Research On Energy Equilibrium Routing Protocol Design In Wireless Sensor Networks

As the development of wireless communication and low power consumption chips, wireless sensor network(WSN) emerges as the times require. It has brought profound influence to modern technology and changed the interaction way between man and nature, thus it becomes an increasingly hot research field. WSN has wide potential application fields such as military, national defense, environment maintenance, automation, medical treatment, intelligent space and so on.Wireless sensor network is often deployed in some unforgiving places. Once scattered, the energy of sensor node can hardly be recharged, so the choke point in the application of WSN is the limited energy resources. Then how to design a light and highly efficient flat routing protocol to improve the energy utilization rate, prolong the life time and ensure the scalability of WSN is of great importance. The key point of flat routing protocol design is the next-hop strategy. While the gradient based next-hop selecting method and other traditional means care little about the equilibrized energy consumption, so dead nodes often come at the premature stage of network and lifetime of it is often short. Under the sponsor of National Nature Science Foundation of China (No.60132030), Research Found for the Doctoral Program of Higher Education "sensor network research and key issues in the application of water-saving irrigation" (No.20040486049), this paper carried out the following research works:To solve the problem of unbalanced energy consumption caused by lacking of paths variety, GADiD (GA based Dijkstra-Directed Diffusion) routing protocol was proposed. It depends on detecting packet strategy and improved Dijkstra algorithm to generate the initial path collection, which is later optimized by Genetic Algorithm to increase the variety and quality of path collection. The simulation results show that GADiD prolonged the network life to a certain extent, the transmission delay and average energy consumption have also been optimized.In order to fundamentally eliminate the unbalanced energy consumption in the next-hop selection, Fuzzy Gradient based Energy Equilibrium Routing Protocol (FGEE) was designed. In FGEE, fuzzy gradient classification and quality evaluation function based next-hop selecting strategy was devised to balance the energy consumption as a whole. Reject and recommend strategy of low energy node was applied to bypass the load which could balance energy consumption locally. The simulation results show that FGEE utilized the limited resources more thoroughly and rationally, prolonged the network life to a large extent and decreased the average energy consumption.Reactivating strategy for high residual energy node was devised to improve the performance of FGEE and the Residual Energy Scheming based Energy Equilibrium Routing Protocol (RESEE) was proposed. In RESEE, reject and recommend strategy of low residual energy node, and reactivate strategy of high residual energy node were applied together to equilibrize the energy consumption locally. Simulation results show that the performance of lifetime and energy balance in RESEE have a further improvement compared with FGEE. Clustering method has been introduced to design an energy balance strategy which is lighter and more efficient-the coalition and cooperation strategy. The fuzzy gradient strategy is used to select the next-hop node roughly and balance the energy consumption as a whole, then coalition and cooperation strategy is used to achieve precise energy balance locally. The protocol is called Coalition and Cooperation based Energy Balance Routing Protocol (CCEB). The simulation results demonstrate that CCEB utilized the limited energy more thoroughly and rationally, decreased the average energy consumption effectively, prolonged the lifetime of wireless sensor network greatly. And it has been proved that CCEB is extensible. With the increase of coalition scale, the network life and the effect of energy balance are gradually improved, while the complexity of building coalition and cooperating are also on the rise. So taking performance and complexity into account, how to strike the right balance is worth researching into.