Using Grasshopper Optimization Algorithm to Solve 0-1 Knapsack Computation Resources Allocation Problem in Mobile Edge Computing

Abstract

In a mobile edge computing (MEC) system, the MEC server can’t provide sufficient computation resources to support the offloading operations of all concurrent tasks from many mobile devices. In this case, the computation resources of MEC server should be allocated to those important tasks. This paper establishes a computation resources allocation model based on 0-1 knapsack problem, and proposes a grasshopper optimization algorithm for computation resources allocation (GOA-CRA). On the basis of the novel binary grasshopper optimization algorithm (NBGOA), the proposed GOA-CRA adds a position correction step where three strategies (i.e., random correction, maximum correction and minimum correction) are realized, respectively. A series of numerical experiments are investigated among these three correction strategies. The results indicate that the proposed GOA-CRA is an effective and efficient algorithm for computation resources allocation problem in MEC system.