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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Priya, S. B. M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Dept of ECE J.J. College of Engineering & Technology Trichy, India, 620009 (Priya, S. B. M.) |
| Abstract | The performance of the Mobile Ad-Hoc NETwork are influenced by numerous factors which includes topological changes in network, network size variation, mobility of nodes, etc. Since the design of routing protocol is carried out by considering a particular environment, no existing routing protocol performs well for all kind of possible environments and requirements. In this paper we proposes an adaptive protocol selector for MANET which helps in selecting an optimum routing protocol by learning the current network context and user requirement. Regression models of various degrees have been designed for the performance metrics which depicts the functional relationship between the influencing factors and protocol performance. This paper includes the discussion on the design of adaptive protocol selection module, simulated results of Protocol Regression Model (PRM) and the simulated results of adaptive protocol selection. The PRM predicts the routing protocol performance for the current network context and the algorithm which helps in determining the appropriate protocol for a particular environment. Here DSDV, AODV and DSR protocols are chosen for the evaluation process. |
| Starting Page | 509 |
| Ending Page | 514 |
| File Size | 422597 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467351416 |
| e-ISBN | 9781467351447 |
| DOI | 10.1109/INCOSET.2012.6513957 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-12-13 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Multiple Regression DSDV Routing protocol selection DSR Adaptability PRM Ad-Hoc networks AODV |
| Content Type | Text |
| Resource Type | Article |
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