributed energy scheduling (CoDES) algorithm to include both purchasing power from and selling the generated power to the main grid. Second, we model the microgrid as a multi-agent system where the agents (e.g. households) act as players in a cooperative game and employ a distributed algorithm based on the Nash Bargaining Solution (NBS) to fairly allocate the costs of cooperative power management (computed using CoDES) among themselves. The dependency of the day-ahead power schedule and the costs on system parameters, e.g., the price schedule and the user activity level (measured by whether it owns storage and renewable generation devices), is analyzed for a three-agent microgrid example.}, booktitle={2017 ieee power & energy society general meeting}, publisher={IEEE Power & Energy Society General Meeting}, author={An, Lu and Duan, J. and Zhang, Y. and Chow, M. Y. and Duel-Hallen, A.}, year={2017}, pages={1–5} }
 @article{zhang_zhao_an_liu_2016, title={Energy Efficiency of Base Station Deployment in Ultra Dense HetNets: A Stochastic Geometry Analysis}, volume={5}, ISSN={["2162-2345"]}, DOI={10.1109/lwc.2016.2516010}, abstractNote={Ultra dense heterogeneous networks (HetNets), which involve densely deployed small cells underlaying traditional macro cellular networks, will be an enabling solution for extremely high data rate communications. However, the dense deployment of small cell base stations (BSs) inevitably triggers a tremendous escalation of energy consumption. In this letter, we investigate the impact of BS deployment, especially BS density on energy efficiency in ultra dense HetNets using the stochastic geometry theory. The minimum achievable data rate in terms of the traffic load in each tier is characterized, and then the minimum achievable throughput of the whole HetNets is obtained. Finally, the closed-form energy efficiency with respect to the BS deployment is derived. The simulation validates the accuracy of the theoretical analysis, and demonstrates that the energy efficiency maximization can be achieved by the optimized BS deployment.}, number={2}, journal={IEEE WIRELESS COMMUNICATIONS LETTERS}, author={Zhang, Tiankui and Zhao, Jiaojiao and An, Lu and Liu, Dantong}, year={2016}, month={Apr}, pages={184–187} }
 @inproceedings{stochastic geometry based energy-efficient base station density optimization in cellular networks_2015, url={http://dx.doi.org/10.1109/wcnc.2015.7127709}, DOI={10.1109/wcnc.2015.7127709}, abstractNote={In the research of green networks, considering the base station (BS) density from the perspective of energy efficiency is very meaningful for both network deployment and BS sleeping based power saving. In this paper, we optimize the BS density for energy efficiency in cellular networks by the stochastic geometry theory. First, we model the distribution of base stations and user equipment (UE) as spatial Poisson point process (PPP). Based on such model, we derive the closed-form expressions of the average achievable data rate, the network energy consumption and the network energy efficiency with respect to the network load. Then, we optimize the BS density for network energy efficiency maximization by adopting the Newton iteration method. Our study reveals that we can improve the network energy efficiency by deploying the suitable amount of BSs or switching on/off proportion of the BSs according to the network load. The simulation results validate the theoretical analysis, and show that when the right amount of BSs is deployed according to the network load, the network energy efficiency can be maximized and the maximum energy efficiency is a fixed value once the network parameters are given.}, booktitle={2015 IEEE Wireless Communications and Networking Conference (WCNC)}, year={2015}, month={Mar} }
 @inproceedings{aggregate interference statistical modeling and user outage analysis of heterogeneous cellular networks_2014, url={http://dx.doi.org/10.1109/icc.2014.6883494}, DOI={10.1109/icc.2014.6883494}, abstractNote={The heterogeneous cellular networks (HCNs) will be the typical layout of the next generation mobile networks. Understanding the aggregate interference from multi-tier heterogeneous base stations (BSs) of HCNs is the key for research on network deployment and interference management. In this paper, we propose a statistical model for quantifying the aggregate interference in HCNs and evaluating its impact on system performance. We first model the distribution of multitier heterogeneous BSs as spatial Poisson point process and derive the characteristic function (CF) of the downlink aggregate interference for a specific target user. We review the CF of single-tier network interference and proof that the aggregate interference of HCNs follows the stable distribution, based on which, we derive statistical characterization of aggregate interference amplitude and power, respectively. Then, we propose an aggregate interference statistical model based on truncated-stable distribution. Finally, the users outage probability of the HCNs is analysed via the proposed model. The proposed model is validated with simulation. This work provides essential understanding of interference of HCNs and gives insights which can facilitate system performance analysis and interference management.}, booktitle={2014 IEEE International Conference on Communications (ICC)}, year={2014}, month={Jun} }
 @inproceedings{an_zou_liu_hu_niu_2014, title={An analytical model for TDMA-based MAC protocols in VANETs}, url={http://dx.doi.org/10.1109/wpmc.2014.7014889}, DOI={10.1109/wpmc.2014.7014889}, abstractNote={The design of reliable and adaptive Medium Access Control (MAC) protocol is of crucial importance in the actual emergence of vehicular ad hoc networks (VANETs). Time Division Multiple Access (TDMA) based MAC protocol is promising for VANETs as many works have proven that it can provide reliable broadcast services without hidden terminal problem when properly designed. However, the high vehicle mobility, dynamic traffic density and changeable network topology make the TDMA scheduling very difficult. Therefore, the performance of TDMA-based MAC mechanism needs in-depth evaluation. In this paper, three performance metrics for TDMA protocols in VANETs, namely the average reservation delay, slot utility ratio and slot available duration, are introduced and evaluated analytically and by simulations. The expressions of these metrics are derived taking the impact of vehicle mobility and different network parameters such as transmission range, the number of available time slots, the traffic density, vehicle moving speed into account. The proposed analytical model is applied for two existing TDMA based protocols, ADHOC MAC and VeMAC, and the theoretical results are coherent with the simulation results. As a result, some important observations are obtained for the future design and enhancement of TDMA protocols.}, booktitle={2014 International Symposium on Wireless Personal Multimedia Communications (WPMC)}, publisher={IEEE}, author={An, Lu and Zou, Rui and Liu, Zishan and Hu, Zhirui and Niu, Qin}, year={2014}, month={Sep} }
 @inproceedings{zhu_zeng_zhang_an_xiao_2014, title={An energy efficient user association scheme based on cell sleeping in LTE heterogeneous networks}, url={http://dx.doi.org/10.1109/wpmc.2014.7014794}, DOI={10.1109/wpmc.2014.7014794}, abstractNote={The cell sleeping scheme is an efficient method for power saving in the cellular networks. The LTE heterogeneous network (HetNet) with mixed macro cells and small cells is considered in this paper, and we propose an energy efficient user association scheme based on cell sleeping of small cell networks. Given that some of the base stations in the HetNet can be switched off (cell sleeping) along with the dynamic traffic load, the optimization problem of user association for energy efficiency maximization is formulated. Then a Quantum particle swarm optimization (QPSO) based user association scheme is proposed to give a sub-optimal solution for the user association optimization problem. Based on this sub-optimal solution, the small cell without user association will be switched off. We evaluated the network performance of power consumption, spectrum efficiency and energy efficiency by simulation. The results indicate that the proposed scheme can improve the energy efficiency of small cell networks, especially in the low traffic load condition.}, booktitle={2014 International Symposium on Wireless Personal Multimedia Communications (WPMC)}, publisher={IEEE}, author={Zhu, Yutao and Zeng, Zhimin and Zhang, Tiankui and An, Lu and Xiao, Lin}, year={2014}, month={Sep} }
 @inproceedings{joint optimization for base station density and user association in energy-efficient cellular networks_2014, url={http://dx.doi.org/10.1109/wpmc.2014.7014796}, DOI={10.1109/wpmc.2014.7014796}, abstractNote={In the research of green networks, considering the base station (BS) density from the perspective of energy efficiency is very meaningful for both network deployment and BS sleeping based power saving. In this paper, we optimize the BS density for energy efficiency in cellular networks by the stochastic geometry theory and optimize the user association matrix by the Quantum Particle Swarm Optimization (QPSO). On one hand, we model the distribution of base stations and user equipment (UE) as spatial Poisson point process (PPP). Based on such model, we derive the closed-form expressions of the average achievable data rate, the network energy consumption and the network energy efficiency with respect to the network load. Then, we optimize the BS density for network energy efficiency maximization by adopting the Newton iteration method. On the other hand, we build a user association matrix to present the connection state between BSs and UEs, and then optimize it by QPSO. Our study reveals that we can improve the network energy efficiency by switching on/off proportion of the BSs according to the network load. The simulation results validate the theoretical analysis, and show that when the right amount of BSs is deployed according to the network load, the network energy efficiency can be maximized and the maximum energy efficiency is a fixed value once the network parameters are given.}, booktitle={2014 International Symposium on Wireless Personal Multimedia Communications (WPMC)}, year={2014}, month={Sep} }