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Mobile Networks and Applications

, Volume 24, Issue 2, pp 375–385 | Cite as

Particle Swarm Based Resource Optimized Geographic Routing for Improved Network Lifetime in MANET

  • C. NallusamyEmail author
  • A. Sabari
Article
  • 76 Downloads

Abstract

In a Mobile ad hoc network (MANET), scalability, dynamic topology and high mobility are the most significant challenges to perform the routing with improved network lifetime. According to the geographical location, geographic routing termed as position-based routing performs data transmission between source node and destination node in a MANET. But, geographic routing protocols were not able achieve effective routing with enhanced network lifetime by improving the resource optimization and optimal coverage performance. In order to improve the resource optimization and network lifetime, an efficient Particle Swarm based Resource Optimized Geographic Routing (PS-ROGR) technique is introduced in MANET. Initially, each particle (i.e. mobile node) movement in a network is controlled by its local best known position in the search space (i.e. geographic location). The PSO permits all the particles in the network to communicate with the other particles with minimum energy. The particle which has the better global best function is selected for energy efficient routing based on the fitness value. Therefore the entire particles share the similar best position to optimize the network resources. Thereby, the PS-ROGR technique prolong the lifetime of the network with minimum energy utilization. Simulation is carried out on the factors such as packet delivery ratio, average end to end delay, energy consumption and network lifetime. Thus, the proposed PS-ROGR technique improves the network lifetime by 22% and reduces the average end to end delay by 46%. Then, the packet delivery ratio is enhanced up to 11% and energy consumption is minimized to 16% with the help of proposed PS-ROGR technique.

Keywords

MANET Geographic routing Particle swarm optimization Network lifetime Resource optimization 

References

  1. 1.
    Chen Q, Kanhere SS, Hassan M (2013) Adaptive position update for geographic routing in mobile ad hoc networks. IEEE Trans Mob Comput 12(3):489–501CrossRefGoogle Scholar
  2. 2.
    Jin X, Zhang R, Sun J, Zhang Y (2014) TIGHT: a geographic routing protocol for cognitive radio mobile ad hoc networks. IEEE Trans Wirel Commun 13(8):4670–4681CrossRefGoogle Scholar
  3. 3.
    Dong P, Qian H, Zhou K, Lu W, Lan S (2015) “a maximally radio-disjoint geographic multipath routing protocol for MANET”, annals of telecommunications - annales des telecommunications. Spring 70(5):207–220Google Scholar
  4. 4.
    Mouna Rekik, Nathalie Mitton, and Zied Chtourou, “Geographic GReedy routing with ACO recovery strategy GRACO”, Ad-hoc Mobile, and Wireless Networks, Springer, Volume 9143, 2015, Pages 19–32Google Scholar
  5. 5.
    Devi S, Sarje A (2015) Dir-DREAM: geographical routing protocol for FSO MANET. Advances in Intelligent Systems and Computing, Springer, Volume 321:95–106CrossRefGoogle Scholar
  6. 6.
    Manickavelu D, Vaidyanathan RU (2014) Particle swarm optimization (PSO)-based node and link lifetime prediction algorithm for route recovery in MANET. EURASIP J Wirel Commun Net 2014(107):1–10Google Scholar
  7. 7.
    Zachariah SS, Preetha KG (2013) Shortest Path Geographic Routing for Mobile Ad Hoc Networks. Int J Comput Sci Eng Technol (IJCSET) 4(08):1177–1180Google Scholar
  8. 8.
    Xiang X, Wang X, Zhou Z (2012) Self-adaptive on-demand geographic routing for mobile ad hoc networks. IEEE Trans Mob Comput 11(9):1572–1586CrossRefGoogle Scholar
  9. 9.
    Zongming Feia and Jianjun Yang, Hui Luc, “Improving routing efficiency through intermediate target based geographic routing”, Digital Communications and Networks, Elsevier, Volume 1, 2015, Pages 204–212Google Scholar
  10. 10.
    Ding Y-z, XuYuan M-z (2016) Tian Hui-ying li, Bing-xiang Liu, “a BER and 2-hop routing information-based stable geographical routing protocol in MANETs for multimedia applications”. Wirel Pers Commun 90(1):3–32CrossRefGoogle Scholar
  11. 11.
    De Rango F, Guerriero F, Fazio P (2012) Link-stability and energy aware routing protocol in distributed wireless networks. IEEE Transact Parallel Distrib Syst 23(4):713–726CrossRefGoogle Scholar
  12. 12.
    Omidvar A, Mohammadi K (2014) Particle swarm optimization in intelligent routing of delay-tolerant network routing. EURASIP J Wirel Commun Netw 2014(147):1–8Google Scholar
  13. 13.
    Hadi Noureddine, Qiang Ni, Geyong Min, Hamed Al-Raweshidy, “A new link lifetime estimation method for greedy and contention-based routing in mobile ad hoc networks”, Telecommunication Systems, Springer, Volume 55, Issue 3, 2014, Pages 421–433Google Scholar
  14. 14.
    ALaa E. Abdallah, Emad E. Abdallah, Mohammad Bsoul, Ahmed Fawzi Otoom, “Randomized geographic-based routing with nearly guaranteed delivery for 3D ad hoc network”, International Journal of Distributed Sensor Networks, hindawi publishing corporation, Volume 2016, 2016, Pages 1–16Google Scholar
  15. 15.
    Niranjan Kumar Ray and Ashok Kumar Turuk, “A Hybrid Energy Efficient Protocol for Mobile Ad Hoc Networks”, Journal of Computer Networks and Communications, Hindawi Publishing Corporation, Volume 2016, 2016, Pages 1-11Google Scholar
  16. 16.
    Wen-Zao Li, Feng Lin, Ji-Liu Zhou and Yan Wang, “DTN routing with fixed stations based on the geographic grid approach in an urban environment”, Wireless Personal Communications, Springer, Volume 82, Issue 4, 2015, Pages 2033–2049Google Scholar
  17. 17.
    Jamali S, Rezaei L, Gudakahriz SJ (2013) An energy-efficient routing protocol for MANETs: a particle swarm optimization approach. Journal of Applied Research and Technology, Elsevier 11(6):803–812CrossRefGoogle Scholar
  18. 18.
    Mahbubur Rahman, Akhtaruzzaman, “An Efficient Position based Power Aware Routing Algorithm in Mobile Ad-hoc Networks”, Int J Comp Network Inf Secur (IJCNIS), Volume 8, Issue 7, 2016, Pages 43–49,Google Scholar
  19. 19.
    Giagkos A, Wilson MS (2014) “BeeIP – a swarm intelligence based routing for wireless ad hoc networks” information sciences. Elsevier 265:23–35Google Scholar
  20. 20.
    Sheng-Tzong, Cheng Jian-Pan, Li Gwo-Jiun Horng, “An adaptive cluster-based routing mechanism for energy conservation in mobile ad hoc networks”, Wireless Personal Communications, Springer, Volume 70, Issue 2, 2013, Pages 561–579Google Scholar
  21. 21.
    Priyanka Jaiswal and Adwitiya Sinha, “Stable geographic forwarding with link lifetime prediction in mobile adhoc networks for battlefield environment”, Human-centric Computing and Information Sciences, Springer, Issue 1, 2016, Pages 1–18Google Scholar
  22. 22.
    Mishra P, Gandhi C, Singh B (2016) Link quality and energy aware geographical routing in MANETs using fuzzy logics. J Telecommun Inf Technol 6:1–17Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.K S Rangasamy College of TechnologyTiruchengodeIndia

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