4.6 Article

Computation Offloading and Resource Allocation for the Internet of Things in Energy-Constrained MEC-Enabled HetNets

期刊

IEEE ACCESS
卷 8, 期 -, 页码 47509-47521

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2979774

关键词

Task analysis; Resource management; Energy consumption; Interference; Servers; Delays; Computational modeling; MEC enabled HetNets; computation offloading; resource allocation; Internet of Things

资金

  1. National High Technology Research and Development of China 863 Program [2014AA01A701]
  2. Beijing Natural Science Foundation [414142049]
  3. National Natural Science Foundation of China [51507063]
  4. Fundamental Research Funds for the Central Universities [2019QN103]

向作者/读者索取更多资源

In this paper, we present our investigation of a latency-minimization offloading problem for internet of things (IoT) terminals in multiple access edge computing (MEC)-enabled heterogeneous networks (HetNets), which jointly optimizes computation and communication resource allocation. Different from related works, the inter-user interferences caused by computation offloading demonstrate effective management in this paper. We also consider the limited battery capacity for IoT terminals for an energy-limited network. Then, we formulate a joint computation offloading and resource allocation optimization problem to minimize the weight-sum delay of users under the constraint of inter-user interference and energy consumption. Since the problem we formulated is a mixed integer non-linear programming (MINLP) problem, the optimal solution can't be easily obtained. Thus, we decompose the problem into multiple sub-problems. First, we obtain the optimal close solution for local CPU frequencies for each user. Then we propose a low complexity algorithm by using the CVX tool and the successive convex approximation approach (SCA). Finally, we propose a distributed computation offloading algorithm. The simulation results compare the performance of the proposed offloading scheme with different algorithms. We also analyze the influence of network parameters on the network latency and obtain some interesting conclusions.

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