Double-sinks Energy-hole Avoidance Strategy Based On Unequal Clustering For Wireless Sensor Network

With the unprecedented advancement in techniques such as microElectromechanical,system on a Chip,wireless communications,embedded computing and low-power design,wireless sensor networks(WSNs)has been widely used in military,medical treatment,environ-mental monitoring,smart home,and many other aspects.As a bridge connecting the human life and the physical world,WSNs has become a research hot-spot of both domestic and international scholars.In wireless sensor networks,a large number of sensor nodes are deployed in a specific monitoring area in a randomly deployed manner,sensor nodes is powered by the lithium batteries carried by itself,thus the energy of the nodes is extremely limited.As a result,in order to prolong the network's lifetime,it is critical to utilize the energy of the nodes effectively.Energy-hole problem is the key issue affecting the efficiency of network energy,widely exists in hierarchical wireless sensor network.Energy hole problem refers to that,some nodes in certain areas are overloaded and malfunction prematurely,then the nodes around the malfunctioning node would bear more load,which will accelerate the malfunction and appearance of "hot spots".When death node reaches a certain amount,the data of nodes would not be transferred to data gathering point and the network life time is end.In this paper,based on existing energy hole avoid strategy,the energy hole problem is discussed innovatively in large-scale wireless sensor net-works configured of double sinks,presenting a double–sinks energy hole avoidance strategy(DEAS).The main works of this paper are listed as follows:(1)Optimize the cluster structure and the timing broadcast mechanism,transfer data by using flow-partitioned method,and introduce the concept of flow-partitioned degree.In DEAS,there are double sinks in the network and they are responsible for collecting data.Dual sink network can collect data better and reduce the energy consumption of nodes during data transmission.In the network,sensor nodes are organized by the method of non-uniform clusters,and the election radius of candidates cluster head is optimized according to its density of nodes within the cluster.Candidate cluster head adopts the timing mechanism to become the final cluster heads,and those candidate cluster heads which with lower nodes density and lager residual energy would become final cluster head faster.In the process of data routing,data is divided into multiple parts and sent to different cluster heads in order to achieve load balance.The method of data partition can make more nodes participate in the data transmission,and make the load between nodes more balanced.Finally,DEAS introduces the concept of flow.Partitioned degree in order to determine the amount of data distributed to each relay node.(2)To balance the load between double sink node,this paper puts forward a double sink monitoring area dynamic adjustment strategy.In this paper,sensor nodes are random non-uniform deployed in the network and every node is not assembly position sensing device.There are two sinks in the network,and the load in different monitoring area can not be same.In this paper,the load difference degree is determined to describe the load difference between double sink.The larger of the load difference between the two sink nodes,the greater the load difference value,and the smaller the load difference value.As time goes by,the load difference between double sink will be more lager,those nodes which have heavier load would quickly run out of energy,The network appear energy hole.To make the node load tends to balance,DEAS algorithm with the method of dynamic adjustment of the double sink monitoring area,so as to realize the balance between the double sink node load.(3)To make the adjustment of the double sink monitoring area more efficient,an adjusting threshold training strategy is put forward.In DEAS algorithm,when the load degree between double sink is more than a certain threshold,the monitoring area of double sink would be adjusted,on the otherhand,the monitoring area of double sink would not be changed.If the threshold is set too large,there will be a big load difference between dual sink still the adjustment is over,if the threshold value is set too small,will cause the network has been in a state of adjustment,both of which are not conducive to the network load balancing.We determine the threshold as the area adjustment threshold,the area adjustment threshold is very important to improve the efficiency of double sink monitoring area adjustment strategy,to make the adjustment of the double sink monitoring area more efficient,a kind of area adjustment threshold training mechanism is put forward to obtain a more reasonable adjusting the threshold.(4)Talk about energy-hole problem under the environment with multiple sinks,and the heuristic algorithm is put forward.In larger networks,always deploying multiple sinks to save energy consumption in data transmission process and raise the utilization ratio of the energy of the nodes in the network.In multiple sink networks,how to determine the deployment location of multiple sink nodes is a difficult problem.The network is divided into multiple sub regions,and multiple sinks are deployed at the center of each sub region.In this paper,we divide the energy-hole problem in multiple sinks environment is divided into multiple double sink environment energy-hole problem and put forward a heuristic algorithm.Finally,compared DEAS algorithm with LEACH,EEUC,DEBUC algorithms and proved DEAS algorithm has more excellent performance in network life time and energy utilization than these algorithms.