Please use this identifier to cite or link to this item:
|Title:||Optimal data aggregation tree in wireless sensor networks based on intelligent water drops algorithm|
|Citation:||Hoang, D.C., Kumar, R., Panda, S.K. (2012-09). Optimal data aggregation tree in wireless sensor networks based on intelligent water drops algorithm. IET Wireless Sensor Systems 2 (3) : 282-292. ScholarBank@NUS Repository. https://doi.org/10.1049/iet-wss.2011.0146|
|Abstract:||Energy conservation is an important aspect in wireless sensor networks (WSNs) to extend the network lifetime. In order to obtain energy-efficient data transmission within the network, sensor nodes can be organised into an optimal data aggregation tree with optimally selected aggregation nodes to transfer data. Various nature-inspired optimisation methods have been shown to outperform conventional methods when solving this problem in a distributed manner, that is, each sensor node makes its own decision on routing the data. In this study, a novel optimisation algorithm called intelligent water drops (IWDs) is adopted to construct the optimal data aggregation trees for the WSNs. Further enhancement of the basic IWD algorithm is proposed to improve the construction of the tree by attempting to increase the probability of selecting optimum aggregation nodes. The computational experiment results show that the IWD algorithm is able to obtain a better data aggregation tree with a smaller number of edges representing direct communication between two nodes when compared with the well-known optimisation method such as ant colony optimisation. In addition, the proposed improved version of the IWD algorithm provides better performance in comparison with the basic IWD algorithm for saving the energy of WSNs. © 2012 The Institution of Engineering and Technology.|
|Source Title:||IET Wireless Sensor Systems|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jan 21, 2019
WEB OF SCIENCETM
checked on Jan 14, 2019
checked on Nov 17, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.