Design and evaluation of two geocast protocols for vehicular ad-hoc networks

Vehicular ad-hoc networks (VANETs) offer a large number of new potential applications. One of the envisioned applications is of course Internet access, which can be provided with the help of some roadside basestations. Many of the applications benefit from multi-hop relaying of information, thus requiring a routing protocol. Characteristics unique to VANETs (such as high mobility and the need for geographical addressing) make many conventional ad hoc routing protocols unsuitable. In this paper we design and evaluate two different, so called, geocast protocols for VANETs. One protocol is designed for fast communication across a large area. The purpose of the other protocol is to provide a routing service for a future reliable transport protocol (enabling Internet applications). We evaluate the performance of the protocols using realistic network and traffic models

VANET Applications Under Loss Scenarios & Evolving Wireless Technology

In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a one-vehicle look-ahead CACC platoon under different network loss scenarios, and propose to adapt the time headway parameter of the model according to a network reliability metric that we defined based on packet burst loss length to maximize traffic flow efficiency while maintaining a string stable platoon. Our findings show that careful adjustment of headway value according to the wireless network reliability allows the platoon to maintain string stable operation while maximizing traffic flow. We also study the impact that evolving wireless technology can have on VANET applications such as CACC, where we study the performance when using DSRC and 5G NR V2X. In addition, we study the evolution of RATs used in VANET application, and we propose DSRC+, as a possible enhancement to traditional DSRC, that utilizes modern modulation/coding schemes and performs random blind retransmission to improve packet delivery ratio. We finally study the trade-offs in the choice of RAT in VANET applications such as CACC, concluding that RATs with time-division channel access can be reliable with lower packet loss, but performs poorly when needing to disseminate messages over longer CACC platoons

Reliable Neighborcast Protocol for Vehicular Ad hoc Networks

This dissertation introduces a new communication paradigm, neighborcast, for vehicular ad hoc networks and proposes a new communication protocol, reliable neighborcast protocol (RNP), to implement the paradigm. Vehicular applications such as collision avoidance can benefit from allowing vehicles to communicate with their nearby vehicles in order to coordinate movements. Neighborcast is a new paradigm for communications between each vehicle and all nearby vehicles that are within a specified distance from it i.e., its neighbors. In neighborcast, each vehicle has its own set of vehicles with which it wants to communicate i.e., the set of its neighbors, which is different from that of other vehicles. Our proposed communication protocol, RNP, is aimed at providing reliable neighborcast communications. It provides guaranteed message delivery from each vehicle in a vehicular ad hoc network to all of its neighbors within a bounded delay, ensures that all the neighbors that receive the same messages sequence them in the same order and use each of them at the same time, and provides the neighbors the knowledge of whether all of the other neighbors have received the message or which neighbors are missing the message. The implementation of RNP is significantly different from reliable multicast/broadcast protocols. In a reliable multicast/broadcast protocol, all communicating vehicles are in one group. But in our RNP, the group size is constrained to limit the communication delay, so we cannot have all vehicles in one group. As a result, we organize vehicles into several overlapping groups and each vehicle may communicate in more than one overlapping group. RNP is created as an overlay protocol on top of overlapping broadcast groups that use a modified version of a recently invented reliable broadcast protocol, M-RBP, and transfers the guarantees provided by the modified M-RBP from the broadcast group level to the neighborhood level. RNP is composed of two parts. The first is the self-organizing protocol that organizes vehicles into overlapping broadcast groups that use the modified version of M-RBP. The self-organizing protocol ensures that each vehicle is always a member of at least one broadcast group containing itself and all of its neighbors. This way, it can reach all of its neighbors by transmitting messages in one broadcast group, resulting in the same message sequencing for all neighbors. The self-organizing protocol also limits the size of each broadcast group to limit the message delivery delay, limits the number of broadcast groups of which a vehicle is a member to limit the number of recovery messages, and moves the broadcast groups with the vehicles to limit the rate at which a vehicle changes groups. The second part of RNP is the mechanism that transfers the guarantees from M-RBP to provide the RNP guarantees. In this dissertation, we also show an example of using RNP in conjunction with sensors to avoid rear-end collisions. We propose a simple set of rules for using RNP with sensors to automatically maintain a safe following distance, provide warnings of emergency situations, and negotiate the safe deceleration rates among nearby communicating vehicles. We quantify the highway capacity improvement from using RNP and compare it with that of using sensors alone