This paper investigates distributed edge computing systems powered by hybrid energy sources, where they jointly consider energy consumption from computation, cooling, and power source switching, and proposes an end-to-end solution based on heterogeneous cooperative multi-agent deep reinforcement learning.
Maritime mobile edge computing (MMEC) has emerged as a key enabler for supporting computation-intensive vision applications on uncrewed surface vehicles (USVs). However, volatile maritime channels, heterogeneous computing resources, and mismatched task offloading strategies jointly lead to excessive energy consumption...
Wen-Qian Luo, Yanglong Sun, Wei-Jian Xu et al.· IEEE Transactions on Communi...· 0 citations
With the rapid proliferation of IoT devices and latency‐sensitive applications such as autonomous driving and immersive reality, edge computing has become essential for meeting stringent delay and bandwidth requirements. However, the increasing volume of computation‐intensive tasks, together with resource heterogenei...
Chen-Qian Fang, Xiu-Guo Zhang, Yan-Xing Wen et al.· Concurrency and Computation· 0 citations
Satellite-terrestrial integrated communication and computing network (STICCN) faces the core challenge of supporting highly heterogeneous tasks with differentiated requirements, under stringent dual constraints of communication and computing resources. Most existing scheduling schemes focus on macroscopic system perfor...
JATO is presented, a framework to jointly tackle the problems of adaptive task offloading and transmission optimization using Deep Reinforcement Learning, and offers a mono-faceted solution, learning a policy to simultaneously determine the best offloading target and the transmission quality.
G. Purnama, Irma Amelia Dewi, A. Langi et al.· Journal of ICT Research and...· 0 citations
With the rapid development of Vehicle-to-Everything (V2X) and Vehicular Edge Computing (VEC), the massive computation-intensive tasks generated by intelligent vehicles during driving, including environmental perception, path planning, and autonomous driving decision-making, impose extremely high requirements on real-ti...
Jun Wang, Lin Chai, Yu-Mei Yang et al.· Journal of networking and ne...· 0 citations
This paper investigates a phased sensing-assisted mobile edge computing system composed of multiple unmanned aerial vehicles (UAVs). A framework is proposed to operate in three sequential phases: local user sensing, global state aggregation, and centralized decision making for distributed offloading. To achieve efficie...
