Quantum-behaved PSO Algorithm Applying In Internet Of Things

Wireless sensor network(WSN) is an energy limited network. Completing the coverage control with minimal energy consumption is the key issue of designing WSN. As the wireless sensor network nodes are many ,more difficult to replenish their energy and deployment environment is complex, this may make the lifetime of network to be short and relatively low coverage rate. Therefore ,it is necessary to adopt some coverage control strategy to ensure sensor nodes can cover the monitoring areas efficiently.Wireless sensor network coverage control is essentially a kind of constrained optimization problem. The optimization goal is to ensure the quality of sensor network coverage while minimizing the network energy consumption, thus extending the life of network. AFSA has a good ability to overcome the local extremum and obtain good global extremum. But with the complexity and size of optimization problem continues to expand, AFSA has a slowly convergence rate in the late and difficult to obtain accurate optimal solution, only can find a satisfactory solution domain. QPSO has a faster convergence rate, but all the particles are moving to the optimal direction, it makes particles tending to homogenization. It makes the algorithm easy to fall into local optimum and post-shock easily, it will cause precocious phenomenon and evolution stagnation. Hybrid algorithm with AFSA and QPSO combine the advantages of both AFSA and QPSO, it makes the mixture algorithm not only have the quick local search speed, but also have the global convergence.This make it more applicable to the convergence optimization control problem of wireless sensor network. The main work in this paper includes:(1) Based on the research of AFSA and QPSO, we proposed the fish swarm and particle swarm hybrid algorithm, this algorithm combines the advantage of artificial fish swarm algorithm and Quantum-behaved particle swarm algorithm, and ensures the global convergence while improves the local search speed and result's precision of the algorithm, this make the algorithm more effectively in solving complex combinatorial optimization problems.(2) To the wireless sensor network which the nodes are fixed. And proposing the calculation formula which solves the coverage rate problem of the static sensor network by using of point coverage approximate the regional coverage, while provides the objective function of coverage optimization control. It has proved that this algorithm optimize the coverage control of wireless sensor network by experiment.(3) In the wireless sensor network which contains mobile nodes. In virtual force-directed algorithm, the mobile nodes can not jump from the virtual shackle of the static nodes .This makes the mobile nodes hard to make up the problem of coverage hole. While this algorithm also does not consider the energy heterogeneous problem of mobile node. This paper proposes a multi fish parallel coverage optimization strategy, making the network not only maximize the network coverage but also can balance the consumption of the node.