Reliable Multidimensional Resource Scheduling for Heterogeneous Computing Networks via Coded Distributed Computing and Hypergraph Neural Networks

The emergence of 6G applications, such as artificial intelligence, augmented reality, and digital twins has imposed stringent requirements on the high reliability, low latency, and energy efficiency of computing networks. Therefore, in this article, we propose a novel high-reliability resource sched...

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Veröffentlicht in:	IEEE internet of things journal Jg. 12; H. 22; S. 48242 - 48261
Hauptverfasser:	Wang, Weian, Zhu, Xiaorong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 15.11.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial intelligence Augmented reality Cloud computing Coding distributed computing Collaboration Computation offloading Computational modeling computing network Digital twins Distributed computing Distributed processing Energy consumption Graph theory Graphs hypergraph neural network (HGNN) hypernetwork Internet of Things Job shop scheduling Network latency Neural networks Optimization particle swarm algorithm Particle swarm optimization Processor scheduling Reliability Resource allocation Resource management Resource scheduling task offloading (TO)
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
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