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Task Offloading in Terrestrial-Support-Free Multi-Layer Multi-Access Edge Computing
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AI
DOI：10.1109/MCOM.001.2300020.png)
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Abstract
En 中文
The article investigates aerial computing terrestrial-support-free multi-layer multi-access edge computing (AC-TMMEC) systems within the context of massive machine-type communications (mMTC) beyond 5G (B5G). With its four layers, namely space platform (S), high-altitude platform (HAP), low-altitude platform (LAP), and ground mobile access point platform (G), task offloading of ground users takes place in a sparsely distributed and dynamic environment mainly due to the high mobility of the AC-TMMEC entities. The article begins by reviewing the state-of-the-art, then identifies data routing and trajectory planning as new challenges in the design of AC-TMMEC offloading schemes. A simple yet effective task offloading scheme under AC-TMMEC, called iterative maximum flow algorithm (IMFA), is introduced, aiming to jointly solve the problems of source-destination pairing and data routing in a single shot via iterative maximum flow search. Extensive case studies are conducted to gain insights on the offloading latency performance of the proposed IMFA and compare it with a couple of counterparts with respect to two key parameters, namely the number of task requests and data size of each request.
Keywords:
Surveys
Space vehicles
Multi-access edge computing
Trajectory planning
Routing
Search problems
Iterative methods
Journal
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