Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (6A): 240100188-9.doi: 10.11896/jsjkx.240100188

• Network & Communication • Previous Articles     Next Articles

Delay and Energy-aware Task Offloading Approach for Orbit Edge Computing

WANG Zhongxiao1, PENG Qinglan1, SUN Ruoxiao1, XU Xifeng2, ZHENG Wanbo3, XIA Yunni2   

  1. 1 College of Artificial Intelligence,Henan University,Zhengzhou 475004,China
    2 College of Computer Science,Chongqing University,Chongqing 400044,China
    3 Data Science Research Center,Kunming University of Science and Technology,Kunming 650031,China
  • Published:2024-06-06
  • About author:WANG Zhongxiao,born in 2003,His main research interests include orbit edge computing and computation task offloading strategy.
    PENG Qinglan,born in 1994,Ph.D,lecturer,master supervisor.His main research interests include edge computing,service computing,and cloud computing.
  • Supported by:
    National Natural Science Foundation of China(62172062,62162036),Key Research and Development Project of Henan Province(231111211900),Young Scientists Fund of the Natural Science Foundation of Henan Province(242300421700) and Key Scientific Research Projects of Colleges and Universities in Henan Province(24A520005).

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Abstract: The rapid growth of smart devices around the world has created a huge demand for computing resources to sink to the edge,giving rise to the emergence of the edge computing paradigm.At the same time,the demand for computing power in remote areas where computing resources are scarce has driven the concept of orbit edge computing(OEC).In the OEC scenario,users in remote areas can offload computing tasks to edge servers deployed on LEO satellites for processing and execution through the communication link between ground station and satellite and the communication link between satellites in constellation,so as to provide low-latency and high-reliability services for users in remote areas by utilizing satellite computing resources.However,the satellite arithmetic in the OEC scenario is constrained by the limited load and solar energy conversion efficiency,and there is also the limitation of limited available time slots due to highly dynamic satellite-ground connection caused by LEO satellites circling around the earth,which is faced with the challenge of the scarcity of computational resources and the limited available communication latency.Therefore,excellent task offloading decision algorithms are needed to ensure the efficient operation of OEC systems.However,most of the current task offloading approaches for OEC scenario are unable to take into account the delay cost and energy cost when processing tasks,and the traditional approaches also lack the consideration of task diversity.To address the above problems,an adaptive large neighborhood search-based task offloading method for orbit edge computing,OEC-ALNS,is proposed,which takes the task processing cost weighted by task type as the optimization objective,and consists of destruction and repair operators based on the minimization of latency.Experimental results based on Walker Delta LEO satellite constellation and real computing task data show that,compared with the traditional OEC-TA(OEC task allocation)approach,the proposed OEC-ALNS approach could achieve at most 42.22% reduction on the weighted task processing cost and most 42.46% reduction of the average latency cost in OEC scenarios with heterogeneous multiple task sets.

Key words: Orbit edge computing, Low-orbit satellite constellation, Computation task offloading, Adaptive large neighborhood search

CLC Number: 

  • TP311
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