Research On Routing Protocol Based On The Strategies Of Dividing Space And Co-evolution In Wireless Sensor Networks

Wireless Sensor Networks(WSN) are composed of a large number of sensor nodes, which are limited in many aspects, such as energy, storage and computing capacities. But these nodes can cooperate with each other and send the sensing data to the Sink node by wireless communication. It has been widely applied in the military defense, environmental observation, health and underwater monitoring. Sensor nodes are usually powered by micro-battery and often deployed in the danger environment. Once their energy was depleted, it was difficult to power them in time. So how to set up the effective energy policy has become the key technology in the routing protocol research of wireless sensor network. But an efficient, energy-saving routing protocol not only should take the energy consumption of a single node into consideration, but also should consider the load-balancing of the entire network for maximizing the network lifetime.This paper carries out the in-depth research on the problems of energy control and network load balance in wireless sensor networks routing protocols for improving network performance. On one hand, the strategies of establishing the routing path and maintaining network load balance are proposed for WSN routing protocol in the two-dimensional situation. On the other hand, a multi-path routing based on three-dimensional space is proposed. And the simulations are conducted for them. The main work and results in this paper as follows:Firstly, the strategy of establishing the routing path under the two-dimensional situation is proposed. A new multi-population co-evolutionary Genetic algorithm(MPCCGA) is designed based on to the multi-population co-evolution(CCA) and the unit communication model of nodes. The one hop neighboring space of current node is divided into several sub-spaces. A new fitness function is proposed to select the local best individual in each sub-space. In order to select the best individual of the whole space, the former local optimum individual is weighted to accelerate the convergence speed toward to the Sink node. The global best individuals in every generation make contributions to the optimal path from the source node to the Sink node, and the suboptimal are composed by the other local sub-optimal individuals in each generation.Secondly, a multi-path data distribution strategy is proposed. Due to the nodes in the optimal path usually need forward numerous data, especially the direct neighbor nodes of the Sink node, they often dead early from the energy depletion. So, a multi-path data distribution strategy(MDDS) is designed. The forwarding data traffic of the nodes in the optimal path can be transferred to the nodes the sub-optimal path through this strategy, reducing the optimal path node energy consumption rate, so improve the load balance of the whole network.In addition, a regional co-evolution multi-path routing protocol(MRPTSRC) is proposed to solve the problems of the consumption imbalance in three-dimensional space. The protocol designs the zoning model to dividing neighboring space of the node into three subspaces. The Regional Co-evolutionary Algorithm(RCA) is designed to select locally optimal nodes of each subspace and determine the best next hop. The former region weighted strategies is utilized to escape from local optima and to accelerate the convergence rate toward to the Sink node. So a routing path is built by RCA.