i-manager Publications

Energy Efficient Clustering with Mobile Data Collectionin Wireless Sensor Networks

Kalaivani S*, C.Gomathi**, N.Santhiyakumari***

* PG Scholar, Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Salem, India.

** Assistant Professor, Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Salem, India

*** Head, Department of Electronics and Communication Engineering, Knowledge Institute of Technology, Salem, India.

Periodicity:February - April'2015
DOI : https://doi.org/10.26634/jmt.2.1.3753

Abstract

The Wireless Sensor Networks consist of static sensors, which can be deployed in a wide environment for monitoring applications. While transmitting the data from source to static sink, the amount of energy consumption of the sensor node is high. This results in improved lifetime of the network. Some of the WSN architectures have been proposed based on mobile elements such as three-layer framework is for mobile data collection, which includes the sensor layer, cluster head layer, and mobile collector layer (called SenCar layer). This framework employs Distributed Load Balanced Clustering and Dual Data Uploading, it is referred to as LBC-DDU. In the sensor layer, a distributed Load Balanced Clustering (LBC) algorithm is used for sensors to self-organize themselves into clusters. The cluster head layer use inter- Cluster transmission range which is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster, cooperate with each other to perform energy-saving in the inter-cluster communications. Through this transmissions, cluster head information is send to the SenCar for its moving trajectory planning. This is done by utilizing Multi-User Multiple-Input and Multiple-Output (MU-MIMO) technique. Then the results show each cluster has at most two cluster heads. LBC-DDU achieves over 50% energy saving per node. The 60% energy saving on cluster heads comparing with data collection through multi-hop relay to the static data sink. The 20% shorter data collection time compared to traditional mobile data gathering.

Keywords

Wireless Sensor Networks (WSN), Load Balanced Clustering, Dual Data Uploading, Multi-User Multiple-Input And Multiple-Output (MU-MIMO), Sencar, Mobility Control, Polling Point.

How to Cite this Article?

Kalaivani, S., Gomathi, C., and Santhiyakumari, N. (2015). Energy Efficient Clustering with Mobile Data Collection in Wireless Sensor Networks. i-manager’s Journal on Mobile Applications and Technologies, 2(1), 24-31. https://doi.org/10.26634/jmt.2.1.3753

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Energy Efficient Clustering with Mobile Data Collectionin Wireless Sensor Networks

Abstract

Keywords

How to Cite this Article?

References

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