1,391 research outputs found

    Modeling and Analysis of Location Service Management in Vehicular Ad Hoc Networks

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    Recent technological advances in wireless communication and the pervasiveness of various wireless communication devices have offered novel and promising solutions to enable vehicles to communicate with each other, establishing a decentralized communication system. An emerging solution in this area is the Vehicular Ad Hoc Networks (VANETs), in which vehicles cooperate in receiving and delivering messages to each other. VANETs can provide a viable alternative in situations where existing infrastructure communication systems become overloaded, fail (due for instance to natural disaster), or inconvenient to use. Nevertheless, the success of VANETs revolves around a number of key elements, an important one of which is the way messages are routed between sources and destinations. Without an effective message routing strategy VANETs' success will continue to be limited. In order for messages to be routed to a destination effectively, the location of the destination must be determined. Since vehicles move in relatively fast and in a random manner, determining the location (hence the optimal message routing path) of (to) the destination vehicle constitutes a major challenge. Recent approaches for tackling this challenge have resulted in a number of Location Service Management Protocols. Though these protocols have demonstrated good potential, they still suffer from a number of impediments, including, signaling volume (particularly in large scale VANETs), inability to deal with network voids and inability to leverage locality for communication between the network nodes. In this thesis, a Region-based Location Service Management Protocol (RLSMP) is proposed. The protocol is a self-organizing framework that uses message aggregation and geographical clustering to minimize the volume of signalling overhead. To the best of my knowledge, RLSMP is the first protocol that uses message aggregation in both updating and querying, and as such it promises scalability, locality awareness, and fault tolerance. Location service management further addresses the issue of routing location updating and querying messages. Updating and querying messages should be exchanged between the network nodes and the location servers with minimum delay. This necessity introduces a persuasive need to support Quality of Service (QoS) routing in VANETs. To mitigate the QoS routing challenge in VANETs, the thesis proposes an Adaptive Message Routing (AMR) protocol that utilizes the network's local topology information in order to find the route with minimum end-to-end delay, while maintaining the required thresholds for connectivity probability and hop count. The QoS routing problem is formulated as a constrained optimization problem for which a genetic algorithm is proposed. The thesis presents experiments to validate the proposed protocol and test its performance under various network conditions

    A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks

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    The initial phase of the deployment of Vehicular Ad-Hoc Networks (VANETs) has begun and many research challenges still need to be addressed. Location privacy continues to be in the top of these challenges. Indeed, both of academia and industry agreed to apply the pseudonym changing approach as a solution to protect the location privacy of VANETs'users. However, due to the pseudonyms linking attack, a simple changing of pseudonym shown to be inefficient to provide the required protection. For this reason, many pseudonym changing strategies have been suggested to provide an effective pseudonym changing. Unfortunately, the development of an effective pseudonym changing strategy for VANETs is still an open issue. In this paper, we present a comprehensive survey and classification of pseudonym changing strategies. We then discuss and compare them with respect to some relevant criteria. Finally, we highlight some current researches, and open issues and give some future directions

    Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

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    We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches
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