Detecting and Minimizing Node Failure Context in Wireless Sensor Network

Authors(3) :-S. Parthiban, S. Ramkumar, S. Neranjana

Node failure detection in mobile wireless networks is very challenging due to node movements, the network may not be always connected, and the resources are limited. In this project, propose solutions to address the challenge specific to sensor networks, to design a fault tolerant, energy efficient monitoring system in a distributed manner. In proposed concept focus on fully distributed monitoring algorithms, objective to minimize the number of overall pollers while bounding the false alarm rate. To increase the energy efficiency and reduce the monitoring overhead, take the hop-by-hop aggregation opportunities in sensor network. When building the monitoring architecture, focus on the fundamental tradeoff between the number of monitoring nodes (i.e., poller) the false alarm rate. To achieve the optimal aggregation path problem and propose an opportunistic greedy algorithm, which achieves an approximation ratio.

Authors and Affiliations

S. Parthiban
Computer Science and Engineering, Anna University/IFET College of Engineering, Villupuram, Tamil Nadu, India
S. Ramkumar
Computer Science and Engineering, Anna University/IFET College of Engineering, Villupuram, Tamil Nadu, India
S. Neranjana
Computer Science and Engineering, Anna University/IFET College of Engineering, Villupuram, Tamil Nadu, India

Wireless, Sensor Network, ACK, MIS, Poller

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Publication Details

Published in : Volume 2 | Issue 2 | March-April 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 429-433
Manuscript Number : CSEIT1722132
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

S. Parthiban, S. Ramkumar, S. Neranjana, "Detecting and Minimizing Node Failure Context in Wireless Sensor Network ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.429-433, March-April-2017.
Journal URL : http://ijsrcseit.com/CSEIT1722132

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