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Energy-Efficient Perspicacious Ant Colony Optimization Based Routing Protocol for Mobile Ad-Hoc Network


Affiliations
1 Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
 

Mobile Ad-hoc Networks (MANETs) are a special kind of network that organize by itself, and they provide high-quality service despite the cost of routing. In MANET, there exist no option to reach other hosts in a single-hop where it needs multi-hop. Many intermediary hosts relay packets transmitted by the source host before reaching the destination host in a multi-hop situation. The level of energy at each node plays a significant role in MANET. Routes are frequently broken, and new routes are discovered in MANETs because of node mobility. In this paper, Energy-Efficient Perspicacious Ant Colony Optimization Based Routing Protocol (EEPACORP) is proposed to determine the optimum route to transfer the data to reduce energy spent by each node for data transmission. EEPACORP is based on the ant's inherent disposition to seek for food. EEPACORP is inspired from genetic character of ant towards finding its food. Pheromone concentration are modified in EEPACORP to find the most appropriate route. The performance of EEPACORP is analyzed in NS3 using standard network metrics. EEPACORP's studies demonstrate that it reduces delays and energy consumption better than the present routing methods.

Keywords

Optimization, Routing, ACO, Delay, MANET, Energy.
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  • M. U. Farooq and M. Zeeshan, “Connected Dominating Set Enabled On-Demand Routing (CDS-OR) for Wireless Mesh Networks,” IEEE Wirel. Commun. Lett., vol. 10, no. 11, pp. 2393–2397, 2021, doi: 10.1109/LWC.2021.3101476.

  • A. Medina and S. Bohacek, “Performance modeling of neighbor discovery in proactive routing protocols,” J. Adv. Res., vol. 2, no. 3, pp. 227–239, 2011, doi: https://doi.org/10.1016/j.jare.2011.04.007.

  • D.-G. Zhang et al., “A Multi-Path Routing Protocol Based on Link Lifetime and Energy Consumption Prediction for Mobile Edge Computing,” IEEE Access, vol. 8, pp. 69058–69071, 2020, doi: 10.1109/ACCESS.2020.2986078.

  • J. Ramkumar and R. Vadivel, “Improved frog leap inspired protocol (IFLIP) – for routing in cognitive radio ad hoc networks (CRAHN),” World J. Eng., vol. 15, no. 2, pp. 306–311, 2018, doi: 10.1108/WJE-08-2017-0260.

  • A. S. Arsalaan, H. Nguyen, A. Coyle, and M. Fida, “Quality of information with minimum requirements for emergency communications,” Ad Hoc Networks, vol. 111, p. 102331, 2021, doi: https://doi.org/10.1016/j.adhoc.2020.102331.

  • N. S. Saba Farheen and A. Jain, “Improved routing in MANET with optimized multi path routing fine tuned with hybrid modeling,” J. King Saud Univ. - Comput. Inf. Sci., 2020, doi: https://doi.org/10.1016/j.jksuci.2020.01.001.

  • R. Joseph Manoj, M. D. Anto Praveena, and K. Vijayakumar, “An ACO–ANN based feature selection algorithm for big data,” Cluster Comput., vol. 22, no. 2, pp. 3953–3960, Mar. 2019, doi: 10.1007/s10586-018-2550-z.

  • B. S. P. Mishra, S. Dehuri, and S. B. Cho, “Swarm intelligence in multiple and many objectives optimization: A survey and topical study on EEG signal analysis,” Stud. Comput. Intell., vol. 592, pp. 27–73, 2015, doi: 10.1007/978-3-662-46309-3_2.

  • N. Ramluckun and V. Bassoo, “Energy-efficient chain-cluster based intelligent routing technique for Wireless Sensor Networks,” Appl. Comput. Informatics, 2020, doi: 10.1016/j.aci.2018.02.004.

  • W. Wang, B. Yang, O. Takahashi, X. Jiang, and S. Shen, “On the packet delivery delay study for three-dimensional mobile ad hoc networks,” Ad Hoc Networks, vol. 69, pp. 38–48, Feb. 2018, doi: 10.1016/j.adhoc.2017.10.004.

  • R. Chaudhry and S. Tapaswi, “Optimized power control and efficient energy conservation for topology management of MANET with an adaptive Gabriel graph,” Comput. Electr. Eng., vol. 72, pp. 1021–1036, 2018, doi: https://doi.org/10.1016/j.compeleceng.2018.03.013.

  • N. Schweitzer, A. Stulman, T. Hirst, R. D. Margalit, and A. Shabtai, “Network bottlenecks in OLSR based ad-hoc networks,” Ad Hoc Networks, vol. 88, pp. 36–54, 2019, doi: https://doi.org/10.1016/j.adhoc.2018.12.002.

  • A. Tahir, N. Shah, S. A. Abid, W. Z. Khan, A. K. Bashir, and Y. Bin Zikria, “A three-dimensional clustered peer-to-peer overlay protocol for mobile ad hoc networks,” Comput. Electr. Eng., vol. 94, p. 107364, 2021, doi: https://doi.org/10.1016/j.compeleceng.2021.107364.

  • B. Hammi, S. Zeadally, H. Labiod, R. Khatoun, Y. Begriche, and L. Khoukhi, “A secure multipath reactive protocol for routing in IoT and HANETs,” Ad Hoc Networks, vol. 103, p. 102118, 2020, doi: https://doi.org/10.1016/j.adhoc.2020.102118.

  • J. Arshad, M. A. Azad, K. Salah, R. Iqbal, M. I. Tariq, and T. Umer, “Performance analysis of content discovery for ad-hoc tactile networks,” Futur. Gener. Comput. Syst., vol. 94, pp. 726–739, 2019, doi: https://doi.org/10.1016/j.future.2018.11.037.

  • W. A. Hussein, B. M. Ali, M. F. A. Rasid, and F. Hashim, “Smart geographical routing protocol achieving high QoS and energy efficiency based for wireless multimedia sensor networks,” Egypt. Informatics J., 2022, doi: https://doi.org/10.1016/j.eij.2021.12.005.

  • D. Zhang, Y. Cui, and T. Zhang, “New quantum-genetic based OLSR protocol (QG-OLSR) for Mobile Ad hoc Network,” Appl. Soft Comput., vol. 80, pp. 285–296, 2019, doi: https://doi.org/10.1016/j.asoc.2019.03.053.

  • S. V Simpson and G. Nagarajan, “A fuzzy based Co-Operative Blackmailing Attack detection scheme for Edge Computing nodes in MANET-IOT environment,” Futur. Gener. Comput. Syst., vol. 125, pp. 544–563, 2021, doi: https://doi.org/10.1016/j.future.2021.06.052.

  • L. E. Jim, N. Islam, and M. A. Gregory, “Enhanced MANET security using artificial immune system based danger theory to detect selfish nodes,” Comput. Secur., vol. 113, p. 102538, 2022, doi: https://doi.org/10.1016/j.cose.2021.102538.

  • D. B.D. and F. Al-Turjman, “A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks,” Ad Hoc Networks, vol. 97, p. 102022, 2020, doi: https://doi.org/10.1016/j.adhoc.2019.102022.

  • M. Usman, M. A. Jan, X. He, and P. Nanda, “QASEC: A secured data communication scheme for mobile Ad-hoc networks,” Futur. Gener. Comput. Syst., vol. 109, pp. 604–610, 2020, doi: https://doi.org/10.1016/j.future.2018.05.007.

  • A. E. Hilal and A. B. MacKenzie, “A distributed coalition game model for cooperation in MANETs,” Ad Hoc Networks, vol. 85, pp. 46–59, 2019, doi: https://doi.org/10.1016/j.adhoc.2018.10.019.

  • J. Ramkumar and R. Vadivel, “Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay,” Int. J. Intell. Eng. Syst., vol. 12, no. 1, pp. 221–231, 2019, doi: 10.22266/ijies2019.0228.22.

  • J. Ramkumar and R. Vadivel, “Intelligent Fish Swarm Inspired Protocol (IFSIP) For Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks,” Int. J. Comput. Digit. Syst., vol. 10, no. 1, pp. 1063–1074, 2020, doi: http://dx.doi.org/10.12785/ijcds/100196.

  • J. Ramkumar and R. Vadivel, “Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks,” Wirel. Pers. Commun., pp. 1–23, Apr. 2021, doi: 10.1007/s11277-021-08495-z.

  • J. Ramkumar and R. Vadivel, “Bee inspired secured protocol for routing in cognitive radio ad hoc networks,” INDIAN J. Sci. Technol., vol. 13, no. 30, pp. 3059–3069, 2020, doi: 10.17485/IJST/v13i30.1152. How to cite this article:

  • R. Vadivel and J. Ramkumar, “QoS-Enabled Improved Cuckoo Search-Inspired Protocol (ICSIP) for IoT-Based Healthcare Applications,” pp. 109–121, 2019, doi: 10.4018/978-1-7998-1090-2.ch006.

  • J. Ramkumar and R. Vadivel, “Meticulous elephant herding optimization based protocol for detecting intrusions in cognitive radio ad hoc networks,” Int. J. Emerg. Trends Eng. Res., vol. 8, no. 8, pp. 4549–4554, 2020, doi: 10.30534/ijeter/2020/82882020.

  • J. Ramkumar and R. Vadivel, “CSIP—cuckoo search inspired protocol for routing in cognitive radio ad hoc networks,” in Advances in Intelligent Systems and Computing, 2017, vol. 556, pp. 145–153, doi: 10.1007/978-981-10-3874-7_14.

  • K. Nabar and G. Kadambi, “Affinity Propagation-driven Distributed clustering approach to tackle greedy heuristics in Mobile Ad-hoc Networks,” Comput. Electr. Eng., vol. 71, pp. 988–1011, 2018, doi: https://doi.org/10.1016/j.compeleceng.2017.10.014.


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  • Energy-Efficient Perspicacious Ant Colony Optimization Based Routing Protocol for Mobile Ad-Hoc Network

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Authors

K. Sumathi
Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
D.
Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India

Abstract


Mobile Ad-hoc Networks (MANETs) are a special kind of network that organize by itself, and they provide high-quality service despite the cost of routing. In MANET, there exist no option to reach other hosts in a single-hop where it needs multi-hop. Many intermediary hosts relay packets transmitted by the source host before reaching the destination host in a multi-hop situation. The level of energy at each node plays a significant role in MANET. Routes are frequently broken, and new routes are discovered in MANETs because of node mobility. In this paper, Energy-Efficient Perspicacious Ant Colony Optimization Based Routing Protocol (EEPACORP) is proposed to determine the optimum route to transfer the data to reduce energy spent by each node for data transmission. EEPACORP is based on the ant's inherent disposition to seek for food. EEPACORP is inspired from genetic character of ant towards finding its food. Pheromone concentration are modified in EEPACORP to find the most appropriate route. The performance of EEPACORP is analyzed in NS3 using standard network metrics. EEPACORP's studies demonstrate that it reduces delays and energy consumption better than the present routing methods.

Keywords


Optimization, Routing, ACO, Delay, MANET, Energy.

References





DOI: https://doi.org/10.22247/ijcna%2F2022%2F212339