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

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.

[1]  Shervin Erfani,et al.  Survey of multipath routing protocols for mobile ad hoc networks , 2009, J. Netw. Comput. Appl..

[2]  Feng Zhang,et al.  Novel Data Fusion Algorithm Based on Event-Driven and Dempster–Shafer Evidence Theory , 2018, Wireless Personal Communications.

[3]  Xuesong Qiu,et al.  A service recovery method based on trust evaluation in mobile social network , 2016, Multimedia Tools and Applications.

[4]  Ren-Hung Hwang,et al.  p-MANET: Efficient Power Saving Protocol for Multi-Hop Mobile Ad Hoc Networks , 2005, Third International Conference on Information Technology and Applications (ICITA'05).

[5]  Alex Alvarado.  Information rates and post-FEC BER prediction in optical fiber communications , 2017, 2017 Optical Fiber Communications Conference and Exhibition (OFC).

[6]  M. Rajaram,et al.  Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks , 2015, TheScientificWorldJournal.

[7]  Kandaraj Piamrat,et al.  A Realistic Multipath Routing for Ad Hoc Networks , 2014, GLOBECOM 2014.

[8]  Torsten Braun,et al.  Energy-Efficient Multi-path Routing in Wireless Sensor Networks , 2008, ADHOC-NOW.

[9]  Kewei Sha,et al.  Noname Manuscript No. (will Be Inserted by the Editor) Multipath Routing Techniques in Wireless Sensor Networks: a Survey , 2022 .

[10]  Lin Li,et al.  An energy-aware probability routing in MANETs , 2004, 2004 IEEE International Workshop on IP Operations and Management.

[11]  Charu Gandhi,et al.  Node Disjoint Multipath Routing Considering Link and Node Stability protocol: A characteristic Evaluation , 2010, ArXiv.

[12]  Driss Aboutajdine,et al.  Carrier sense aware multipath geographic routing protocol , 2016, Wirel. Commun. Mob. Comput..

[13]  Jie Jia,et al.  A genetic approach on cross-layer optimization for cognitive radio wireless mesh network under SINR model , 2015, Ad Hoc Networks.

[14]  Chris GauthierDickey,et al.  Result verification and trust-based scheduling in peer-to-peer grids , 2005, Fifth IEEE International Conference on Peer-to-Peer Computing (P2P'05).

[15]  Sung-Ju Lee,et al.  Split multipath routing with maximally disjoint paths in ad hoc networks , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[16]  Katia Obraczka,et al.  Combining on-demand and opportunistic routing for intermittently connected networks , 2009, Ad Hoc Networks.

[17]  Mohammad Mehdi Ebadzadeh,et al.  A novel particle swarm optimization algorithm with adaptive inertia weight , 2011, Appl. Soft Comput..

[18]  Hamid R. Rabiee,et al.  An adaptive cross-layer error control protocol for wireless multimedia sensor networks , 2017, Ad Hoc Networks.

[19]  Ganesh U. Mali,et al.  Shortest Path Evaluation in Wireless Network Using Fuzzy Logic , 2018, Wirel. Pers. Commun..

[20]  Mahesh K. Marina,et al.  On-demand multipath distance vector routing in ad hoc networks , 2001, Proceedings Ninth International Conference on Network Protocols. ICNP 2001.

[21]  Xiaohong Jiang,et al.  On the packet delivery delay study for three-dimensional mobile ad hoc networks , 2018, Ad Hoc Networks.

[22]  M. Rajaram,et al.  A Memory Aided Broadcast Mechanism with Fuzzy Classification on a Device-to-Device Mobile Ad Hoc Network , 2016, Wirel. Pers. Commun..

[23]  Sushanta Karmakar,et al.  Fault resilience in sensor networks: Distributed node-disjoint multi-path multi-sink forwarding , 2015, J. Netw. Comput. Appl..

[24]  Teresa H. Y. Meng,et al.  Minimum energy mobile wireless networks , 1999, IEEE J. Sel. Areas Commun..

[25]  Athanasios V. Vasilakos,et al.  Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs , 2011, Math. Comput. Model..

[26]  Yong Wang,et al.  Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet , 2002, ASPLOS X.