Resource allocation in D2D based mobile edge computing system for applications in rural areas

With the development with 5G the mobile connectivity in rural areas has increased. The use of artificial intelligence (AI) and internet of things (IOT) has increased its horizon in some applications like Agriculture, Dam monitoring etc. This high computation application requires high computation capacity and low latency. A multi-hop mobile edge computation with D2D communication (MECD2D) has been proposed. The resource allocation has been performed using improved artificial bee colony optimization algorithm (IABCO). It aims at minimizing overall cost of computation by reducing energy consumption and optimizing number of idle users for computation offloading. The simulation results shows that the proposed algorithm performs better as compared to the Kuhn Munkres algorithm. The performance is improved by 2% in terms of energy consumption and 32-48% in terms of resource consumption.