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Volume 41 Issue 5
Apr.  2019
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Haibo ZHANG, Hu LI, Shanxue CHEN, Xiaofan HE. Computing Offloading and Resource Optimization in Ultra-dense Networks with Mobile Edge Computation[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1194-1201. doi: 10.11999/JEIT180592
Citation: Haibo ZHANG, Hu LI, Shanxue CHEN, Xiaofan HE. Computing Offloading and Resource Optimization in Ultra-dense Networks with Mobile Edge Computation[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1194-1201. doi: 10.11999/JEIT180592

Computing Offloading and Resource Optimization in Ultra-dense Networks with Mobile Edge Computation

doi: 10.11999/JEIT180592
Funds:  The National Natural Science Foundation of China (61771084, 61601071), The Foundation for Changjiang Scholars and Innovative Research Team in University (IRT16R72), The Basic Research and Frontier Exploration Projects in Chongqing (cstc2018jcyjAX0463)
  • Received Date: 2018-06-13
  • Rev Recd Date: 2019-01-21
  • Available Online: 2019-02-14
  • Publish Date: 2019-05-01
  • Mobile Edge Computing (MEC) improves the quality of users experience by providing users with computing capabilities at the edge of the wireless network. However, computing offloading in MEC still faces some problems. In this paper, a joint optimization problem of offloading decision and resource allocation is proposed for the computation offloading problem in Ultra-Dense Networks (UDN) with MEC. To solve this problem, firstly, the coordinate descent method is used to formulate the optimization scheme for the offloading decision. Meanwhile, the improved Hungarian algorithm and greedy algorithm are used to allocate the channels to meet the user’s delay requirements. Finally, the problem of minimizing energy consumption is converted into a problem of minimizing power. Then it is converted into a convex optimization problem to get the user’s optimal transmission power. Simulation results show that the proposed scheme can minimize the energy consumption of the system while satisfying the users’ different delay requirements, and improve effectively the performance of the system.

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