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Alternative TitleResearch on Node Deployment Problem in Data Collection Oriented Wireless Sensor Networks
Thesis Advisor于海斌 ; 曾鹏
Keyword无线传感器网络 节点部署 中继节点 簇首节点 网络生命期
Call NumberTP212/L73/2009
Degree Discipline机械电子工程
Degree Name博士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Other AbstractWith the rapid developments in MEMS, wireless communication, automatic control and artificial intelligence, the Wireless Sensor Network (WSN) gains a great deal of academic attention all over the world. The WSN is changing the way people interacting with the physical world. Its application fields have broadened into every sector of our social life. Node deployment is one of the fundamental issues in the research of WSN. In some WSN applications, network nodes are usually deployed manually. To meet the performance requirements such as energy-efficiency, reliability, and real-time, additional nodes are needed. To keep the network cost within a certain limit, these newly added nodes need to be deployed purposefully. Based on this kind of application mentioned above, the research work in this paper is mainly focused on the study of node deployment strategy for data collection oriented WSN. The main contributions of this thesis are as follows: At first, the paper describes the general research efforts nowadays relating to node deployment problem, discusses their classifications, and indicates their evaluation metrics. Related works are surveyed systematically and the deficiencies of current researches are summarized. In the second part, the paper proposes a heuristic relay node deployment strategy to enhance the connectivity and to satisfy the requirement of network lifetime, in which node deployment is divided into two phases. The first phase deployment aims at ensuring connectivity. The second phase deployment combined with a load balance route protocol meets the requirement of network lifetime. The simulation results show that the strategy minimizes the number of relay nodes for a demanded lifetime. A common problem in data collection oriented WSNs is how to decide cluster-heads. Unreasonable selection of cluster-heads will easily cause high cost for data collection. In the third part, the paper proposes a cluster-head selection algorithm, which is based on optimal data collection cost and successfully solved the problem. Given the network topology, cluster-head selection is a combinatorial optimization problem. For a small-scale network, the globally optimal solution can be achieved by using Brute-Force-Method, which has very high time complexity. In contrast, the heuristic, optimized cluster-head selection algorithm introduced in the paper is more applicable to large networks. The algorithm can get a sub-optimal solution in much shorter time in a large-scale WSN. After that, the optimal problem of cluster-head deployment is formulated as an Integer Programming with the condition of restrictions of cluster-head capacity and the maximal cluster radius. This paper proposes two heuristics strategies to optimize the cluster-head deployment. One is based on the algorithm of K-mean, the other is based on the hybrid algorithm of K-mean and simulated annealing. The former is applicable to deploy cluster-heads when the network is running while the latter is suitable before the network operate in practice. The simulation results show that the clustered network meets restrictions mentioned above while the network lifetime requirement is farthest satisfied. All researches mentioned above are based on network health status monitoring. To avoid too much network resources being used for a long time by the monitoring process, this paper finally proposes, an efficient network status monitoring mechanism is discussed in the last part of this paper. All the nodes in WSN are encoded and a logical multi-level cluster is constructed among the nodes. Making use of the similarity of network status data and continuity of node codes in sub-cluster, in-network lossless aggregation can be realized. Without losing details of network status data, this monitoring mechanism reduces communication cost significantly. The research results may serve as guidelines for WSN designers, solution providers, and system integrators of WSN application. But we need to point out that the paper provides only a framework for WSN planning and deploying. A complete planning and deploying system for WSN is still not available yet. A lot of work is to be done in the future.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
刘琳. 面向数据收集的无线传感器网络节点部署问题研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2009.
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