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Forwarding Zone enabled PSO routing with Network lifetime maximization in MANET

Authors:

Rashmi Chaudhry,

Shashikala Tapaswi,

Neetesh KumarAuthors Info & Claims

Applied Intelligence, Volume 48, Issue 9

Pages 3053 - 3080

https://doi.org/10.1007/s10489-017-1127-5

Published: 01 September 2018 Publication History

Abstract

Network lifetime maximization is one of the most sought after issues in Mobile Adhoc Networks (MANETs). Whereas, due to geographical routing based approaches, the packet transmission becomes more suitable in dynamic environment such as MANETs. Direct heuristics are not suitable in such scenarios to provide desired solution as the problem becomes NP-hard in dense networks, thus researchers focused to utilize meta-heuristic techniques. Particle Swarm Optimization (PSO) is one of the most effective meta-heuristic techniques to solve such problems with near optimal solution. However, meta-heuristic techniques (PSO) become slow in convergence and require more computational time when network size increases. Therefore, in this work, PSO is adaptively modified (APSO) to best fit in our scenario, and re-enforced using Forwarding Search Space (FSS) heuristic technique to overcome the PSO's convergence and computational time related issues, significantly improves the performance of PSO. In FSS, a Forwarding Zone (FZ) is selected between source and destination such that the optimal solution lies in that area and APSO is applied for an effective routing in FZ area instead of complete network. To utilize the complementary characteristics of both (APSO and FSS), a hybrid FZ-APSO is proposed for routing in dense network with minimum delay and energy consumption in order to increase the lifetime of the network. Comparative simulation results evidenced that the proposed FZ-APSO routing algorithm significantly improved the performance of the routing in terms of energy consumption, end to end delay, computational time and network lifetime.

References

[1]

Jabbar WA, Ismail M, Nordin R, Arif S (2016) Power-efficient routing schemes for MANETs: a survey and open issues. Wireless Networks 23(6):1---36

Digital Library

[2]

Bratton D, Kennedy J (2007) Defining a standard for particle swarm optimization. In: Swarm Intelligence Symposium, 2007. SIS 2007. IEEE. IEEE, pp 120---127

Digital Library

[3]

Priyadharshini C, Selvan D (2016) PSO based dynamic route recovery protocol for predicting route lifetime and maximizing network lifetime in MANET. In: Technological Innovations in ICT for Agriculture and Rural Development (TIAR), 2016 IEEE. IEEE, pp 97---104

[4]

Basurra SS, De Vos M, Padget J, Ji Y, Lewis T, Armour S (2015) Energy efficient zone based routing protocol for MANETs. Ad Hoc Netw 25:16---37

Digital Library

[5]

Chang CT, Chang CY, Kuo CH, Hsiao CY (2016) A location-aware power saving mechanism based on quorum systems for multi-hop mobile ad hoc networks. Ad Hoc Netw 53:94---109

[6]

Finn GG (1987) Routing and Addressing Problems in Large Metropolitan-Scale Internetworks. ISI Research Report

[7]

Li J, Jannotti J, De Couto DS, Karger DR, Morris R (2000) A scalable location service for geographic ad hoc routing. In: Proceedings of the 6th annual international conference on Mobile computing and networking. ACM, pp 120---130

Digital Library

[8]

Grossglauser M, Vetterli M (2002) Locating nodes with EASE: Mobility diffusion of last encounters in ad hoc networks (No. LCAV-REPORT-2002-004)

[9]

Flury R, Wattenhofer R (2006) MLS: an efficient location service for mobile ad hoc networks. In: Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing. ACM, pp 226---237

Digital Library

[10]

Kumar V, Kumar S (2016) Energy balanced position-based routing for lifetime maximization of wireless sensor networks. Ad Hoc Netw 52:117---129

Digital Library

[11]

Kennedy J (2011) Particle swarm optimization. In: Encyclopedia of machine learning. Springer, US, pp 760---766

[12]

Selvi PFA, Manikandan MSK (2017) Ant based multipath backbone routing for load balancing in MANET. IET Commun 11(1):136---141

[13]

Vallikannu R, George A, Srivatsa SK (2015) Autonomous localization based energy saving mechanism in indoor MANETs using ACO. J Discret Algorithm 33:19---30

Digital Library

[14]

Cadger F, Curran K, Santos J, Moffett S (2013) A survey of geographical routing in wireless ad-hoc networks. IEEE Commun Surv Tutorials 15(2):621---653

[15]

Singh H (1999) Compass routing on geometric graphs. University of Ottawa, Canada

[16]

Na J, Kim CK (2006) GLR: A novel geographic routing scheme for large wireless ad hoc networks. Comput Netw 50(17):3434---3448

Digital Library

[17]

Na J, Soroker D, Kim CK (2007) Greedy geographic routing using dynamic potential field for wireless ad hoc networks. IEEE Commun Lett 11(3).

[18]

Leong B, Liskov B, Morris R (2006, May) Geographic routing without planarization. In: NSDI, vol 6, p 25

Digital Library

[19]

Ruehrup S, Stojmenović I (2010) Contention-based georouting with guaranteed delivery, minimal communication overhead, and shorter paths in wireless sensor networks. In: 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS). IEEE, pp 1---9

[20]

Arad N, Shavitt Y (2009) Minimizing recovery state in geographic ad hoc routing. IEEE Trans Mob Comput 8(2):203---217

Digital Library

[21]

Kuhn F, Wattenhofer R, Zollinger A (2008) An algorithmic approach to geographic routing in ad hoc and sensor networks. IEEE/ACM Trans Netw (TON) 16(1):51---62

Digital Library

[22]

Barriere L, Fraigniaud P, Narayanan L, Opatrny J (2003) Robust position-based routing in wireless ad hoc networks with irregular transmission ranges. Wirel Commun Mob Comput 3(2):141---153

[23]

Lebhar E, Lotker Z (2009) Unit disk graph and physical interference model: Putting pieces together. In: IEEE International Symposium on Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE, pp 1---8

Digital Library

[24]

Kuhn F, Wattenhofer R, Zollinger A (2003) Worst-case optimal and average-case efficient geometric ad-hoc routing. In: Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing. ACM, pp 267---278

Digital Library

[25]

Shah SH, Nahrstedt K (2002) Predictive location-based QoS routing in mobile ad hoc networks. In: IEEE International Conference on Communications, 2002. ICC 2002, vol 2. IEEE, pp 1022---1027

[26]

Watanabe M, Higaki H (2007) No-beacon GEDIR: location-based ad-hoc routing with less communication overhead. In: Fourth International Conference on Information Technology, 2007. ITNG'07. IEEE, pp 48---55

Digital Library

[27]

Cadger F, Curran K, Santos J, Moffett S (2013) A survey of geographical routing in wireless ad-hoc networks. IEEE Commun Surv Tutorials 15(2):621---653

[28]

Shen H, Zhao L (2013) ALERT: an anonymous location-based efficient routing protocol in MANETs. IEEE Trans Mob Comput 12(6):1079---1093

Digital Library

[29]

Ilkhechi AR, Korpeoglu I, Güdükbay U, Ulusoy Ö (2017) PETAL: A fully distributed location service for wireless ad hoc networks. J Netw Comput Appl 83:1---11

Digital Library

[30]

Patel MK, Kabat MR, Tripathy CR (2014) A hybrid ACO/PSO based algorithm for QoS multicast routing problem. Ain Shams Eng J 5(1):113---120

[31]

Kumar S, Mehfuz S (2016) Intelligent probabilistic broadcasting in mobile ad hoc network: a PSO approach. J Reliab Intell Environ 2(2):107---115

[32]

Lu T, Zhu J, Chang S, Zhu L (2010) Maximizing multicast lifetime in unreliable wireless ad hoc network. Wireless Networks:1---11.

Digital Library

[33]

Correia F, Vazão T (2010) Simple ant routing algorithm strategies for a (Multipurpose) MANET model. Ad Hoc Netw 8(8):810--- 823

Digital Library

[34]

Zhang X, Zhang X, Gu C (2017) A micro-artificial bee colony based multicast routing in vehicular ad hoc networks. Ad Hoc Netw 58:213---221

Digital Library

[35]

Suraj R, Tapaswi S, Yousef S, Pattanaik KK, Cole M (2016) Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm. Wirel Netw 22(6):1797---1806

Digital Library

[36]

Kumar N, Vidyarthi DP (2016) A model for resource-constrained project scheduling using adaptive PSO. Soft Comput 20(4):1565---1580

Digital Library

[37]

Pedersen MEH, Chipperfield AJ (2010) Simplifying particle swarm optimization. Appl Soft Comput 10 (2):618---628

Digital Library

[38]

Tasgetiren MF, Sevkli M, Liang YC, Gencyilmaz G (2004) Particle swarm optimization algorithm for single machine total weighted tardiness problem. In: Congress on Evolutionary Computation, 2004. CEC2004, vol 2. IEEE, pp 1412---1419

[39]

Hong X, Gerla M, Pei G, Chiang CC (1999) A group mobility model for ad hoc wireless networks. In: Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems. ACM, pp 53---60

Digital Library

[40]

Jianya YYG (1999) An Efficient Implementation of Shortest Path Algorithm Based on Dijkstra Algorithm {J}. Journal of Wuhan Technical University of Surveying and Mapping (Wtusm), 3 (004)

[41]

Wang D, Tan D, Liu L (2017) Particle swarm optimization algorithm: an overview. Soft Computing:1---22.

Digital Library

[42]

Mandhare VV, Thool VR, Manthalkar RR (2016) QoS Routing enhancement using metaheuristic approach in mobile ad-hoc network. Comput Netw 110:180---191

Digital Library

[43]

Kout A, Labed S, Chikhi S (2017) AODVCS, a new bio-inspired routing protocol based on cuckoo search algorithm for mobile ad hoc networks. Wireless Networks:1---11.

[44]

Xiang W, Wang N, Zhou Y (2016) An Energy-Efficient Routing Algorithm for Software-Defined Wireless Sensor Networks. IEEE Sensors J 16(20):7393---7400

[45]

Hazra J, Sinha AK (2007) Congestion management using multiobjective particle swarm optimization. IEEE Trans Power Syst 22(4):1726---1734

[46]

Yin PY, Chang RI, Chao CC, Chu YT (2014) Niched ant colony optimization with colony guides for QoS multicast routing. J Netw Comput Appl 40:61---72

Digital Library

[47]

Vijayalakshmi P, Francis SAJ, Dinakaran JA (2016) A robust energy efficient ant colony optimization routing algorithm for multi-hop ad hoc networks in MANETs. Wirel Netw 22(6):2081---2100

Digital Library

[48]

Dongyao J, Shengxiong Z, Meng L, Huaihua Z (2016) Adaptive multi-path routing based on an improved leapfrog algorithm. Inf Sci 367:615---629

Digital Library

[49]

Seetaram J, Kumar PS (2016) An energy aware Genetic Algorithm Multipath Distance Vector Protocol for efficient routing. In: International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, pp 1975---1980

[50]

Bhatt M, Sharma S, Luhach AK, Prakash A (2016) Nature inspired route optimization in vehicular adhoc network. In: 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO). IEEE, pp 447---451

[51]

Choudhary A, Tuithung T, Roy OP, Maharaj D (2015) Performance evaluation of improved reliable DSR protocol in case of node failure. In: Internet Technologies and Applications (ITA), 2015. IEEE, pp 329---334

[52]

Perera C, Zaslavsky A, Liu CH, Compton M, Christen P, Georgakopoulos D (2014) Sensor search techniques for sensing as a service architecture for the internet of things. IEEE Sensors J 14(2):406---420

[53]

Kumar N, Vidyarthi DP (2016) A novel hybrid PSO---GA meta-heuristic for scheduling of DAG with communication on multiprocessor systems. Eng Comput 32(1):35---47

Digital Library

Cited By

Alotaibi M(2022)Geographic routing in mobile ad hoc networks (MANET) using hybrid optimization model: a multi-objective perspectiveApplied Intelligence10.1007/s10489-022-03885-753:9(11214-11228)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1007/s10489-022-03885-7
Mehto ATapaswi SPattanaik K(2021)Multi-objective particle swarm optimization based rendezvous point selection for the energy and delay efficient networked wireless sensor data acquisitionJournal of Network and Computer Applications10.1016/j.jnca.2021.103234195:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.jnca.2021.103234
Pham QNguyen DMirjalili SHoang DNguyen DPathirana PHwang W(2021)Swarm intelligence for next-generation networksJournal of Network and Computer Applications10.1016/j.jnca.2021.103141191:COnline publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1016/j.jnca.2021.103141
Show More Cited By

Forwarding Zone enabled PSO routing with Network lifetime maximization in MANET

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Published In

cover image Applied Intelligence

Applied Intelligence Volume 48, Issue 9

September 2018

665 pages

ISSN:0924-669X

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

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Kluwer Academic Publishers

United States

Publication History

Published: 01 September 2018

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Cited By

Alotaibi M(2022)Geographic routing in mobile ad hoc networks (MANET) using hybrid optimization model: a multi-objective perspectiveApplied Intelligence10.1007/s10489-022-03885-753:9(11214-11228)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1007/s10489-022-03885-7
Mehto ATapaswi SPattanaik K(2021)Multi-objective particle swarm optimization based rendezvous point selection for the energy and delay efficient networked wireless sensor data acquisitionJournal of Network and Computer Applications10.1016/j.jnca.2021.103234195:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.jnca.2021.103234
Pham QNguyen DMirjalili SHoang DNguyen DPathirana PHwang W(2021)Swarm intelligence for next-generation networksJournal of Network and Computer Applications10.1016/j.jnca.2021.103141191:COnline publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1016/j.jnca.2021.103141
Gopalan S(2021)ZHRP-DCSEI, a Novel Hybrid Routing Protocol for Mobile Ad-hoc Networks to Optimize Energy Using Dynamic Cuckoo Search AlgorithmWireless Personal Communications: An International Journal10.1007/s11277-021-08180-1118:4(3289-3301)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s11277-021-08180-1
Muneeswari BManikandan M(2019)RETRACTED ARTICLE: Defending against false data attacks in 3D grid-based MANET using soft computing approachesSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-03899-323:18(8579-8595)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s00500-019-03899-3

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