PSOBLAP: Particle Swarm Optimization-Based Bandwidth and Link Availability Prediction Algorithm for Multipath Routing in Mobile Ad Hoc Networks

  • Y. Harold RobinsonEmail author
  • S. Balaji
  • E. Golden Julie


In mobile ad hoc network (MANET), optimal path identification is the main problem for implementing the Multipath routing technique. MANET desires an efficient algorithm for improving the performance of the network by improving the connectivity of network organization. MANET routing protocol will consider so many parameters like extended power, the superiority of wireless associations, path failures, desertion, obstruction, and topological adjusts are generated for the discovery of optimal path for increasing the original routing algorithms. Further advancement in multipath routing algorithm proposal will be based on local rerouting called particle swarm optimization-based bandwidth and link availability prediction algorithm for multipath routing and to ensure forwarding continuity with compound link failures. In the route discovery phase, each node establishes a link between their neighboring nodes. If there is any route failure resulting in data loss and overhead will occur. Hence routing in MANET is developed by the movement of a node (mobility). In this paper, the particle swarm optimization based on available bandwidth and link quality based on mobility prediction algorithm is used to provide the multipath routing in MANET. In this prediction phase, the available bandwidth, link quality, and mobility parameters are used to select the node based on their fuzzy logic. The selected node will broadcast information among all the nodes and details are verified before transmission. In the case of link failure, the nodes are stored into a blacklisted link. Furthermore, the routes are diverted and backward to find a good link as a forwarder or intermediate node. The proposed scheme is able to attain a significant progress in the packet delivery ratio, path optimality, and end-to-end delay.


MANET PSOBLAP Fuzzy logic Link failure 



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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSCAD College of Engineering and TechnologyTirunelveliIndia
  2. 2.Department of Computer Science and EngineeringFrancis Xavier Engineering CollegeTirunelveliIndia
  3. 3.Department of Computer Science and EngineeringAnna University Regional CampusTirunelveliIndia

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