@article{wang_wang_wang_2023, title={Remedy or Resource Drain: Modeling and Analysis of Massive Task Offloading Processes in Fog}, volume={10}, ISSN={["2327-4662"]}, DOI={10.1109/JIOT.2023.3245100}, abstractNote={Task offloading, which refers to processing (computation-intensive) data at facilitating servers, is an exemplary service that greatly benefits from the fog computing paradigm, which brings computation resources to the edge network for reduced application latency. However, the resource-consuming nature of task execution, as well as the sheer scale of IoT systems, raises an open and challenging question: whether fog is a remedy or a resource drain, considering frequent and massive offloading operations? This question is nontrivial, because participants of offloading processes, i.e., fog nodes, may have diversified technical specifications, while task generators, i.e., task nodes, may employ a variety of criteria to select offloading targets, resulting in an unmanageable space for performance evaluation. To overcome these challenges of heterogeneity, we propose a gravity model that characterizes offloading criteria with various gravity functions, in which individual/system resource consumption can be examined by the device/network effort metrics, respectively. Simulation results show that the proposed gravity model can flexibly describe different offloading schemes in terms of application and node-level behavior. We find that the expected lifetime and device effort of individual tasks decrease as <inline-formula> <tex-math notation="LaTeX">$O({}{1}/{N})$ </tex-math></inline-formula> over the network size <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>, while the network effort decreases much slower, even remain <inline-formula> <tex-math notation="LaTeX">$O(1)$ </tex-math></inline-formula> when load balancing measures are employed, indicating a possible resource drain in the edge network.}, number={13}, journal={IEEE INTERNET OF THINGS JOURNAL}, author={Wang, Jie and Wang, Wenye and Wang, Cliff}, year={2023}, month={Jul}, pages={11669–11682} }
 @article{wang_pambudi_wang_wang_2023, title={Toward Fast and Energy-Efficient Access to Cloudlets in Hostile Environments}, volume={22}, ISSN={["1558-2248"]}, DOI={10.1109/TWC.2023.3262311}, abstractNote={Cloudlets, which refer to the edge computing services deployed at the proximity of end devices, are key providers of connectivity, storage, and computation resources to many applications. While access to cloudlets is pervasive in typical settings, it can be difficult in challenging, even hostile environments, such as military or post-disaster scenarios, featuring multi-hop communication and energy-constrained end devices. In these cases, cloudlets may have become the only equipment powerful enough to execute life-critical applications, such as battle-field situation awareness, tactic cooperation, and search-and-rescue missions. Quality of these services is greatly influenced by the minimum time that a packet can be delivered, i.e., the cloudlet access delay (CAD), whose characteristics remain unknown. To address the open question of fast and efficient cloudlet access, we establish a packet mobility model that allows CAD and energy consumption to be analyzed as a function of the initial device-cloudlet distance. We find that the expected CAD scales either linearly or quadratically under distinct types of packet mobility, and the successful access rate (SAR) can be bounded by functions of the delay constraint. Based on these findings, we develop a packet shedding algorithm that saves 24% transmission power, and reduces the average CAD by 2%, while maintaining a similar SAR in simulated cloudlet access environments.}, number={11}, journal={IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS}, author={Wang, Jie and Pambudi, Sigit Aryo and Wang, Wenye and Wang, Cliff}, year={2023}, month={Nov}, pages={8320–8335} }