Unequal Distributed Spatial Correlation-based Tree Clustering for Approximate Data Collection
- DOI
- 10.2991/scict-14.2014.22How to use a DOI?
- Keywords
- Spatial-Temporal; Competitive Radius; DSCC; Multi-hop transmission;Similarity
- Abstract
Dividing the networks into several unequal sizes of clusters and the nodes with similar readings and neighboring geographical location are in the same cluster is an effective way to prolong the WSN lifetime. Most applications in WSNs can tolerate certain accuracy loss of the sensor readings and we can exploit the tradeoff between data accuracy and energy consumption. In this paper, we present an improved protocol called UDSCTC (Unequal Distributed Spatial Correlation-based Tree Clustering for Approximate Data Collection). We modify the radius of node competition depending on the distance of the nodes to the sink node to make close to the sink node of the cluster radius decreases, and realize the compromise of energy-consumption between intra and inter clusters. At the same time, we make the clusters’ data forwarded to the sink node by multi-hops like tree architecture in traditional network. The method can enlarge the network area. Simulation result shows that UDSCTC has some improvement in the number of the cluster, the energy consumption, etc.
- Copyright
- © 2014, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Maiying Shen AU - Shuo Chen PY - 2014/05 DA - 2014/05 TI - Unequal Distributed Spatial Correlation-based Tree Clustering for Approximate Data Collection BT - Proceedings of the 2nd International Conference on Soft Computing in Information Communication Technology PB - Atlantis Press SP - 93 EP - 97 SN - 1951-6851 UR - https://doi.org/10.2991/scict-14.2014.22 DO - 10.2991/scict-14.2014.22 ID - Shen2014/05 ER -