Route Optimization by using Multiple Travelling Sales Person Problem in MANETs

Authors(1) :-M V Narayana

Finding the route between two mobile nodes is one of critical task in Mobile Adhoc Networks (MANETs). In this work mainly focusing on route optimization with nearest neighbour for Multiple Travelling Sales Person Problems (MTSP). MANET is a multi-hop wireless network with mobility feature like mobile phones, computers. Each node will be act as router and communicate without server concept. In the Travelling Sales Person Problem (TSP), all the possible number of routes to be found by a salesperson (Mobile Routing Agent) through cover every node and finally come back to starting point along with possible number of shortest paths. Mobile Routing Agent collects the node and its total information in the network like node position, neighbour node data and message agent (salesperson) helps during the data transmission. The main aim of the proposed concept is to obtain the optimum route between source and destination nodes. With MTSP, Provide acceptable solution to overall network congestion in terms of hop count and distance, the constant updates of the hops and choosing the best path over the network.

Authors and Affiliations

M V Narayana
Department of CSE, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Hyderabad, Telangana, India

MANET, TSP, MTSP, Nearest Neighbor Algorithms, Euclidean Distance

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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) : 776-781
Manuscript Number : CSEIT1831194
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

M V Narayana, "Route Optimization by using Multiple Travelling Sales Person Problem in MANETs", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.776-781, January-February-2018.
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