Energy efficient differential data aggregation in a dynamic cluster based WSN

TLDR: The objective of this work is to develop an energy efficient data collection environment for a large scale, randomly deployed cluster based wireless sensor networks by using a virtual grid based mechanism to localize the clusters and stabilize the cluster sizes in the network.

Abstract: A key aspect of collaboration systems, and therefore collaboration technologies is the ability to access concerned information in timely manner. The Internet of things (IoT) is being envisioned as the architecture of the future to assist in this regard. It will be created by combining sensing and communicating devices, which will provide data that can be analyzed and used to initiate automated actions. This structure of IoT has now given a new recognition to Wireless Sensor etworks (WS ) such that WS can be identified as the datacollecting component of the IoT. Efficient data collection from a large scale WS , with limited power supply, bandwidth and packet sizes, is a critical issue. One of the methods of data collection in a WS is through forming multiple clusters of the sensor nodes with one cluster head (CH) in each cluster. The objective of this work is to develop an energy efficient data collection environment for a large scale, randomly deployed cluster based wireless sensor networks by using a virtual grid based mechanism to localize the clusters and stabilize the cluster sizes in the network. This has been done as a precondition to implement the proposed differential data aggregation scheme for the spatially correlated data in a cluster.