Nature-inspired metaheuristics for optimizing information dissemination in vehicular networks

Masegosa, Antonio D.; Osaba, Eneko; Angarita-Zapata, Juan S.; Laña, Ibai; Ser, Javier Del

doi:10.1145/3319619.3326847

Cited by 3 publications

(9 citation statements)

References 46 publications

(71 reference statements)

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“…In terms of the evidence of discretized MOAs deployed in VANET, authors in [25] investigated discrete versions of the bat, firefly, CSO, and PSO algorithms. The uniform cross over and swapping functions were adopted with results demonstrating better performances by the bat, firefly, and PSO algorithms.…”

Section: A Evidence Prior To the Present Studymentioning

confidence: 99%

“…Essentially, most MOAs are designed to solve continuous optimization problems, thus, it is pertinent to accurately describe the adaptation as well as the codification process of these continuous-based MOAs to their discrete versions, which is the form required to solve combinatorial problems in VANETs. However, with an exception to the approaches in [25], [26], most articles mentioned above lack the required details needed to understand the discretization processes used in their respective implementations, which limits their use and stifles the replication of these methods for further investigations.…”

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

“…The details of the DCSO algorithm adopted in [25] leaves much to be desired since authors simply mentioned that the uniform crossover and swapping functions were used, without providing sufficient details with regards to its implementation process. Instead, authors simply mentioned that they adopted the DCSO version proposed in [8], which was designed to address the travelling salesman problem (TSP).…”

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

“…Instead, authors simply mentioned that they adopted the DCSO version proposed in [8], which was designed to address the travelling salesman problem (TSP). While the approach in [8] adopted a 2-opt and double-bridge operator to introduce new solutions, authors in [25] used the uniform crossover and swap operators, which may have been responsible for the contradictory report of a poorer DCSO performance in [25] as against the improved performance of the DCSO algorithm reported in [8]- [10]. Further, the DCSO variant reported in [25] performed least in comparison to the bat, firefly, and PSO algorithms, which contradicts reports in [9] about the superior performance of the DCSO algorithm against other well-known protocols.…”

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

“…While the approach in [8] adopted a 2-opt and double-bridge operator to introduce new solutions, authors in [25] used the uniform crossover and swap operators, which may have been responsible for the contradictory report of a poorer DCSO performance in [25] as against the improved performance of the DCSO algorithm reported in [8]- [10]. Further, the DCSO variant reported in [25] performed least in comparison to the bat, firefly, and PSO algorithms, which contradicts reports in [9] about the superior performance of the DCSO algorithm against other well-known protocols. Thus, such a poor performance of the DCSO algorithm as reported in [25] leaves much room for improvement since incidentally, authors claimed that the same operators, i.e the uniform crossover and swapping functions were used in all the MOAs compared therein.…”

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

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New Discrete Cuckoo Search Optimization Algorithms for Effective Route Discovery in IoT-Based Vehicular Ad-Hoc Networks

et al. 2020

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Recently, the Internet of Things (IoT) is widely considered in vehicular ad-hoc networks (VANETs) for use in intelligent transportation systems. In particular, the pervasive deployment of different sensors in modern vehicles has unlocked interesting possibilities for improving routing performance in VANETs. Nevertheless, the discovery of short single loop-free routes for effective and efficient information dissemination in VANETs remains a challenge. This challenge proves more difficult to solve since it reduces to the case of finding the shortest Hamiltonian path for effective routing in VANETs. Consequently, in this paper, we propose two discretized variants of the cuckoo search optimization (CSO) algorithm, namely, the Lévy flight-based discrete CSO (LF-DCSO) and the random walk-based discrete CSO (RW-DCSO) for effective route discovery in VANETs. In addition, we investigated the inverse mutation operator gleaned from genetic algorithm (GA) in order to improve the exploration properties of our DCSO variants. We describe a new objective function that effectively models the reliability of individual links between nodes that comprise a single route. A detailed report of the routing protocol that controls the routing process is presented. Our proposed methods were compared against the roulette wheel-based GA and the improved kmeans-based GA termed IGAROT. Specifically, our findings reveal that there was no significant difference in the performance of the different methods in the low vehicle density scenario, however, in the medium vehicle density scenario, the RW-DCSO algorithm achieved 2.56%, 100%, and 128.57% percentage increment in its route reliability score over the LF-DCSO, RW-GA, and IGAROT algorithms, respectively. Whereas in the high vehicle density scenario, the LF-DCSO algorithm achieved a percentage increment of 42.85%, 525%, and 733.33% in the route reliability score obtained over the RW-DCSO, IGAROT, and RW-GA algorithms, respectively. Such results suggest that our methods are able to guarantee effective routing in VANETs.

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Section: A Evidence Prior To the Present Studymentioning

confidence: 99%

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

Section: B Gaps In Prior Studiesmentioning

confidence: 99%

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New Discrete Cuckoo Search Optimization Algorithms for Effective Route Discovery in IoT-Based Vehicular Ad-Hoc Networks

et al. 2020

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Internet of Vehicles and Intelligent Routing: A Survey-Based Study

Hassan

Attia

Rizk

2022

The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022)

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An Intelligent Optimized Route-Discovery Model for IoT-Based VANETs

Karunanidy¹,

Ramalingam²,

Dumka³

et al. 2021

Processes

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Intelligent Transportation system are becoming an interesting research area, after Internet of Things (IoT)-based sensors have been effectively incorporated in vehicular ad hoc networks (VANETs). The optimal route discovery in a VANET plays a vital role in establishing reliable communication in uplink and downlink direction. Thus, efficient optimal path discovery without a loop-free route makes network communication more efficient. Therefore, this challenge is addressed by nature-inspired optimization algorithms because of their simplicity and flexibility for solving different kinds of optimization problems. NIOAs are copied from natural phenomena and fall under the category of metaheuristic search algorithms. Optimization problems in route discovery are intriguing because the primary objective is to find an optimal arrangement, ordering, or selection process. Therefore, many researchers have proposed different kinds of optimization algorithm to maintain the balance between intensification and diversification. To tackle this problem, we proposed a novel Java macaque algorithm based on the genetic and social behavior of Java macaque monkeys. The behavior model mimicked from the Java macaque monkey maintains well-balanced exploration and exploitation in the search process. The experimentation outcome depicts the efficiency of the proposed Java macaque algorithm compared to existing algorithms such as discrete cuckoo search optimization (DCSO) algorithm, grey wolf optimizer (GWO), particle swarm optimization (PSO), and genetic algorithm (GA).

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Nature-inspired metaheuristics for optimizing information dissemination in vehicular networks

Cited by 3 publications

References 46 publications

New Discrete Cuckoo Search Optimization Algorithms for Effective Route Discovery in IoT-Based Vehicular Ad-Hoc Networks

New Discrete Cuckoo Search Optimization Algorithms for Effective Route Discovery in IoT-Based Vehicular Ad-Hoc Networks

Internet of Vehicles and Intelligent Routing: A Survey-Based Study

An Intelligent Optimized Route-Discovery Model for IoT-Based VANETs

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