Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/331807
Title: Selfish Nodes Mitigation Mechanism Through Trust Management Framework In Wireless Sensor Network
Researcher: Kanchana Devi, V
Guide(s): Ganesan, R
Keywords: Computer Science
Computer Science Artificial Intelligence
Engineering and Technology
University: VIT University
Completed Date: 2019
Abstract: Wireless Sensor Network (WSN) consists of sensor nodes, which are deployed in newlinean open environment for monitoring physical phenomena and transmit data to the sinknode through multi-hop communication which is vulnerable for inside and outside attackers.The traditional cryptographic security mechanisms can be compromised by newlinethe attacker. Trust Management bridges the gap laid by the traditional security mechanisms.Reputation based trust management is a powerful system which can be deployed for mitigating the inside attacker and improve the trust between the nodes in an open remote unattended environment. Consecutive dropping of the packets and the early detection of the selfish nodes are some of the challenges that demand attention to improve robustness in WSN. The primary objective of this research work is to propose a selfish node mitigation mechanism using trust management, as follows: _ A reputation based framework to identify and isolate the selfish node in WSN._ A novel algorithm for mitigation of selfish nodes by watching the neighbor node and addressing the consecutive drops. Formulation of the trust value of each node through the Beta Probability Distribution Function. Applying the calculated trust in Semi-Markov Process inspired model for statechange and isolating the corresponding selfish node. Simulation experiments were carried out using the Network Simulator (Version 2.35). The performance of the wireless sensor network was analyzed by varying the number of sensor nodes and selfish nodes, considering various network performance metrics like network lifetime, throughput, energy, and packet delivery ratio. Simulation results depicted the proposed framework as highly efficient in detecting and isolating the selfish nodes when compared to various approaches considered for the analysis. newline
Pagination: i-x, 102
URI: http://hdl.handle.net/10603/331807
Appears in Departments:School of Computing Science and Engineering -VIT-Chennai

Files in This Item:
File Description SizeFormat 
01_title page.pdfAttached File165.84 kBAdobe PDFView/Open
02_declartion & certifigate.pdf2.12 MBAdobe PDFView/Open
03_abstract.pdf89.44 kBAdobe PDFView/Open
04_acknowledgement.pdf61.84 kBAdobe PDFView/Open
05_table of contents.pdf210.07 kBAdobe PDFView/Open
06_list of figures.pdf99.14 kBAdobe PDFView/Open
07_list of tables.pdf63.52 kBAdobe PDFView/Open
08_list of terms and abbreviations.pdf108.03 kBAdobe PDFView/Open
09_chapter_01.pdf1.65 MBAdobe PDFView/Open
10_chapter_02.pdf1.77 MBAdobe PDFView/Open
11_chapter_03.pdf327.62 kBAdobe PDFView/Open
12_chapter_04.pdf777.73 kBAdobe PDFView/Open
13_chapter_05.pdf1.22 MBAdobe PDFView/Open
14_chapter_06.pdf952.02 kBAdobe PDFView/Open
15_chapter_07.pdf970.59 kBAdobe PDFView/Open
16_chapter_08.pdf108.76 kBAdobe PDFView/Open
17_bibliography.pdf311.85 kBAdobe PDFView/Open
18_list of publications.pdf94.33 kBAdobe PDFView/Open
80_recommendation.pdf274.99 kBAdobe PDFView/Open
Show full item record


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: