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Thomas Seidl2009, Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data - SensorKDD '09
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Abstract
Clustering is an established data mining technique for grouping objects based on similarity. For sensor networks one aims at grouping sensor measurements in groups of similar measurements. As sensor networks have limited resources in terms of available memory and energy, a major task sensor clustering is efficient computation on sensor nodes. As a dominating energy consuming task, communication has to be reduced for a better energy efficiency. Considering memory, one has to reduce the amount of stored information on each sensor node.
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A Communication-Efficient Distributed Clustering Algorithm for Sensor Networks
22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008
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Clustering and Energy Efficiency in Wireless Sensor Networks: A Study
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On clustering in sensor networks
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International Journal of Wireless and Mobile Computing, 2006
Since sensor nodes operate on batteries, energy-efficient mechanisms for gathering sensor data are indispensable in prolonging the lifetime of a sensor network as long as possible.
Applying Clustering Strategies to Improve the Efficiency of Network in Wireless Sensor Networks
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Wireless Sensor Networks are comprised of thousands of sensor nodes which are disseminated in a specific region to screen natural conditions like temperature, sound, pressure and so on and agreeably pass their information to the base station. WSN is steadily creating innovation. There are substantial scale applications in WSN like ecological observing, front line mindfulness, temperature detecting and so on in this way, there is need of expanding network lifetime in WSN as changing sensors regularly isn't conceivable for all intents and purposes constantly. In the past methods, the clustering of nodes isn't balanced and this can make the network energy unbalanced. Based on their separation and location, making it basically not quite the same as the Proposed Location Based Clustering Algorithm (LBC) can perform superior to anything leaving LEACH and Rescue Phase to shape a cluster. In LBC algorithm the location of every single present hub in the network are computed as for X, Y-organizes. This can maintain a strategic distance from arbitrary choice of nodes in clusters. It enhances the adjusting of the network and energy of network can be spared. Proposed Center Point Detection Clustering Algorithm (CPDC) decides the focal point of the cluster and closest hub to that point with high energy chose as Cluster Head (CH).
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Wireless networks data aggregation allows in-network processing, reduces packet transmission and data redundancy, and thus helps extend wireless sensor systems to the full duration of their lives. There have been many ways of dividing the network into clusters, collecting information from nodes and adding it to the base station, to extend wireless sensor network life. Certain cluster algorithms consider the residual energy of the nodes when selecting clusterheads and others regularly rotate the selection head of the cluster. However, we seldom investigate the network density or local distance. In this report we present an energy-efficient clustering algorithm that selects the best cluster heads of the system after dividing the network into clusters. The cluster head selection depends on the distance between the base station nodes and the remaining power of this approach.Each node's residual energy is compared to the node count. Our results show that the solution proposed more ef...
Energy Efficient Clustering Techniques for Wireless Sensor Networks-A Review
International Journal of Scientific Research and Management, 2017
The applications of Wireless Sensor Networks (WSNs) are growing at rapid pace and providing pervasive computing environments. Energy constraints is the most critical issue in sensor applications and that needs be optimized to prolong the life of resource constrained sensor network. Clustering is an efficient technique to group the sensor nodes of entire network into number of clusters to support high scalability and provide better data aggregation by efficient utilization of limited resources of sensor nodes and that prolongs network lifetime. In this paper, some widely explored clustering algorithms in WSNs are discussed on several aspects and characteristics such as clustering timings, clustering attributes, convergence rate etc. The advantages and disadvantages of corresponding clustering algorithms are also explained with suitable examples. The paper finally concludes with discussion on the challenges of clustering in WSNs with mentioning the future research topics.
An unbalanced and distributed clustering algorithm-UBDC (日韓合同ワークショップ 1st Korea-Japan Joint Workshop on Ubiquitous Computing and Networking …
情報処理学会研究報告. UBI,[ユビキタス …, 2005
抄録 Many in-network aggregation and clustering methods have been proposed for reducing energy consumption in sensor networks. In this paper, we propose an unbalanced and distributed clustering algorithm based on in-network aggregation at nodes within clusters. ...
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