Dynamic Task Scheduling Strategy with Game Theory in Wireless Sensor Networks

Abstract

Task allocation and scheduling is an important typical problem in the area of high performance computing. Unfortunately, the existing traditional solutions to this problem in high performance computing cannot be directly implemented in wireless sensor networks (WSNs) due to the limitations of WSNs such as resource availability and shared communication medium. In this paper, a dynamic task scheduling strategy with the application of the game theory in WSNs is presented. First, an effective parallel alliance generating algorithm is proposed to process the multi-tasks environment. A task allocation algorithm based on the game theory is used to enhance the performance of the network. A novel resource conflict eliminating algorithm is also developed to eliminate the conflicting issues. Finally, the simulation results confirm and reassure the effectiveness of our proposed scheme as we compare with that of the other schema's available in the public domain.