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Wireless Sensor Networks Part 7

Tham khảo tài liệu 'wireless sensor networks part 7', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Data Aggregation Tree Construction Algorithms and Challenges 143 2. Aggregation Tree Construction As a result of energy saving of data aggregation different aggregation algorithms have been presented. In this section we review them briefly and compare their efficiency and then we introduce a new algorithm describe it and evaluate its efficiency. Finally we consider a new challenge i.e. tree construction cost. 2.1 Recent Works In Krishnamachari et al 2002 the authors investigate the computational complexity of optimal data aggregation in sensor networks and show that it is generally NP-hard they present some suboptimal data aggregation tree generation heuristics Center at Nearest Source CNS Shortest Paths Tree SPT and Greedy Incremental Tree GIT and show the existence of polynomial special cases. As presented in Zhang Cao 2004 DCTC algorithm dynamically constructs the aggregation tree for mobile target tracking. In the presented algorithm depending on the target location a subset of nodes participates in tree construction. In Upadhyayula et al 2003 the sink saves the entire network state and then by considering link cost in centralized form constructs the tree with minimum cost. In cluster algorithm Younis Fahmy 2004 after partitioning the network into clusters cluster s members construct aggregation tree and transmit data to cluster head. After aggregation cluster heads transmit aggregated data to the sink in one hop or multihop manner Chen et al 2005 . Espan Lee Wong a 2005 is an energy-aware spanning tree algorithm that constructs the aggregation tree to aggregate the data. In Espan the source node which has the highest residual energy is chosen as the root and other nodes choose their corresponding parent node among their neighbors based on distance to the root and residual energy. Each node selects the closest neighbors to root as its parent. If there are multiple neighbors with equal distance the node which has the most remaining energy is selected as parent.