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AC-RDV: a novel ant colony system for roadside units deployment in vehicular ad hoc networks

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AC-RDV: a novel ant colony system for roadside units deployment in vehicular ad hoc networks

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dc.contributor.author Guerna, Abderrahim es_ES
dc.contributor.author Bitam, Salim es_ES
dc.contributor.author Tavares De Araujo Cesariny Calafate, Carlos Miguel es_ES
dc.date.accessioned 2021-07-01T03:32:24Z
dc.date.available 2021-07-01T03:32:24Z
dc.date.issued 2021-03 es_ES
dc.identifier.issn 1936-6442 es_ES
dc.identifier.uri http://hdl.handle.net/10251/168599
dc.description.abstract [EN] Vehicular ad hoc network (VANET) is a mobile and wireless network that consists of connected vehicles, and stationary nodes called roadside units (RSUs) placed on the aboard of roads to improve traffic safety and to ensure drivers' and passengers' comfort. However, deploying RSUs is one of the most important challenges in VANETs due to the involved placement, configuration, and maintenance costs in addition to the network connectivity. This study focuses on the issue of deploying a set of RSUs that is able to maximize network coverage with a reduced cost. In this paper, we propose a new formulation of RSUs deployment issue as a maximum intersection coverage problem through a graph-based modeling. Moreover, we propose a new bio-inspired RSU placement system called Ant colony optimization system for RSU deployment in VANET (AC-RDV). AC-RDV is based on the idea of placing RSUs within the more popular road intersections, which are close to popular places like touristic and commercial areas. Since RSU deployment problem is considered as NP-Hard, AC-RDV inspires by the foraging behavior of real ant colonies to discover the minimum number of RSU intersections that ensures the maximum network connectivity. After a set of simulations and comparisons against traditional RSU placement strategies, the results obtained showed the effectiveness of the proposed AC-RDV in terms of number of RSUs placed, the average area coverage, the average connectivity and the overlapping ratio. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Peer-to-Peer Networking and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject VANET es_ES
dc.subject RSU deployment es_ES
dc.subject Intersection-coverage es_ES
dc.subject Ant colony system es_ES
dc.subject Dynamic heuristic function es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title AC-RDV: a novel ant colony system for roadside units deployment in vehicular ad hoc networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s12083-020-01011-3 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Guerna, A.; Bitam, S.; Tavares De Araujo Cesariny Calafate, CM. (2021). AC-RDV: a novel ant colony system for roadside units deployment in vehicular ad hoc networks. Peer-to-Peer Networking and Applications. 14(2):627-643. https://doi.org/10.1007/s12083-020-01011-3 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s12083-020-01011-3 es_ES
dc.description.upvformatpinicio 627 es_ES
dc.description.upvformatpfin 643 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\420547 es_ES
dc.description.references Mejri MN, Ben-Othman J, Hamdi M (2018) Survey on security challenge and possible cryptographic solutions. Vehic Commun 1(2):53–66 es_ES
dc.description.references Hanshi SM, Wan T, Kadhum MM, Bin-Salem AA (2018) Review of geographic forwarding strategies for inter-vehicular communications from mobility and environment perspectives. Vehic Commun 14:64–79 es_ES
dc.description.references Bitam S, Mellouk A (2014) Routing for vehicular Ad Hoc networks, Bio-Inspired Routing Protocols for Vehicular Ad Hoc Networks, Wiley Edition es_ES
dc.description.references Muhammad M, Safdar GA (2018) Survey on existing authentication issues for cellular-assisted V2X communication. Vehic Commun 12:50–65 es_ES
dc.description.references Wang Z, Zheng J, Wu Y, Mitton N (2017) A centrality-based RSU deployment approach for vehicular ad hoc networks. In : 2017 IEEE International Conference on Communications (ICC). IEEE, p 1–5 es_ES
dc.description.references Liu H, Ding S, Yang L, Yang T (2014) A -based strategy for roadside units placement in vehicular ad hoc networks. Int J Hybrid Info Technol 7(1):91–108 es_ES
dc.description.references Trullols O, Fiore M, Casetti C, Chiasserini C, Ordinas JB (2010) Planning roadside infrastructure for information dissemination in intelligent transportation systems. Comput Commun 33(4):432–442 es_ES
dc.description.references Papadimitriou CH, Steiglitz K (1998) Combinatorial optimization: algorithms and complexity. Courier Corporation es_ES
dc.description.references Hromkovič J (2013) Algorithmics for hard problems: introduction to combinatorial optimization, randomization, approximation, and heuristics, ed: Springer Science & Business Media es_ES
dc.description.references Jo Y, Jeong J (2016) RPA: Road-Side Units Placement Algorithm for Multihop Data Delivery in Vehicular Networks. In: IEEE 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp 262–266 es_ES
dc.description.references Chi J, Jo Y, Park H, Park S (2013) Intersection-priority based optimal RSU allocation for VANET, in: Fifth International Conference on Ubiquitous and Future Networks (ICUFN), pp 350–355 es_ES
dc.description.references Dorigo M, Birattari M, Blum C, Gambardella LM, Mondada F, Stützle T (2004) Ant Colony Optimization and Swarm Intelligence, In: 6th International Conference (ANTS), Belgium, ed: Springer, 5217 es_ES
dc.description.references Guerna A, Bitam S (2019) GICA: An evolutionary strategy for roadside units deployment in vehicular networks,in: International Conference on Networking and Advanced Systems (ICNAS). IEEE, p 1–6 es_ES
dc.description.references Liya X, Chuanhe H, Peng L, Junyu Z (2013) A Randomized Algorithm for Roadside Units Placement in Vehicular Ad Hoc, In: IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks MSN, pp 193–197 es_ES
dc.description.references Liu C, Huang H, Du H (2017) Optimal RSUs deployment with delay bound along highways in VANET. J Comb Optim 33(4):1168–1182 es_ES
dc.description.references Aslam B, Amjad F, Zou CC (2012) Optimal roadside units placement in urban areas for vehicular networks. In: IEEE Symposium on Computers and Communications ISCC, pp 423–429 es_ES
dc.description.references Patil P, Gokhale A (2013) Voronoi-based placement of road-side units to improve dynamic resource management in Vehicular Ad Hoc Net-works. In: International Conference on Collaboration Technologies and Systems (CTS), pp 389–396 es_ES
dc.description.references Ghorai C, Banerjee I (2018) A constrained Delaunay triangulation based RSUs deployment strategy to cover a convex region with obstacles for maximizing communications probability between V2I. Vehic Commun 13:89–103 es_ES
dc.description.references Cavalcante ES, Aquino AL, Pappa GL (2012) Roadside unit deployment for information dissemination in a VANET: an evolutionary approach, In: Proceedings of the 14th annual conference companion on genetic and evolutionary computation, ACM, New York, pp. 27–34 es_ES
dc.description.references Sarubbi JFM, Vieira D, Wanner E, Silva CM (2016) A GRASP-based heuristic for allocating the roadside infrastructure maximizing the number of distinct vehicles experiencing contact opportunities. IEEE Symposium on Network Operations and Management (NOMS), pp 1187–1192 es_ES
dc.description.references Kim D, Velasco Y, Wang W, Uma RN, Hussain R, Lee S (2017) A new comprehensive RSU installation strategy for cost-efficient VANET deployment. IEEE Trans Veh Technol 66(5):4200–4211 es_ES
dc.description.references Irit D, Safra S (2005) On the hardness of approximating minimum vertex cover. Annals Math: 439–485 es_ES
dc.description.references Srinivanas M, Patnaik LM (1994) Genetic algorithms: A survey. Computer 27(6):17–26 es_ES
dc.description.references Dorigo M, Gambardella LM (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53–66 es_ES
dc.description.references Dorigo M, Caro GD, Gambardella LM (1999) Ant algorithms for discrete optimization. Art&Life 5(2):137–172 es_ES
dc.description.references Jovanovic R, Tuba M (2011) An ant colony optimization algorithm with improved pheromone correction strategy for the minimum weight vertex cover problem. Appl Soft Comput 11(8):5360–5366 es_ES
dc.description.references Reis AB, Sargento S, Neves F (2014) Deploying roadside units in sparse vehicular networks: What really works and what does not. IEEE Trans Veh Technol 63(6):2794–2806 es_ES
dc.description.references Lessing L, Dumitrescu I, Stützle T (2004) A comparison between ACO algorithms for the set covering problem, in: International Workshop on ant colony optimization and swarm, ed: Springer, Berlin, pp 1–12 es_ES
dc.description.references Zaki MJ, Meira W Jr (2014) Data mining and analysis fundamental concept and algorithms. Cambridge University Press, Cambridge es_ES


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