Load Balanced Clustering and Data Uploading for Efficient Allocation of Periodic Feedback in Wireless Sensor Networks

Authors(2) :-G. Phani Adi Sai, G. LakshmiKanth

This paper is the primary to advocate a framework for strong allocation of periodic feedback channels to the nodes ofa wi-fi group. Several valuable optimization disorders aredefined and effective algorithms for fixing them are furnished. A scheme for making a choice on when the base station (BS) will have got to invoke each algorithm can be proposed and shown by way of simulations to perform very well. On this paper, a 3-layer framework is proposed for cellular expertise assortment in wireless sensor networks, which involves the sensor layer, cluster head layer, and telephone collector (referred to as SenCar) layer. The framework employs dispensed load balanced clustering and dual know-how importing, which is referred to as LBC-DDU. The goal is to obtain excellent scalability, prolonged community lifetime and low expertise assortment latency. On the sensor layer, a allotted load balanced clustering (LBC) algorithm is proposed for sensors to self-arrange themselves into clusters.

Authors and Affiliations

G. Phani Adi Sai
M. Tech, Department of CSE, Sree Rama Engineering College, Tirupati, India
G. LakshmiKanth
Associate Professor, Head of Department, Department of CSE,,Sree Rama Engineering College, Tirupati, India

Base Station, Cellular Expertise ,Telephone Collector ,3-Layer Framework ,Cluster Head Layer And Sensor Layer

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 213-217
Manuscript Number : CSEIT183166
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

G. Phani Adi Sai, G. LakshmiKanth, "Load Balanced Clustering and Data Uploading for Efficient Allocation of Periodic Feedback in Wireless Sensor Networks", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.213-217, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT183166

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