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Minimizing Energy Consumption in Vehicular Sensor Networks Using Relentless Particle Swarm Optimization Routing


Affiliations
1 Department of Computer Science, Skyline University, Nigeria
2 Department of Computer Science, Dr. N.G.P. Arts and Science College, Tamil Nadu, India
3 Department of Computer Science and Applications, Sankara College of Science and Commerce, Tamil Nadu, India
4 Department of Computer Science and Engineering, Annamalai University, Tamil Nadu, India
5 Department of Computer and Information Science, Annamalai University, Tamil Nadu, India
 

Increasing traffic issues, particularly in highly populated nations, have prompted recent interest in Vehicular Sensor Networks (VSNETs) from academics in several fields. Accident rates continue to rise, highlighting the need for a highly functional Smart Transport System (STS). Improvements to the STS should not be spread thin across the board but should concentrate on improving traffic flow, maintaining system reliability, and decreasing vehicle carbon dioxide and methane emissions. Current routing protocols for VSNETs consider various scenarios and approaches to provide safe and effective vehicle-to-infrastructure communication. The reliability of vehicle connections during data transmission has not been well explored. This paper proposes a Relentless Particle Swarm Optimization based Routing Protocol (RPSORP) for VSNET to use vehicle kinematics and mobility to identify vehicle location, send routing information packets to road-side devices, and choose the most reliable path for travel. RPSORP optimizes local and global search to minimize energy consumption in VSNET. The RPSORP is evaluated in the GNS3 simulator using Throughput, Packet Delivery, Delay, and Energy Consumption metrics. RPSORP has superior performance than state-of-the-art routing protocols.

Keywords

VSNET, Routing, Swarming, PSO, Local-Search, Global-Search.
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  • H. Khelifi, S. Luo, B. Nour, H. Moungla, S. H. Ahmed, and M. Guizani, “A blockchain-based architecture for secure vehicular Named Data Networks,” Comput. Electr. Eng., vol. 86, p. 106715, 2020, doi: 10.1016/j.compeleceng.2020.106715.
  • O. S. Al-Heety, Z. Zakaria, M. Ismail, M. M. Shakir, S. Alani, and H. Alsariera, “A Comprehensive Survey: Benefits, Services, Recent Works, Challenges, Security, and Use Cases for SDN-VANET,” IEEE Access, vol. 8, pp. 91028–91047, 2020, doi: 10.1109/ACCESS.2020.2992580.
  • M. A. Hossain et al., “Multi-Objective Harris Hawks Optimization Algorithm Based 2-Hop Routing Algorithm for CR-VANET,” IEEE Access, vol. 9, pp. 58230–58242, 2021, doi: 10.1109/ACCESS.2021.3072922.
  • M. Naderi, F. Zargari, and M. Ghanbari, “Adaptive beacon broadcast in opportunistic routing for VANETs,” Ad Hoc Networks, vol. 86, pp. 119–130, 2019, doi: 10.1016/j.adhoc.2018.11.011.
  • M. Lingaraj and A. Prakash, “Power aware routing protocol (PARP) to reduce energy consumption in wireless sensor networks,” Int. J. Recent Technol. Eng., vol. 7, no. 5, pp. 380–385, Jan. 2019, Accessed: Apr. 07, 2021. [Online]. Available: https://www.ijrte.org/wpcontent/uploads/papers/v7i5/E1969017519.pdf
  • T. N. Sugumar and N. R. Ramasamy, “mDesk: a scalable and reliable hypervisor framework for effective provisioning of resource and downtime reduction,” J. Supercomput., vol. 76, no. 2, pp. 1277–1292, Feb. 2020, doi: 10.1007/s11227-018-2662-5.
  • A. J. Kadhim and S. A. H. Seno, “Energy-efficient multicast routing protocol based on SDN and fog computing for vehicular networks,” Ad Hoc Networks, vol. 84, pp. 68–81, 2019, doi: 10.1016/j.adhoc.2018.09.018.
  • L. Yao, J. Wang, X. Wang, A. Chen, and Y. Wang, “V2X Routing in a VANET Based on the Hidden Markov Model,” IEEE Trans. Intell. Transp. Syst., vol. 19, no. 3, pp. 889–899, 2018, doi: 10.1109/TITS.2017.2706756.
  • K. A. Awan, I. Ud Din, A. Almogren, M. Guizani, and S. Khan, “StabTrust-A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks,” IEEE Access, vol. 8, pp. 21159–21177, 2020, doi: 10.1109/ACCESS.2020.2968948.
  • R. Yarinezhad, “Reducing delay and prolonging the lifetime of wireless sensor network using efficient routing protocol based on mobile sink and virtual infrastructure,” Ad Hoc Networks, vol. 84, pp. 42–55, Mar. 2019, doi: https://doi.org/10.1016/j.adhoc.2018.09.016.
  • D. BD 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.
  • S. Maurya, V. K. Jain, and D. R. Chowdhury, “Delay aware energy efficient reliable routing for data transmission in heterogeneous mobile sink wireless sensor network,” J. Netw. Comput. Appl., vol. 144, pp. 118–137, 2019, doi: https://doi.org/10.1016/j.jnca.2019.06.012.
  • S. Jain, K. K. Pattanaik, and A. Shukla, “QWRP: Query-driven virtual wheel based routing protocol for wireless sensor networks with mobile sink,” J. Netw. Comput. Appl., vol. 147, p. 102430, 2019, doi: https://doi.org/10.1016/j.jnca.2019.102430.
  • P. Srinivasa Ragavan and K. Ramasamy, “Software defined networking approach based efficient routing in multi-hop and relay surveillance using Lion Optimization algorithm,” Comput. Commun., vol. 150, pp. 764–770, 2020, doi: 10.1016/j.comcom.2019.11.033.
  • Z. Sun, M. Wei, Z. Zhang, and G. Qu, “Secure Routing Protocol based on Multi-objective Ant-colony-optimization for wireless sensor networks,” Appl. Soft Comput. J., vol. 77, pp. 366–375, Apr. 2019, doi: 10.1016/j.asoc.2019.01.034.
  • W. Qi, Q. Song, X. Kong, and L. Guo, “A traffic-differentiated routing algorithm in Flying Ad Hoc Sensor Networks with SDN cluster controllers,” J. Franklin Inst., vol. 356, no. 2, pp. 766–790, 2019, doi: 10.1016/j.jfranklin.2017.11.012.
  • F. Al-Turjman, “Cognitive routing protocol for disaster-inspired Internet of Things,” Futur. Gener. Comput. Syst., vol. 92, pp. 1103– 1115, Mar. 2019, doi: 10.1016/j.future.2017.03.014.
  • R. W. L. Coutinho, A. Boukerche, and A. A. F. Loureiro, “A novel opportunistic power controlled routing protocol for internet of underwater things,” Comput. Commun., vol. 150, pp. 72–82, Jan. 2020, doi: 10.1016/j.comcom.2019.10.020.
  • R. Yarinezhad and S. N. Hashemi, “Solving the load balanced clustering and routing problems in WSNs with an fpt-approximation algorithm and a grid structure,” Pervasive Mob. Comput., vol. 58, p. 101033, 2019, doi: 10.1016/j.pmcj.2019.101033.
  • M. Vigenesh and R. Santhosh, “An efficient stream region sink position analysis model for routing attack detection in mobile ad hoc networks,” Comput. Electr. Eng., vol. 74, pp. 273–280, 2019, doi: 10.1016/j.compeleceng.2019.02.005.
  • K. N. Qureshi, S. Din, G. Jeon, and F. Piccialli, “Link quality and energy utilization based preferable next hop selection routing for wireless body area networks,” Comput. Commun., vol. 149, pp. 382– 392, 2020, doi: 10.1016/j.comcom.2019.10.030.
  • S. Rashidibajgan and R. Doss, “Privacy-preserving history-based routing in Opportunistic Networks,” Comput. Secur., vol. 84, pp. 244– 255, 2019, doi: 10.1016/j.cose.2019.03.020.
  • E. P. M. Câmara Júnior, L. F. M. Vieira, and M. A. M. Vieira, “CAPTAIN: A data collection algorithm for underwater optical-acoustic sensor networks,” Comput. Networks, vol. 171, p. 107145, Apr. 2020, doi: 10.1016/j.comnet.2020.107145.
  • J. Ramkumar and R. Vadivel, “Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks,” Wirel. Pers. Commun., vol. 120, no. 2, pp. 887–909, Apr. 2021, doi: 10.1007/s11277-021- 08495-z.
  • R. Jaganathan 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, 2021, doi: 10.12785/ijcds/100196.
  • J. Xu et al., “Data transmission method for sensor devices in internet of things based on multivariate analysis,” Meas. J. Int. Meas. Confed., vol. 157, p. 107536, Jun. 2020, doi: 10.1016/j.measurement.2020.107536.
  • G. Han, M. Xu, Y. He, J. Jiang, J. A. Ansere, and W. Zhang, “A dynamic ring-based routing scheme for source location privacy in wireless sensor networks,” Inf. Sci. (Ny)., vol. 504, pp. 308–323, 2019, doi: https://doi.org/10.1016/j.ins.2019.07.028.

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  • Minimizing Energy Consumption in Vehicular Sensor Networks Using Relentless Particle Swarm Optimization Routing

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Authors

A. Senthilkumar
Department of Computer Science, Skyline University, Nigeria
J. Ramkumar
Department of Computer Science, Dr. N.G.P. Arts and Science College, Tamil Nadu, India
M. Lingaraj
Department of Computer Science and Applications, Sankara College of Science and Commerce, Tamil Nadu, India
D. Jayaraj
Department of Computer Science and Engineering, Annamalai University, Tamil Nadu, India
B. Sureshkumar
Department of Computer and Information Science, Annamalai University, Tamil Nadu, India

Abstract


Increasing traffic issues, particularly in highly populated nations, have prompted recent interest in Vehicular Sensor Networks (VSNETs) from academics in several fields. Accident rates continue to rise, highlighting the need for a highly functional Smart Transport System (STS). Improvements to the STS should not be spread thin across the board but should concentrate on improving traffic flow, maintaining system reliability, and decreasing vehicle carbon dioxide and methane emissions. Current routing protocols for VSNETs consider various scenarios and approaches to provide safe and effective vehicle-to-infrastructure communication. The reliability of vehicle connections during data transmission has not been well explored. This paper proposes a Relentless Particle Swarm Optimization based Routing Protocol (RPSORP) for VSNET to use vehicle kinematics and mobility to identify vehicle location, send routing information packets to road-side devices, and choose the most reliable path for travel. RPSORP optimizes local and global search to minimize energy consumption in VSNET. The RPSORP is evaluated in the GNS3 simulator using Throughput, Packet Delivery, Delay, and Energy Consumption metrics. RPSORP has superior performance than state-of-the-art routing protocols.

Keywords


VSNET, Routing, Swarming, PSO, Local-Search, Global-Search.

References





DOI: https://doi.org/10.22247/ijcna%2F2023%2F220737