| Wireless sensor network is composed of a large number of tiny sensor nodes which can sense and collect environmental information. With the development of digital circuit and radio communication technology, wireless sensor networks have more and more widely application in industry, military, ecological environment monitoring fields. The size of a sensor node is small and usually carries very limited energy, and the nodes are usually deployed in the complex environment, so it is almost impossible to replace the battery or supplement energy. Therefore, the design of high efficiency and energy saving routing protocol is one of the research focuses in wireless sensor networks. From the perspective of energy efficient hierarchical clustering routing algorithm, this paper will endeavor to optimize the network topology, balance energy consumption, reduce the network communication load, save the network energy, alleviate “hot spot” problem, and extend the life circle of network.This paper will discuss the wireless sensor network energy efficient routing algorithm by the three aspects below. At the same time, the improved algorithm will be proposed. By comparing with the methods of predecessors, it will prove that the algorithms in this paper have more advantages.(1) In response to the problem of redundant data in wireless sensor network, an energy efficient clustering data fusion algorithm is proposed. The cluster heads are selected according to the residual energy of nodes, the distances between the nodes and sink, and the number of neighbor nodes. And then, using Simpson integral rule to calculate and forecast data based on the received data. In the full of accuracy and reliability, the proposed algorithm can reduce the redundant data, balance communication load, and minimize energy consumption. The simulation results show that the algorithm can efficiently forecast data to reduce the network traffic and prolong the network lifetime.(2) In order to reduce the energy consumption and prolong the network lifetime of wireless sensor networks, a fuzzy clustering hierarchy arithmetic based on residual energy prediction is proposed. The new algorithm estimates required energy consumption that the candidate nodes forward their data packets to base station according to the distance between nodes and the base station and the number of neighbors, and then obtains the expected residual energy of nodes. Cluster-heads are elected on the basis of the competition radius that can be computed through fuzzy theory based on the consideration of the original energy and the remaining energy of the candidate nodes, to build clusters of uneven size. Simulation experiments show that compared with other routing algorithms, this arithmetic can better optimize the structure of the cluster, balance energy consumption, and prolong the life cycle of the network.(3) In the cluster-based routing algorithm of wireless sensor network, “hot spot” problem is resulted from energy consumption imbalance between sensors. For this problem, a hybrid multi-hop routing algorithm of effective “hot spot” problem avoidance is put forward on the basis of the research of the flat and hierarchical routing protocol. Firstly, the concept of hotspot area is introduced to divide the monitoring area, and then in clustering stage, the amount of data outside the hotspot area is reduced by using uneven clustering algorithm which can integrate data within the clusters. Secondly, energy consumption is cut down in the hotspot area during clustering stage by no clustering. Finally, in inter-cluster communication phase, the particle swarm optimization algorithm is addressed to seek optimal transmission path which can simultaneously meet minimize the maximum next hop distance between two nodes in the routing path and minimize the maximum hop count. Theoretical analysis and experimental results show that, the proposed algorithm shows better performance in energy efficiency and energy consumption uniformity, which can avoid the “hot spot” problem effectively. |
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