Learning-Based Deadlock-Free Multi-Objective Task Offloading in Satellite Edge Computing With Data-Dependent Constraints and Limited Buffers

Satellite edge computing (SEC) is important for future network deployments because of its global coverage and low-latency computing services. Nevertheless, due to data dependencies among tasks and limited buffers in satellites, a coupling exists between transmission and computation, and undesired de...

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Veröffentlicht in:	IEEE transactions on network science and engineering Jg. 12; H. 1; S. 356 - 368
Hauptverfasser:	Zhang, Ruipeng, Feng, Yanxiang, Yang, Yikang, Li, Xiaoling, Li, Hengnian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Buffers Computation offloading Costs Couplings Edge computing Energy consumption Energy resolution Evolutionary algorithms Internet of Things Machine learning Mixed integer multi-task offloading Multiple objective analysis Nonlinear programming Petri nets Polynomials Real time satellite edge computing Satellite-terrestrial integrated networks Satellites Scheduling algorithms Search process System recovery Traffic control Vectors Windows (intervals)
ISSN:	2327-4697, 2334-329X
Online-Zugang:	Volltext
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