1,391 research outputs found
Modeling and Analysis of Location Service Management in Vehicular Ad Hoc Networks
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
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MobileTrust: Secure Knowledge Integration in VANETs
Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy
A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks
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
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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