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Joint Offloading and Resource Allocation for Multi-User Multi-Edge Collaborative Computing System

Zihan Gao, Wanming Hao, Shouyi Yang

2021IEEE Transactions on Vehicular Technology34 citationsDOI

Abstract

In this paper, we consider a computation offloading problem in a three-tier network consisting of multiple mobile users (MUs), multiple edge clouds, and a central cloud. On this basis, we formulate a system Energy Time Cost ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ETC$</tex-math></inline-formula> ) minimization problem by jointly optimizing the resource allocation, mobile-edge matching decision, and offloading decision. Due to the difficulty of directly solving the formulated problem, we decompose it and propose two offloading algorithms, namely Gale-Shapley based Minimum/Sequential Offloading Algorithm (GS-MOA/GS-SOA), to optimize offloading decisions by minimizing the system <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ETC$</tex-math></inline-formula> , in which the mobile-edge matching strategies based on the proposed Gale-Shapley based Mobile-Edge mAtching aLgorithm (GS-MEAL) and resource allocations are optimized iteratively. The simulations show the effectiveness of our proposed algorithm.

Topics & Concepts

Computer scienceMobile edge computingResource allocationCloud computingEnhanced Data Rates for GSM EvolutionComputation offloadingMatching (statistics)Edge computingMathematical optimizationAlgorithmMathematicsArtificial intelligenceComputer networkStatisticsOperating systemIoT and Edge/Fog ComputingAge of Information OptimizationIoT Networks and Protocols