Guilherme Maia

DRIVE: An efficient and robust data dissemination protocol for highway and urban vehicular ad hoc networks

Abstract Vehicular Ad hoc Networks (VANETs) are an emerging technology that allows vehicles to form self-organized networks without the need of permanent infrastructure. VANETs have attracted the attention of the research community recently as they have opened up a myriad of on the road applications and increased their potential by providing intelligent transport systems. The envisaged applications, as well as some inherent VANET characteristics make data dissemination an essential service and a challenging task in these networks. Many data dissemination protocols have been proposed in the literature. However, most of these protocols were designed to operate exclusively in urban or highway scenarios and under dense or sparse networks. In addition, the existing solutions for data dissemination do not effectively address broadcast storm and network partition problems simultaneously. To tackle these problems, we propose a novel Data dissemination pRotocol In VEhicular networks (DRIVE) that relies exclusively on local one-hop neighbor information to deliver messages under dense and sparse networks. In dense scenarios, DRIVE selects vehicles inside a sweet spot to rebroadcast messages to further vehicles. Moreover, the protocol employs implicit acknowledgements to guarantee robustness in message delivery under sparse scenarios. DRIVE eliminates the broadcast storm problem and maximizes data dissemination capabilities across network partitions with short delays and low overhead. Simulation results show that DRIVE performs data dissemination with better efficiency than other algorithms, outperforming them in different scenarios in all the evaluations carried out.

Data communication in VANETs: Protocols, applications and challenges

Abstract VANETs have emerged as an exciting research and application area. Increasingly vehicles are being equipped with embedded sensors, processing and wireless communication capabilities. This has opened a myriad of possibilities for powerful and potential life-changing applications on safety, efficiency, comfort, public collaboration and participation, while they are on the road. Although, considered as a special case of a Mobile Ad Hoc Network, the high but constrained mobility of vehicles bring new challenges to data communication and application design in VANETs. This is due to their highly dynamic and intermittent connected topology and different application’s QoS requirements. In this work, we survey VANETs focusing on their communication and application challenges. In particular, we discuss the protocol stack of this type of network, and provide a qualitative comparison between most common protocols in the literature. We then present a detailed discussion of different categories of VANET applications. Finally, we discuss open research problems to encourage the design of new VANET solutions.

A distributed data storage protocol for heterogeneous wireless sensor networks with mobile sinks

Abstract This paper presents ProFlex, a distributed data storage protocol for large-scale Heterogeneous Wireless Sensor Networks (HWSNs) with mobile sinks. ProFlex guarantees robustness in data collection by intelligently managing data replication among selected storage nodes in the network. Contrarily to related protocols in the literature, ProFlex considers the resource constraints of sensor nodes and constructs multiple data replication structures, which are managed by more powerful nodes. Additionally, ProFlex takes advantage of the higher communication range of such powerful nodes and uses the long-range links to improve data distribution by storage nodes. When compared with related protocols, we show through simulation that Proflex has an acceptable performance under message loss scenarios, decreases the overhead of transmitted messages, and decreases the occurrence of the energy hole problem. Moreover, we propose an improvement that allows the protocol to leverage the inherent data correlation and redundancy of wireless sensor networks in order to decrease even further the protocol’s overhead without affecting the quality of the data distribution by storage nodes.

HyDi: a hybrid data dissemination protocol for highway scenarios in vehicular ad hoc networks

In this paper we tackle the problem of data dissemination under both well-connected and intermittent connected vehicular ad hoc networks. For such a purpose, we propose HyDi, a data dissemination protocol suited for highway scenarios. HyDi can seamless operate under well-connected networks by applying broadcast suppression techniques in order to avoid contention at the link layer, and also at intermittent connected networks by applying store-carry-forward techniques, thus delivering messages even when there is no end-to-end path. By means of simulation using the recently defined IEEE 802.11p standard, we compare HyDi against the only two existing solutions in the literature --- DV-CAST and SRD --- and we show that HyDi has an overhead as good as DV-CAST, outperforms both protocols when considering the average delay under heavy traffic scenarios, decreases the average number of hops to deliver messages and can deliver data to almost all nodes in a given region of interest.

Traffic aware video dissemination over vehicular ad hoc networks

Video dissemination to a group of vehicles is one of the many fundamental services envisioned for Vehicular Ad hoc Networks. For this purpose, in this paper we describe VoV, a video dissemination protocol that operates under extreme traffic conditions. Contrary to most existing approaches that focus exclusively on always-connected networks and tackle the broadcast storm problem inherent to them, VoV is designed to operate under any kind of traffic condition. We propose a new geographic-based broadcast suppression mechanism that gives higher priority to broadcast to vehicles inside especial forwarding zones. Furthermore, vehicles store and carry received messages in a local buffer in order to forward them to vehicles that were not covered by the first dissemination process, probably as a result of collisions or intermittent disconnections. Finally, VoV employs a rate control mechanism that sets the pace at which messages must be transmitted in an attempt to avoid channel overloading and to overcome the synchronization effects introduced by the channel hopping mechanism employed by IEEE 802.11p. When compared to two well-known solutions -- UV-CAST and AID -- we show that our proposal is more efficient in terms of message delivery, delay and overhead.

Data dissemination in urban Vehicular Ad hoc Networks with diverse traffic conditions

Envisioned applications for VANETs will rely extensively on the exchange of broadcast messages to deliver data to vehicles located in a region of interest. Many data dissemination protocols have been proposed in the literature to suppress this need. Surprisingly, most of them were designed to operate exclusively under dense or sparse networks. However, it is reasonable to assume that diverse traffic conditions will coexist in realistic scenarios. Therefore, data dissemination protocols for VANETs should be designed to perceive the traffic condition at hand and adapt accordingly. With this in mind, in this paper we propose HyDiAck, a data dissemination protocol for urban VANETs that relies exclusively on local one-hop neighbor information to deliver messages under dense and sparse networks. In dense scenarios, HyDiAck selects vehicles inside a forwarding zone to rebroadcast messages to further vehicles. Moreover, the protocol employs implicit acknowledgements to guarantee robustness in message delivery under sparse scenarios. When compared to two related protocols - UV-CAST and slotted-1-persistence - simulation results for both Manhattan grid and real city street scenarios show that HyDiAck decreases both the latency to disseminate messages and the network overhead, and also guarantees message delivery to all vehicles in the region of interest.

Socially inspired data dissemination for vehicular ad hoc networks

People have routines and their mobility patterns vary during the day, which have a direct impact on vehicular mobility. Therefore, proto- cols and applications designed for Vehicular Ad Hoc Networks need to adapt to these routines in order to provide better services. With this issue in mind, in this work, we propose a data dissemination solution for these networks that considers the daily road traffic variation of large cities and the relationship among vehicles. The focus of our approach is to select the best vehicles to rebroadcast data messages according to social metrics, in particular, the clustering coefficient and the node degree. Moreover, our solution is designed in such a way that it is completely independent of the perceived road traffic density. Simulation results show that, when compared to related protocols, our proposal provides better delivery guarantees, reduces the network overhead and possesses an acceptable delay.

A self-adaptive data dissemination solution for intelligent transportation systems

Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and other information, along with the provisioning of convenience applications for passengers. For that, many applications and services use broadcast to perform the transmission of their data to intended recipients. However, due to the wireless medium and the characteristics inherent to vehicular environments, broadcasting becomes a challenging task. For instance, uncoordinated broadcasts may lead to severe packet collisions, thus resulting in network congestion. Such problem is well known as the broadcast storm problem. Moreover, the broadcasting mechanism must handle network disconnections, otherwise, the data delivery capability may be hampered. Although there are many studies that deal with these problems separately, very few consider a solution for both problems. Furthermore, those that handle both problems do not consider different scenarios, i.e., they only focus on urban or highway scenarios. Therefore, to deal with both problems and different scenarios, we propose a preemptive algorithm that automatically adjusts the data transmission process (PREDAT) to reduce the total number of collisions and maximize the data delivery capability across network disconnections. Simulation results show that our proposed solution induces short delays and a low overhead. Moreover, it provides good efficiency with respect to the coverage of the event and the distance to which the information is propagated.

Decreasing greenhouse emissions through an intelligent traffic information system based on inter-vehicle communication

Traffic congestion is an urban mobility problem, which generates stress to drivers and economic losses. In 2012, greenhouse gas emissions from transportation accounted for about 28% of total U.S. greenhouse gas emissions. Intelligent transportation systems can assist in the identification and reduction of vehicular traffic congestion. In this context, this work proposes an intelligent traffic information system based on inter-vehicle communication to avoid vehicle traffic congestion. The main goal of the proposed solution is to decrease CO2 emissions, the average trip time and fuel consumption by avoiding congested roads. Simulation results show that our proposed solution can reduce the average trip time, and the overall CO2 emission and fuel consumption. In particular, the trip time was decreased approximately 86%, the fuel consumption 40% and the CO2 emission 55%. This shows the potential of the proposed solution.

An intelligent transportation system for detection and control of congested roads in urban centers

Traffic jams frustrate drivers and cost billions per year in time and fuel consumption. In order to avoid such problems, this paper presents an intelligent transportation system that collects real-time traffic information and is able to detect and manage traffic congestion based on this information. Simulation results show that the proposed protocol can reduce the average travel time, CO2 emission and fuel consumption. In particular, the average travel time was reduced in approximately 23%, the average fuel consumption in 9% and average CO2 emission in 10%.