Title

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

Department

Computer Science

Document Type

Article

Publication Date

8-4-2016

Abstract

Recently, the studies on vehicular adhoc network (VANET) are booming due to the huge potential. Road side unit (RSU) is a key component of the VANET infrastructure connecting mobile vehicles and 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 are not fully proven yet, such large scale deployment can hardly be a viable option as of today. Motivated by this observation, this paper investigates a new strategy to best deploy RSUs so that their spatio-temporal 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 setting to study the effectiveness of the proposed

Journal

IEEE Vehicular Technology Society

Journal ISSN

1939-9359

Volume

PP

Issue

99

First Page

1

Last Page

13

Digital Object Identifier (DOI)

10.1109/TVT.2016.2598253