Enhancing OLSR protocol in VANETs with multi-objective particle swarm optimization

Hanlin Yang, Cunlai Pu, Jiexin Wu, Yanqing Wu and Yongxiang Xia

Physica A: Statistical Mechanics and its Applications, 2023, vol. 614, issue C

Abstract: The Optimized Link State Routing Protocol (OLSR) is envisioned as one of the key components to the operation of future vehicular ad hoc networks (VANETs). Its performance is however fairly constrained in the vehicular communication environment due to the limited coverage of wireless transmission and high-speed movement of nodes. In this brief, we propose a multi-objective particle swarm optimization (MOPSO) framework to enhance the performance of OLSR in VANETs. Specifically, we formulate a multi-objective optimization problem (MOP) considering not only the quality of service (QoS), including throughput, delay and packet loss rate, but also the cost of service, i.e., routing load. We solve this MOP with MOPSO and obtain the Pareto front corresponding to the optimal equilibrium of performance and cost. In the experiment, our optimization framework is used in a general setting of VANETs to obtain the optimal parameters of OLSR, i.e., Hello and TC intervals, and these parameters are further validated in realistic VANET scenarios. Our optimization framework can be naturally extend to other dynamic routing protocols in networks.

Keywords: VANETs; OLSR; Multi-objective optimization; Particle swarm optimization (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:614:y:2023:i:c:s0378437123001255

DOI: 10.1016/j.physa.2023.128570

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