A New Comprehensive RSU Installation Strategy for Cost-Efficient VANET Deployment

软件部署 车载自组网 计算机科学 无线自组网 计算机网络 网格 钥匙(锁) 无线 分布式计算 计算机安全 电信 几何学 数学 操作系统
作者
Donghyun Kim,Yesenia Velasco,Wei Wang,R. Uma,Rasheed Hussain,Sejin Lee
出处
期刊:IEEE Transactions on Vehicular Technology [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1 被引量:118
标识
DOI:10.1109/tvt.2016.2598253
摘要

Recently, studies on vehicular ad hoc networks (VANETs) are booming due to their huge potential. The road side unit (RSU) is a key component of the VANET infrastructure connecting mobile vehicles to the rest of the infrastructure. To maximize the availability of RSUs, RSUs should be densely deployed. Otherwise, blind spots may exist in which vehicles lose the connection to the infrastructure. Unfortunately, the massive deployment of RSUs to seamlessly cover the whole area of interest, which could be a vast metropolitan, can be very expensive. As the effectiveness and the benefits of the VANET have yet to be fully proven, such large scale deployment can hardly be a currently viable option. Motivated by this observation, this paper investigates a new strategy of how to best deploy RSUs so that their spatiotemporal coverage is maximized under a limited budget. In detail, for the first time in the literature, we consider an innovative RSU deployment framework, which is a well-balanced combination of three different approaches: deploying RSUs on static locations, public mobile transportation, and fully controllable vehicles owned by the local government. We first introduce a new strategy to abstract a map of city area into a grid graph. Then, we formulate the problem as a new optimization problem and show its NP-hardness. To solve this problem, we transform this problem into another optimization problem. Then, we propose a new polynomial running time approximation algorithm for the problem and show that the performance ratio (the ratio between the quality of an output of the proposed algorithm and the quality of the best possible solution) is at least half of the best possible ratio. We also conduct simulations under various settings to study the effectiveness of the proposed approach.
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