Research Article
Modeling and Simulation of Computation Offloading at LEO Satellite Constellation Network Edge
@INPROCEEDINGS{10.1007/978-3-030-72795-6_37, author={Junyu Lai and Huidong Tan and Meilin He and Ying Qu and Lei Zhong}, title={Modeling and Simulation of Computation Offloading at LEO Satellite Constellation Network Edge}, proceedings={Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part II}, proceedings_a={SIMUTOOLS PART 2}, year={2021}, month={4}, keywords={Satellite network Edge computing Computation offloading Simulation Performance evaluation}, doi={10.1007/978-3-030-72795-6_37} }- Junyu Lai
Huidong Tan
Meilin He
Ying Qu
Lei Zhong
Year: 2021
Modeling and Simulation of Computation Offloading at LEO Satellite Constellation Network Edge
SIMUTOOLS PART 2
Springer
DOI: 10.1007/978-3-030-72795-6_37
Abstract
Similar to terrestrial networks where edge computing facilities have already been introduced to decrease the user request response delay and to reduce the backhaul bandwidth consumption, low earth orbit (LEO) satellite constellation networks can also be benefited by adopting edge computing technologies. The computation tasks generated by ground users can be offloaded to their accessing LEO satellites to enhance network QoS and user QoE. This paper focuses on modeling and simulating computation offloading at LEO constellation network edge. A one-dimensional networking model for edge computing enabled LEO constellation networks is derived, and on that basis, a Monte Carlo simulator is developed from scratch to evaluate system performance. As a case study, three different computation offloading schemes are elaborated and implemented on the simulator. Comparative evaluation experiments have been conducted and the results indicate that, in resource restricted scenarios, allowing computation offloading to the neighbors of the access satellites can considerably reduce the request blocking probability with only slightly increasing the average request response delay.
