Control over Distributed Topology of Wire-less Sensor Network based on Power Optimization.

With the rapid development of intelligent manufacturing technology, Wireless Sensor Networks have been widely implemented in increasingly more industries, while gradually getting mature. However, the topology control ability and power consumption have limited their scale and performance for a long time. Therefore, in order to improve the robustness of their network structures and prolong their life cycles, this study explores Energy Network Topology Control based on Power Optimization. A topology structure model of an Energy Network was established based on the graph theory, and certain indicators of network connectivity and energy consumption were adopted as objective functions. Eventually, the problem was transformed into a multi-objective combinational optimization issue. Based on the characters of energy harvesting wireless sensor network, this study also proposed a new Distributed Hybird Strategy Grey Wolf Optimizer algorithm (DHS-GWO). The design of the distributed architecture and addition of parallel search operators greatly improved the solving speed and operation quality of the original GWO algorithm. A distributed protocol was designed to eliminate the conflicts generated in the process of distributed decisions and generate a quasi-global solution. Experimental results proved the effectiveness and competitiveness of the proposed method in terms of performance and running speed. In numerical experiments, the running time of DHS-GWO is decreased by 81.5% on average, and the transmitting power consumption of DHS-GWO is declined by 51.9% on average.