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Energy-Efficient Computation Peer Offloading in Satellite Edge Computing Networks
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DOI：10.1109/TMC.2023.3269801.png)
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摘要
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Recently, MEC has been integrated with satellite networks to process remote terrestrial computation tasks with superior coverage and delay. Since single satellite computation is hard to tackle spatially uneven computation workloads, computation peer offloading among multiple satellites is urgently needed to further improve service quality and resource utilization. However, considering limited resources, deficient energy, and costly overheads of communication and computation, how to enable efficient offloading cooperation in the time-varying satellite networks is a significant challenge. In this paper, we first design a satellite peer offloading scheme, where offloading is performed along multi-hop paths to explore collaborative computing capabilities. Second, we formulate the Multi-Hop Satellite Peer offloading (MHSPO) problem, aiming to jointly minimize the delay and energy consumption under system resources and backlog constraints. Then, to adapt to the network dynamics, the decision-making process with uncertain future workloads is optimized by leveraging the delayed online learning method under the Lyapunov framework. Finally, we develop a practical online distributed algorithm to solve the MHSPO problem, which is proven to achieve close-to-optimal performance. Extensive simulations show that multi-hop peer offloading among satellites improves edge computing performance efficiently.
Keyword:
Satellites
Task analysis
Energy consumption
Delays
Computational modeling
Peer-to-peer computing
Edge computing
Satellite networks
edge computing
load balancing
energy efficiency
peer-to-peer offloading
期刊
IF:
9.2
论文数:
5.9K
被引数:
1.8W
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Computing over Space-Air-Ground Integrated Networks: Challenges and Opportunities空间-空中-地面综合网络上的计算: 挑战与机遇.png)
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