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Enhancing VANET communication using squid game optimization based energy aware clustering approach

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Abstract

Vehicular Ad-Hoc Networks (VANETs) are studied wireless networks that enable communication among vehicles and roadside infrastructure. The role a vital play in improving on-road safety, efficacy, and convenience by enabling real-time data interchange for controlling traffic, infotainment services, and collision avoidance. Energy efficiency in VANETs is vital because of the restricted power resources of vehicles. Methods like clustering, vehicles are categorized into groups to decrease communication overhead, and meta-heuristic approaches that optimize network performance by intelligent problem-solving approaches are deployed to exploit energy efficiency while preserving network reliability and responsiveness. These methodologies contribute to the effective implementation of VANETs, ensuring sustainable and dependable communication in dynamic vehicular environments. In this study, a new Squid Game Optimization based Energy Aware Clustering Approach (SGO-EACA) technique for VANET is introduced. The goal of the SGO-EACA technique is to optimally choose the cluster heads (CHs) and produce clusters in the VANET in such a way as to realize energy efficiency. In the SGO-EACA technique, the concept of typical Korean sport is used where the attackers try to achieve their goal, but players try to eliminate each other. Moreover, the SGO-EACA approach derives a fitness function (FF) containing multiple metrics such as Residual Energy (RE), Trust Level, Degree Difference, Total Energy consumption, Distance to Base Station (DBS), and Mobility. The simulation values exposed that the SGO-EACA approach surpassed earlier state-of-the-art approaches with respect to various aspects.

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References

  1. Buvanesvari M, Uthayakumar J, Amudhavel J (2017) Fuzzy based clustering to maximize network lifetime in wireless mobile sensor networks. J Adv Res Dyn Control Syst 2156–2167

  2. Bello-Salau H, Aibinu AM, Wang Z, Onumanyi AJ, Onwuka EN, Dukiya JJ (2019) An optimized routing algorithm for vehicle ad-hoc networks. Eng Sci Technol Int J 22(3):754–766

    Google Scholar 

  3. Liu K, Ng JKY, Lee VCS, Son SH, Stojmenovic I (2016) Cooperative data scheduling in hybrid vehicular ad hoc networks: VANET as a software defined network, IEEE/. ACM Trans Netw 24(3):1759–1773

    Article  Google Scholar 

  4. More S, Naik U (2021) Optimal multipath routing for video transmission in VANETs. Wirel Pers Commun 116(1):805–827

    Article  Google Scholar 

  5. Kumar N, Chilamkurti N, Park JH (2013) ALCA: agent learning-based clustering algorithm in vehicular ad hoc networks. Personal Ubiquitous Comput 17(8):1683–1692

    Article  Google Scholar 

  6. Dilliwar V, Sahu M, Rakesh N (2024) Cluster computing-based EEG sub-band signal extraction with channel-wise and time-slice-wise data partitioning technique. Int j inf Tecnol 16:2763–2773. https://doi.org/10.1007/s41870-024-01924-9

    Article  Google Scholar 

  7. Mann SK, Chawla S (2023) A proposed hybrid clustering algorithm using K-means and BIRCH for Cluster based cab recommender system (CBCRS). Int j inf Tecnol 15:219–227. https://doi.org/10.1007/s41870-022-01113-6

    Article  Google Scholar 

  8. Jayabalan D, Elango S (2024) ICE-VDOP: an integrated clustering and ensemble machine learning methods for an enhanced vector-borne disease outbreak prediction using climatic variables. Int j inf Tecnol 16:2077–2088. https://doi.org/10.1007/s41870-024-01757-6

    Article  Google Scholar 

  9. Prasad RK, Chakraborty S, Sarmah R (2023) Impact of distance measures on partition-based clustering method—an empirical investigation. Int j inf Tecnol 15:627–642. https://doi.org/10.1007/s41870-022-01088-4

    Article  Google Scholar 

  10. Devi MD, Saharia N (2024) Identification of domain-specific euphemistic tweets using clustering. Int j inf Tecnol 16:21–31. https://doi.org/10.1007/s41870-023-01595-y

    Article  Google Scholar 

  11. Choksi A, Shah M (2024) Machine learning based centralized dynamic clustering algorithm for energy efficient routing in vehicular ad hoc networks. Trans Emerg Telecommunications Technol 35(1):e4914

    Article  Google Scholar 

  12. Madasamy B, Balasubramaniam P (2022) Enhanced load balanced clustering technique for VANET using location aware genetic algorithm. Promet-Traffic&Transportation 34(1):39–52

    Article  Google Scholar 

  13. Giridhar K, Anbuananth C, Krishnaraj N (2023) Energy efficient clustering with heuristic optimization based Ro/uting protocol for VANETs. Measurement: Sens 27:100745

    Google Scholar 

  14. Gorikapudi S, Kondaveeti HK (2024) Energy aware cluster based Routing Algorithm for Optimal Routing and Fault Tolerance in Wireless Sensor Networks. J Netw Syst Manage 32(2):1–31

    Article  Google Scholar 

  15. Kadam MV, Vaze VM, Todmal SR (2023) Trust aware clustering-based routing for secure and reliable VANET communications. Wireless Pers Commun 132(1):305–328

    Article  Google Scholar 

  16. Habelalmateen MI, Ahmed AJ, Abbas AH, Rashid SA (2022) TACRP: traffic-aware clustering-based Routing Protocol for Vehicular Ad-Hoc Networks. Designs 6(5):89

    Article  Google Scholar 

  17. Meera VK, Balasubramanian C (2024) A hybrid Fennec Fox and Sand Cat optimization Algorithm for Clustering Scheme in VANETs. Sustainable Computing: Inf Syst, p.100983

  18. Alotaibi Y, Rajasekar B, Jayalakshmi R, Rajendran S (2024) Falcon Optimization algorithm-based energy efficient communication protocol for cluster-based vehicular networks. Computers Mater Continua, 78(3)

  19. Salim A, Khedr AM, Alwasel B, Osamy W, Aziz A (2023) Somaca: A new swarm optimization-based and mobility-aware clustering approach for the internet of vehicles. IEEE access

  20. Sharifi Sani M, Iranmanesh S, Salarian H, Tubbal F, Raad R (2024) Optimizing Energy Efficiency in Opportunistic networks: a Heuristic Approach to Adaptive Cluster-based routing protocol. Information 15(5):283

    Article  Google Scholar 

  21. Abdulsattar NF, Mohammed DA, Alkhayyat A, Hamed SZ, Hariz HM, Abosinnee AS, Abbas AH, Hassan MH, Jubair MA, Abbas FH, Algarni AD (2022) Privacy-Preserving Mobility Model and Optimization-Based Advanced Cluster Head Selection (P2O-ACH) for Vehicular Ad Hoc Networks. Electronics, 11(24), p.4163

  22. Ye Y, Daraz A, Basit A, Khan IA, AlQahtani SA (2024) Cascaded Fractional-Order Controller-Based Load Frequency Regulation for Diverse Multigeneration Sources Incorporated with Nuclear Power Plant. International Journal of Energy Research, 2024

  23. Bharany S, Sharma S, Frnda J, Shuaib M, Khalid MI, Hussain S, Iqbal J, Ullah SS (2022) Wildfire monitoring based on energy efficient clustering approach for FANETS. Drones 6(8):193

    Article  Google Scholar 

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Rajakumar, R., Suresh, T. & Sekar, K. Enhancing VANET communication using squid game optimization based energy aware clustering approach. Int. j. inf. tecnol. 16, 5389–5394 (2024). https://doi.org/10.1007/s41870-024-02176-3

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