Abstract:

Focusing on the shortcomings of low resource utilization rate,high equipment energy consumption and deterioration of user service quality in the mobile edge computing enhanced heterogeneous cloud radio access network at present,an energy consumption aware communication and computing resource allocation mechanism is proposed from the perspective of spectrum resources and computing resources.First,taking the network throughput as the revenue and energy consumption as the cost expenditure,a profit model framework from the perspective of service providers is established.In order to avoid the waste or overload of edge server resources caused by uneven resource allocation,the network throughput is first improved by analyzing various service requests coming from users and reasonably allocating spectrum resources by using the sparse matrix algorithm.For computing resources,a heuristic algorithm is designed to determine user association and user computing resource demand,so that each edge server can be fully utilized.Based on the results of resource utilization and considering the capacity constraints of the optical fiber forward link,the mobile edge computing server can be dynamically deployed at the macro base station or remote radio heads to reduce the equipment overhead.Simulation results for different parameter indexes and service requests at different times of a day show that the proposed mechanism can effectively increase network throughput,reduce network energy consumption and decrease the blocking probability of the optical fiber forward link,so that this mechanism is apparently superior to other algorithms.

Key words: heterogeneous cloud radio access network, energy saving, mobile edge computing, resource allocation