Abstract

Note that the delay of transmission in wireless sensor networks should be constrained within a certain range in most real-time applications. The sensors deliver data to a sink via long distance will exhausts their energy. Thus, a mobile sink, which walks back and forth within the interested region to gather the data collected by the sensors, is regarded as an effective method to ensure data gathering from monitoring sensor nodes to the mobile sink within a short communication range. In this paper, a novel virtual force-based data aggregation mechanism with mobile sink in wireless sensor networks is proposed. Firstly, a hierarchical hybrid of genetic algorithm and particle swarm optimization for distributed clustering is introduced and the whole area is divided into several grids. Secondly, the virtual force theory is adopted to calculate the virtual repulsive force of boundary, obstacles and empty area, and the virtual attractive force of the sensor nodes without being traversed. By combining all virtual forces in according with direction vectors, the residence time for mobile sink and the coordinate of the next rendezvous point can be calculated based on the force size, direction and the number of adjacent clusters. The optimal moving trajectory of sink node is then obtained to achieve high efficiency and energy saving. Consequently, the data aggregation tree can be dynamically constructed for data gathering. Finally, mobile sink node moves along the rendezvous points to aggregate the data from sensor nodes within the communication range according to the selected moving path. Simulation results show that the proposed mechanism can obtain better performance than existing algorithms in aspects of efficient data aggregation, energy saving and the path length of mobile sink.

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