Concurrency and Computation Practice and Experience · 2019 · 14 citations · 36 references
ComputingCloud ComputingComputer ScienceDistributed SystemsEdge ComputingMobile ComputingFog ComputingLatency OptimizationTask OffloadingEdge NodesEquilibriumFog Computing ArchitectureFog OffloadingFog Task OffloadingFog-cloud CollaborationHeterogeneous NetworksUser Satisfaction
Summary With the ever‐increasing popularity of resource‐intensive mobile applications, today, Fog‐to‐Cloud (F2C) computing system becomes a prominent technology for the next generation wireless networks. Despite the benefits of fog computing regarding localized storage and processing, it suffers from restricted power allowance and computational capability of the edge nodes. User nodes also may suffer from extensive delay, especially in offloading periods. Therefore, it is essential to develop a distributed mechanism for users' computation in offloading periods. According to this mechanism, not only the computational servers are exploited at their best capacity but also the users' latency constraints fulfilled. Consequently, this paper develops automated distributed fog computing for computational offloading using the theory of minority game. The proposed scheme achieves user satisfaction latency deadline as well as Quality‐of‐Experience. Moreover, it guarantees an adaptive equilibrium level of F2C computing system, which is suitable for heterogeneous wireless networks.
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