Addressing Data Aggregation Using Polynomial Regression in WSNs

Title:Addressing Data Aggregation Using Polynomial Regression in WSNs

Volume: 5 Issue: 2

Author(s): Adil Khan, Chandra P. Gupta and Iti Sharma

Affiliation:

Keywords: Data aggregation, Data correlation, Polynomial regression, Security, Wireless sensor networks.

Abstract: One of the scarcest resources in wireless sensor networks (WSNs) is energy. Thus, a major issue of WSN is to prolong the network lifetime. The energy dissipation of sensor nodes should be minimized within the network for prolong network lifetime. For the sake of this, data aggregation emerged as an important field of research in modern era. Intensive research has been carried out for providing novel energy efficient and secure data aggregation techniques. Unlike conventional data aggregation techniques, polynomial regression based data aggregation technique increases the network lifetime by transmitting compressed data packets of constant size. Data compression has been carried out by performing regression function on the sensed data. These techniques provide good approximation of the sensed value and are scalable as the data compression ratio is nearly constant. In this paper, we present a detailed review on different polynomial regression based data aggregation techniques and provide a comparison among them.

Cite this article as:

Khan Adil, Gupta P. Chandra and Sharma Iti, Addressing Data Aggregation Using Polynomial Regression in WSNs, International Journal of Sensors, Wireless Communications and Control 2015; 5 (2) . https://dx.doi.org/10.2174/2210327905666150727221731