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Practical algorithms for allocating the roadside units in VANET
- Source :
- IET Intelligent Transport Systems. 14:103-109
- Publication Year :
- 2020
- Publisher :
- Institution of Engineering and Technology (IET), 2020.
-
Abstract
- The vehicle-to-infrastructure communication is a kind of communication mode of the vehicular ad-hoc network (VANET). It is paramount to allocate roadside units (RSUs) appropriately to assure the quality of communication service. Sarubbi et al. have proposed a greedy heuristic allocation algorithm Delta-r. It examines the Δ ρ2 ρ1 -deployment constraint, a metric for evaluating the performance of VANET, with relative contact time. Unfortunately, the relative contact time of vehicles at urban cells may present `false high', which would play an opposite effect on making a decision. In order to solve the problem, a new allocation algorithm Delta-uc is presented, which examines the Δ ρ2 ρ1 -deployment constraint with a useful contribution. It gets rid of the negative effect of `extra' contact time by means of retaining merely the contributing relative duration of a vehicle at an urban cell. Furthermore, an effective recombination operator is introduced basing on algorithm Delta-uc, and a parthenogenetic algorithm UCPGA is presented to solve the allocation problem. Experimental comparisons were performed on the real mobility trace of Cologne, Germany. The experimental results demonstrate that in many Δ ρ2 ρ1 -deployments, the number of RSUs produced by the Delta-uc and UCPGA algorithms are, respectively, fewer than those produced by algorithms Delta-r and DeltaGA.
- Subjects :
- 050210 logistics & transportation
Vehicular ad hoc network
Computer science
Mechanical Engineering
05 social sciences
Transportation
010501 environmental sciences
01 natural sciences
Constraint (information theory)
Software deployment
0502 economics and business
Metric (mathematics)
Resource allocation
Duration (project management)
Greedy algorithm
Law
Algorithm
0105 earth and related environmental sciences
General Environmental Science
TRACE (psycholinguistics)
Subjects
Details
- ISSN :
- 17519578
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- IET Intelligent Transport Systems
- Accession number :
- edsair.doi...........b6d7c83a95be0574bb95589f60ba98e6
- Full Text :
- https://doi.org/10.1049/iet-its.2019.0617