Research On Periodic Data Gathering Algorithms In Wireless Sensor Networks

A wireless sensor network is a modern information system which is composed ofmany sensor nodes by the manner of self-organization, it is able to sense and surveyentironment information or targets, and send the obtained information to users fordecision support. Data gathering is one of the basic jobs of wireless sensor networks,and periodic data gathering is the most common fashion of data gathering for wirelesssensor networks. Because wireless sensor networks are closely related to applications,the research on periodic data gathering has to design appropriate periodic data gatheringalgorithms according to specific application situation to accomplish the task of datagathering and satisfy the capability requirements of application simultaneously.Clustering data gathering algorithm is a kind of periodic data gathering algorithmwhich is researched and applied most widely. Since the intrinsic characteristic ofclustered structure, the hot spots problem could easily come up in clustering datagathering algorithm because of the unbalanced energy dissipation between cluster headsand cluster members or between different cluster heads. In energy restricted applications,this problem will shorten network lifetime. Because the energy dissipationcharacteristics of cluster heads in different kinds of clustering data gathering algorithmsare different, the hot spots problem has to be resolved by proper solutions respectively.Equal clustering data gathering algorithm is the perfect solution to resolve the hot spotsproblem in the clustering data gathering algorithms in which cluster heads transmit datato the base station by multi-hop and the middle cluster heads aggregate the data fromdifferent clusters, while unequal clustering data gathering algorithm is the perfectsolution to resolve the hot spots problem in the clustering data gathering algorithms inwhich cluster heads transmit data to the base station by one-hop and the clustering datagathering algorithms in which cluster heads transmit data to the base station bymulti-hop and the middle cluster heads forward the data of other clusters. However, theexisting equal clustering data gathering algorithms and unequal clustering datagathering algorithms have the defect of unsatisfactory effect in equal clustering andunequal clustering respectively, and both have the defect of low energy efficiency.In addition, the data gathering is mainly accomplished depending on cluster headsin clustering data gathering algorithm, if a cluster head fail, the data gathering of relatednodes will be affected, and the data gathering reliability will decline, this problem iscalled cluster head failure problem in this paper. In energy restricted applications inwhich nodes may fail, the clustering data gathering algorithm will be confronted withhot spots problem and cluster head failure problem. The existing clustering datagathering algorithms have not explicitly resolved the two problems simultaneously,although the two problems can be resolved at the same time by combining some algorithms, this method has the defect of low energy efficiency.Moreover, the existing periodic data gathering algorithms have to build thetransmission structure from each node to the base sation in advance, then make nodestransmit data to the base station along the transmission structure, and basically adopt“one-to-one” data transmission fashion, nodes have to depend on the transmissionstructure to accomplish data gathering, and nodes have high degree of dependence onother nodes. In applications in which nodes may fail, the existing periodic datagathering algorithms are not able to adapt to the state change of nodes, which will resultin fall of data gathering reliability.Aiming at above-mentioned problems, this paper researchs on periodic datagathering algorithms in wireless sensor networks from the following aspects:First of all, in order to energy efficiently resolve the hot spots problem in theclustering data gathering algorithms in which cluster heads transmit data to the basestation by multi-hop and the middle cluster heads aggregate the data from differentclusters, and achieve the goal of prolonging network lifetime, proposes the energyefficient and balanced energy dissipation equal clustering data gathering algorithm. Thealgorithm divides the network into equal grids, and implements cluster head rotation ineach grid respectively, so that it can make the cluster heads uniformly distribute innetwork and achieve better effect in equal clustering, by this way, it is able to balanceenergy dissipation. Moreover, the algorithm adopts some energy saving measures toenhance energy efficiency.Secondly, in order to energy efficiently resolve the hot spots problem in theclustering data gathering algorithms in which cluster heads transmit data to the basestation by one-hop and the clustering data gathering algorithms in which cluster headstransmit data to the base station by multi-hop and the middle cluster heads forward thedata of other clusters, and achieve the goal of prolonging network lifetime, proposes theenergy efficient and balanced energy dissipation unequal clustering data gatheringalgorithm. The algorithm divides the network into several grids, implements clusterhead rotation in each grid respectively, and sets the size of a grid according to theenergy dissipation characteristic of cluster head in the grid to adjust the number ofnodes that participate in cluster head rotation and share the energy dissipation load ofcluster head in the grid, by this way, it is able to balance energy dissipation. Similarly,the algorithm adopts some measures to enhance energy efficiency during clustering anddata gathering.Thirdly, in order to energy efficiently resolve the hot spots problem and clusterhead failure problem in all kinds of clustering data gathering algorithms simultaneously,and achieve the goal of prolonging network lifetime and enhancing data gatheringreliability, proposes the balanced energy dissipation and high reliability clustering datagathering algorithm. The algorithm divides the network into several grids, determines the mumber of cluster heads in a grid based on the failure probability of nodes, makesthe nodes in a grid form a fixed cluster, and chooses multiple cluster heads from a grid.The algorithm also sets the size of grid to adjust the number of nodes that participate incluster head rotation and share the energy dissipation load of cluster head in the grid, bythis way, it is able to balance energy dissipation. In addition, the algorithm makes themultiple cluster heads in a grid cooperate with each other to accomplish the task ofcluster head, so that it is able to enhance data gathering reliability. Furthermore, themeasures adopted by the algorithm such as fixed clustering, multiple cluster headsreceiving and single cluster head sending, are able to enhance energy efficiency.Finally, in order to resolve the problem that the existing periodic data gatheringalgorithms are not able to adapt to the state change of nodes, and achieve the goal ofenhancing data gathering reliability, proposes the structure free and dynamic adaptivedata gathering algorithm. The algorithm adopt the methods of structure free and“many-to-many” data transmission, and is able to adapt to the state change of nodes bydividing the network into equal grid and making the nodes transmit data by grids duringdata gathering, so that it can enhance data gathering reliability remarkably.