Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/346306
Title: A new adaptive broadcast scheduling Algorithm in manets using good Neighbor node detection approach
Researcher: Aparna, C
Guide(s): Nelson kennedy babu, C and Venkatesh, C
Keywords: Engineering and Technology
Engineering
Engineering Electrical and Electronic
broadcast
node detection
University: Anna University
Completed Date: 2020
Abstract: MANET nodes are distinguished by their minimum transmission power, dispensation, mobility, and resources of memory. The wireless mobile nodes enter and leave the network dynamically due to the limited range of transmission, the path of minimum hop and minimum normalized residual energy used. Each device in a mobile adhoc network must transmit traffic and heavy traffic creates congestion that can lead to loss of the packet, reducing the energy of network and high overhead. During the packet transfer, the link interruption occurs due to the dynamic topology network, so QoS can be reduced and routing overhead also increased. Therefore, a new adaptive broadcast scheduling algorithm to increase the QoS and detecting good neighbors in a MANET is required. Internal and external attacks called malicious node, happened in the network affects the integrity, confidentiality or using a network resource without its prior permission. There are many malicious node detection methods to identify abnormal activity. The investigation shows a low accuracy of the network, packet loss, and maximum delay time to established networks. On the other hand, the process of node identification and deployment will become expensive both in terms of time and cost. Based on the above issues, the focus will be on a good neighbor node detection approach, since this is a more efficient, lightweight and easily scalable detection method in MANET newline
Pagination: xvii, 125p
URI: http://hdl.handle.net/10603/346306
Appears in Departments:Faculty of Information and Communication Engineering

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03_vivaproceedings.pdf126.22 kBAdobe PDFView/Open
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06_acknowledgements.pdf108.29 kBAdobe PDFView/Open
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08_listoftables.pdf14.88 kBAdobe PDFView/Open
09_listoffigures.pdf8.92 kBAdobe PDFView/Open
10_listofabbreviations.pdf21.08 kBAdobe PDFView/Open
11_chapter1.pdf148.79 kBAdobe PDFView/Open
12_chapter2.pdf180.21 kBAdobe PDFView/Open
13_chapter3.pdf204.19 kBAdobe PDFView/Open
14_chapter4.pdf655.53 kBAdobe PDFView/Open
15_chapter5.pdf837.53 kBAdobe PDFView/Open
16_conclusion.pdf19.61 kBAdobe PDFView/Open
17_references.pdf115.66 kBAdobe PDFView/Open
18_listofpublications.pdf127.66 kBAdobe PDFView/Open
80_recommendation.pdf51.59 kBAdobe PDFView/Open
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