Research On Clustering Routing Algorithm In Wireless Sensor Networks

In most of wireless sensor networks, each node can only communicate each otherthrough the local network topology information. The reason is that the battery energy ofsensor nodes is limited, and its computation ability, communication ability and memoryability are too weak. So the WSN needs a more simpler and feasible network routingalgorithm. Through sensor network topology control, we can guarantee that the networkconnectivity, reduce the interference between sensor nodes, and improve the efficiency ofnetwork communication. Because of efficient and reasonable utilization of energy andprolong the network life cycle, it puts forward higher requirements. This paper is not justfocus on saving energy of a single node, but also focus on the whole network of energy. Theclustering algorithm is a kind of routing protocol which can effectively control the networktopological structure. According to the isolated cluster head nodes problem in HEEDalgorithm, this paper proposes a distributed algorithm HEED-NCN. And according to EEUCalgorithm, this paper presents an improved uneven clustering algorithm EEUCES.Firstly, this paper declares LEACH algorithm which is a classic clustering algorithm inwireless sensor and its improved algorithm LEACH–DCHS. In the LEACH algorithm,because the random selection of cluster head, the cluster head nodes have an unevendistribution, leading to the node energy consumption is too large and affect the survival period.HEED algorithm is improved with the residual energy as the main reference into account. Wewill have higher residual energy node chosen for candidate cluster head. The nodes coveredby a multiple clusters choose one cluster to join by calculating the minimum communicationcost choice into clusters. The algorithm has a high iteration speed, clustering uniformcharacteristics, and can prolong the network life cycle. But HEED algorithm’s weakness isthat after the end of iterative the isolated node becomes into cluster head. HEED-NCNalgorithm makes an improvement aimed at these final isolated node’s processing ways. If theisolated node has neighbors, choose the largest residual energy of them to join the cluster. Ifthere is no neighbor, search for the optimal cluster head node by adjusting the way ofcommunication power, and join it. This algorithm can obviously reduce the number ofisolated nodes in the HEED algorithm. So they need not to participate into routing process between clusters. Then it can save the network node’s energy, so as to effectively improve theperformance of the whole network.In the NS2simulation environment, HEED-NCN algorithm has a better performance atthe number of cluster heads, energy consumption, networks survival period compared withHEED. From the experiment，the process of isolated cluster nodes optimize the distribution ofthe clusters in the network, balance the energy consumption of the nodes and improve theeffectiveness of the use of energy, prolong the network life cycle.The improved algorithm EEUCES give up the classic uneven clustering algorithm EEUCwhich uses random generation candidate cluster head way, add the residual energy as animportant reference factors, combined with the fact that gathering node distance, optimizationof the candidate cluster head. EEUCES algorithm makes nodes have smaller cluster radiuswhich near the sink node and away from gathering node of the cluster head have relativelylarge cluster radius. The nodes covered by numbers of clusters select cluster which is far fromthe sink to join. In addition, it solves effectively the isolated nodes problem in EEUCalgorithm. Under the inter-cluster communication, node communicates directly with sinknode when its distance is less than the initial communication threshold. The rest of the clusterheads look for neighbor cluster head to communicate which is near the sink and has a largerresidual energy. The algorithm as an uneven distributed clustering algorithm, with a wholetrain of thought, effectively balances the whole network node energy consumption.Simulations show that the number of clusters in the network is relevant to the radius ofcompetition. The greater the radius of competition of clusters in the network，the number ofthe cluster is less, the density is smaller. Compared with the EEUC algorithm, it is concludedthat the algorithm has a relatively good performance at life cycle, the cluster head distribution,energy consumption of each round. It balance network node energy load and improve energyefficiency purpose. EEUCES has a relatively stable cluster head topological structure, whichcan guarantee the network connectivity and usability.