A quantum-inspired evolutionary algorithm based clustering method for wireless sensor networks

How to prolong the lifetime of a wireless sensor network (WSN) has been a critical research issue because most of the sensors in this kind of network environment have a characteristic that the lifespan of batteries is short; thus, the energy consumption of each sensor has to be as low as possible. The number of sensors in a WSN can easily grow up to tens of thousands. In that case, the lifetime optimization will become a difficult problem. This paper presents a quantum-inspired evolutionary algorithm to improve the performance of the low energy adaptive clustering hierarchy (LEACH). Experimental results show that the proposed algorithm can provide a result that is about 12% better than LEACH, in terms of the energy consumed.