Research On Energy-Efficient Data Collection In Wireless Sensor Networks

Wireless sensor network (WSN) is a new hot-spot in current research, and it has broad application foreground. A wireless sensor network consists of a large number of nodes that collaborate together to monitor various phenomenons. WSN.can be used in various fields, such as military, environment, disaster forecast and relief, business, health, etc. The sensor nodes have only limited communication ability, computational ability, storage space, and energy, etc. Moreover, the nodes are difficult to be replaced because they are often deployed in remote or inaccessible environments.Wireless sensor networks are data-oriented and are usually densely deployed in a monitor environment to process a great deal of data. Data collection is one of the most important operations in the network, which means that the data sensed by nodes should be transmitted to the sink for further processing. How to conserve the limited energy of nodes and extend the lifetime of the network is an important issue in data collection. This dissertation focuses on the problem that how to find some ways to effectively decrease energy consumption of the nodes and maximize the network lifetime and improve the scalability of the network. The main contributions of this dissertation are showed as follows.(1) Aiming at the problem of existing clustering protocols usually randomly choose cluster heads or use the node with the highest remaining energy in a cluster as the head, which may lead to unbalanced energy consumption among different nodes and shorten the network lifetime, we propose a distributed energy-balanced dominating set based clustering scheme named EBDSC, which effectively prolongs the network lifetime by balancing energy consumption among nodes. In EBDSC, each node calculates the number of rounds it can afford if it was selected as the cluster head. A node becomes a candidate cluster head if it affords most number of rounds among its neighbors. A candidate cluster head becomes a final cluster head with a probability determined by its uncovered neighbors. The protocol can terminate in O(logn/loge) steps, and its total message complexity is O(nlogn/loge). Simulation results show that EBDSC can balance energy consumption among nodes well. The average energy consumption of EBDSC is reduced in the clustering phase, and the network lifetime is prolonged compared with another clustering algorithm ECDS.(2) Aiming at the problem of exsiting researches construct virtual backbone of network by using minimum connected dominating sets, and each node in the network can transmit its data to the sink by the virtual backbone. But, the minimum connected dominating sets cannot balance the energy consumptions among nodes. Therefore, the network lifetime is hard to be extended. We propose a novel algorithm named DGA-EBCDS to construct an energy-balanced connected dominating set. In DGA-EBCDS, each node in the connected dominating set has high energy and large degree, and these nodes form a virtual backbone in the network. By transmitting data through the backbone with small numbers of sensor nodes, each node can preserve its energy effectively. Moreover, the nodes in the backbone can live longer. Theoretical analyses show that DGA-EBCDS can construct a connected dominating set with O(nlogn) message complexity, and simulations show that the average energy consumption of DGA-EBCDS is reduced, and the network lifetime is prolonged compared with another algorithm mr-CDS.(3) Aiming at the problem of existing data collection protocols mainly assume that every node in the network produces the same amount of data, we propose a novel dominating set based algorithm DSCAU to solve the problem. In DSCAU, when electing the tentative cluster head, each node takes its remainder energy, its traffic load, the number of its neighbors, and the traffic loads of its neighbors into consideration. The tentative cluster head will become final cluster head with a probability inversely proportional to the numbers of other tentative cluster heads that cover its neighbors. Furthermore, the size of clusters is restricted to balance the energy consumption among different cluster heads. Theoretical analyses and simulation results show that DSCAU can effectively prolong the network lifetime in multi-hop WSNs, meanwhile guaranteeing that all the nodes in the network can join a cluster.Moreover, in order to expand the applicability of the algorithm, we futher propose a new algorithm named DSCP to improve DSCAU. In DSCP, a node evaluates the potential lifetime of the network (from its local point of view) assuming that it acts as the cluster head, and claims to be a tentative cluster head if it maximizes the potential lifetime. When evaluating the potential lifetime of the network, a node considers not only its remaining energy, but also other factors including its traffic load, the number of its neighbors, and the traffic loads of its neighbors. The protocol can terminate in O(n/logn) steps, and its total message complexity is O(n2/logn). Simulation results show that DSCP can effectively prolong the lifetime of the network in multi-hop networks with unbalanced traffic load.In a word, the dissertation performs an in-depth study on the data collection of wireless sensor networks. Moreover, several energy-efficient data collection protocols with higher performance are proposed. Therefore, the research of the dissertation has strong theoretical and practical significances.