摘要：One of the most important issues in wireless sensor network programming is to assign a set of tasks to a set of nodes with limited energy resources in order to minimize energy consumption. In this paper, we develop a task assignment model where cost function is formulated as a sum of computation and communication energy spent in the network. The model employs task placement constraints that ensure expected lifetime of individual node. We propose an efficient genetic algorithm with repair operator to obtain a minimal cost solution. The repair operator guarantees valid task assignments that meet model constraints as candidate solutions are generated during the process of evolution. Experiments reveal that provided heuristic takes a reasonable amount of time to produce near optimal results. http://dx.doi.org/10.5755/j01.itc.40.4.984
其他摘要：One of the most important issues in wireless sensor network programming is to assign a set of tasks to a set of nodes with limited energy resources in order to minimize energy consumption. In this paper, we develop a task assignment model where cost function is formulated as a sum of computation and communication energy spent in the network. The model employs task placement constraints that ensure expected lifetime of individual node. We propose an efficient genetic algorithm with repair operator to obtain a minimal cost solution. The repair operator guarantees valid task assignments that meet model constraints as candidate solutions are generated during the process of evolution. Experiments reveal that provided heuristic takes a reasonable amount of time to produce near optimal results.http://dx.doi.org/10.5755/j01.itc.40.4.984
