A highly efficient and multi-objective optimal DAG scheduling algorithm for wireless sensor networks based on PSO

Abstract

In order to increase the lifetime of entire wireless sensor network, the task scheduling in the network demands to achieve as far as possible the shortest task completion time, the lowest level of energy consumption and the highest level of balanced use of energy under condition of limitation in energy of nodes. Therefore, traditional multiprocessor Directed Acyclic Graph (DAG) scheduling algorithm can not be directly applied to sensor task scheduling. This paper proposes a Multi-objective Optimal DAG Scheduling (MODAGS) algorithm for wireless sensor networks. Its central idea is to exploit heuristic optimization algorithms and strategies respectively to realize multi-objective optimization in the task scheduling of wireless sensor networks. Then, take those results of single-objective optimal task scheduling as the initial particle swarm in the Particle Swarm Optimization (PSO) algorithm. By way of redefinition of operations in the PSO algorithm, the task scheduling in wireless sensor networks is optimized synthetically. Experimental results show that: combining heuristic optimization algorithm with bionic algorithm, the optimization technology has good realtime performance and high efficiency of energy.