Efficient Mechanisms and Performance Analysis of Routing Protocols in VANETs for Realistic Scenarios

Efficient Mechanisms and Performance Analysis of Routing Protocols in VANETs for Realistic Scenarios

Christos Bouras, Vaggelis Kapoulas, Enea Tsanai
DOI: 10.4018/IJITN.2016070103
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Abstract

Vehicular Ad Hoc Networks (VANETs) are considered as a special case of mobile Ad Hoc Networks (MANETs) and are recently gaining a great attention from the research community. The need for improved road safety, traffic efficiency and direct communication along with the great complexity in routing, makes VANETs a highly challenging field. Routing in VANETs has to adapt to special characteristics such as high speed and road pattern movement as well as high linkage break probability. In this work, the authors show that traditional MANET routing protocols cannot efficiently handle the challenges in a VANET environment and thus need further modifications. For this reason, they propose and implement an enhancement mechanism, applied to the GPSR routing protocol that adapts to the needs of a VANET. The proposed mechanism's performance is evaluated through simulation sets for urban and highway scenarios and compared to the performance of the most common MANET routing protocols adopted in VANETs. The proposed enhancement is shown to be considerably beneficial and it significantly outperforms the rest of the tested routing protocols for almost every topology setting.
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1. Introduction

Vehicular Ad Hoc Networks (VANETs) are a special class of mobile Ad Hoc Networks (MANETs) with unique characteristics. Similar to MANETs, VANETs are an autonomous and self-configured wireless network that allows communications without any dependency on infrastructures or a central coordinator. Any vehicle can be an active node in a VANET if equipped with wireless transceivers. Most nodes in a VANET are continuously moving with a wide range of speeds and directions in the same way as a vehicle moves in a roadway or an urban area. The moving rates in a VANET are in the general case higher than that in a typical MANET but more predictable for nodes traveling on the same direction. This means that nodes in a VANET moving towards the same direction in a roadway, maintain similar speeds and thus longer radio communication periods of time than those moving in opposite directions. Another unique characteristic of VANETs is their challenging surrounding environment that contains blocks of buildings, roadways that limit the possible node movements and roadside infrastructures that may provide access points to the internet along with a rich variety of services and applications.

The unique nature of VANETs, provides some key advantages over MANETs but also some challenging issues. A main advantage is the unlimited battery power of the vehicle when moving and the high energy levels that allow exceptionally high bandwidth links and integration with new technologies like LTE systems. However, a very important challenge in VANETs is the routing performance (Maan & Mazhar, 2011). Importing existing MANET routing protocols directly into VANETs could lead to abyssal network performance and unsatisfactory performance. Compared to MANETs, the node movement in VANETs is more predictable allowing more effective position allocation algorithms and routing protocols that benefit from GPS and electronic maps. However, the node density may vary a lot due to traffic conditions. An important issue in the environment of VANETs is the presence of buildings in urban areas, which adds negative effects on wireless communications and especially on multipath routes. Implementing a routing protocol able to select the best possible path which avoids passing through buildings and other obstacles in the topology is not an easy task.

In this work, we conduct an experimental performance evaluation of various routing approaches in MANETs, using simulations, for the case of VANETs in different topology and propagation settings, focusing on realistic conditions. The aim is to show that traditional MANET routing protocols need further extensions before their adaption in VANETs and that special characteristic of VANETs have to be used in the routing layer. The VANETs scenarios that are studied in this work are 3: highways, urban areas and Manhattan-Grid like urban areas with buildings affecting the propagation. We also propose an enhancement of the GPSR protocol that takes into account: (a) the dynamics of vehicles in order to estimate future positioning and (b) the nature of the urban environment in order to avoid transmissions through building obstacles and preserve longer route TTLs. This study compares the AODV (Ad Hoc On-Demand Distance Vector), DSDV (Destination Sequenced Distance Vector), DSR (Dynamic Source Routing), OLSR (Optimized Link State Routing), GPSR (Greedy Perimeter Stateless Routing) and the proposed modified GPSR, and measures the packet delivery ratio, the end-to-end delay and the power consumption for each routing protocol. The results show that in many cases, the performance of the studied routing protocols is not satisfactory, especially when the propagation model takes into account the buildings’ presence. However, the proposed enhancement to the GPSR protocol outperforms the other protocols in all cases and shows a highly satisfactory average performance.

The following of this work is organized as follows: Section 2 refers to previous work that is related to the purpose and field of study of this work; Section 3 provides an overview of the routing protocols used in MANETs and VANETs that are the subject of study, and describes the challenges associated with VANETs in an urban setting; Section 4 presents the main challenges and problems of routing in VANETs that this work aims to solve; Section 5 describes the proposed enhancement to the GPRS protocol (named GPRS-Modified of GPRS-M for short); Section 6 presents the simulation setting and the reference scenarios; Section 7 presents and discusses the results from the simulations; Section 8 gives the conclusions of this work and finally section 9 describes ideas and directions for future work.

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