Cost Minimization for Cooperative Computation Framework in MEC Networks

Yijin Pan*, Cunhua Pana, Kezhi Wang*, Huiling Zhu, Jiangzhou Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

In this paper, a cooperative task computation framework exploits the computation resource in user equipments (UEs) to accomplish more tasks meanwhile minimizes the power consumption of UEs. The system cost includes the cost of UEs’ power consumption and the penalty of unaccomplished tasks, and the system cost is minimized by jointly optimizing binary offloading decisions, the computational frequencies, and the offloading transmit power. To solve the formulated mixed-integer non-linear programming problem, three efficient algorithms are proposed, i.e., integer constraints relaxation-based iterative algorithm (ICRBI), heuristic matching algorithm, and the decentralized algorithm. The ICRBI algorithm achieves the best performance at the cost of the highest complexity, while the heuristic matching algorithm significantly reduces the complexity while still providing reasonable performance. As the previous two algorithms are centralized, the decentralized algorithm is also provided to further reduce the complexity, and it is suitable for the scenarios that cannot provide the central controller. The simulation results are provided to validate the performance gain in terms of the total system cost obtained by the proposed cooperative computation framework.

Original languageEnglish
Pages (from-to)3670-3684
Number of pages15
JournalIEEE Transactions on Wireless Communications
Volume20
Issue number6
Early online date27 Jan 2021
DOIs
Publication statusPublished - 1 Jun 2021

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