726 research outputs found
Characterizing the role of vehicular cloud computing in road traffic management
Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles. © The Author(s) 2017
Hybrid-Vehcloud: An Obstacle Shadowing Approach for VANETs in Urban Environment
Routing of messages in Vehicular Ad-hoc Networks (VANETs) is challenging due
to obstacle shadowing regions with high vehicle densities, which leads to
frequent disconnection problems and blocks radio wave propagation between
vehicles. Previous researchers used multi-hop, vehicular cloud or roadside
infrastructures to solve the routing issue among the vehicles, but they suffer
from significant packet delays and frequent packet losses arising from obstacle
shadowing. We proposed a vehicular cloud based hybrid technique called
Hybrid-Vehcloud to disseminate messages in obstacle shadowing regions, and
multi-hop technique to disseminate messages in non-obstacle shadowing regions.
The novelty of our approach lies in the fact that our proposed technique
dynamically adapts between obstacle shadowing and non-obstacle shadowing
regions. Simulation based performance analysis of Hybrid-Vehcloud showed
improved performance over Cloud-assisted Message Downlink Dissemination Scheme
(CMDS), Cross-Layer Broadcast Protocol (CLBP) and Cloud-VANET schemes at high
vehicle densities
Towards Dynamic Vehicular Clouds
Motivated by the success of the conventional cloud computing, Vehicular Clouds were introduced as a group of vehicles whose corporate computing, sensing, communication, and physical resources can be coordinated and dynamically allocated to authorized users. One of the attributes that set Vehicular Clouds apart from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new computing resources become available while others depart, creating a volatile environment where the task of reasoning about fundamental performance metrics becomes very challenging. The goal of this thesis is to design an architecture and model for a dynamic Vehicular Cloud built on top of moving vehicles on highways. We present our envisioned architecture for dynamic Vehicular Cloud, consisting of vehicles moving on the highways and multiple communication stations installed along the highway, and investigate the feasibility of such systems. The dynamic Vehicular Cloud is based on two-way communications between vehicles and the stations. We provide a communication protocol for vehicle-to-infrastructure communications enabling a dynamic Vehicular Cloud. We explain the structure of the proposed protocol in detail and then provide analytical predictions and simulation results to investigate the accuracy of our design and predictions. Just as in conventional clouds, job completion time ranks high among the fundamental quantitative performance figures of merit. In general, predicting job completion time requires full knowledge of the probability distributions of the intervening random variables. More often than not, however, the data center manager does not know these distribution functions. Instead, using accumulated empirical data, she may be able to estimate the first moments of these random variables. Yet, getting a handle on the expected job completion time is a very important problem that must be addressed. With this in mind, another contribution of this thesis is to offer easy-to-compute approximations of job completion time in a dynamic Vehicular Cloud involving vehicles on a highway. We assume estimates of the first moment of the time it takes the job to execute without any overhead attributable to the working of the Vehicular Cloud. A comprehensive set of simulations have shown that our approximations are very accurate. As mentioned, a major difference between the conventional cloud and the Vehicular Cloud is the availability of the computational nodes. The vehicles, which are the Vehicular Cloud\u27s computational resources, arrive and depart at random times, and as a result, this characteristic may cause failure in executing jobs and interruptions in the ongoing services. To handle these interruptions, once a vehicle is ready to leave the Vehicular Cloud, if the vehicle is running a job, the job and all intermediate data stored by the departing vehicle must be migrated to an available vehicle in the Vehicular Cloud
Securing vehicular cloud networks
Vehicular Cloud Networks (VCN) is the network that ensures mobility and availability of resources allowing new services and applications like Network as a Service (NaaS), STorage as a Service (STaaS), Computation as a Service (CompaaS) and Cooperation as a Service (CaaS). In this paper, we propose a solution to secure the Vehicular Cloud Network (VCN). Our challenge in this work is to adapt the PKI architecture, which is mainly used in wired networks to be used in VCN. To propose a security solution for Vehicular Cloud Networks (VCN), our work is based on three steps; the first one is to make network architecture study, where we tried to highlight the main network components. The second step is to propose the security solution architecture. Finally, the last step is to program a test and validate the solution using a simulation
Efficient Profit Maximization in Reliability Concerned Static Vehicular Cloud System
Modern electric VUs are equipped with a variety of increasingly potent
computing, communication, and storage resources, and with this tremendous
computation power in their arsenal can be used to enhance the computing power
of regular cloud systems, which is termed as vehicular cloud. Unlike in the
traditional cloud computing resources, these vehicular cloud resource moves
around and participates in the vehicular cloud for a sporadic duration at
parking places, shopping malls, etc. This introduces the dynamic nature of
vehicular resource participation in the vehicular cloud. As the user-submitted
task gets allocated on these vehicular units for execution and the dynamic stay
nature of vehicular units, enforce the system to ensure the reliability of task
execution by allocating multiple redundant vehicular units for the task.
In this work, we are maximizing the profit of vehicular cloud by ensuring the
reliability of task execution where user tasks come online manner with
different revenue, execution, and deadline. We propose an efficient approach to
solve this problem by considering (a) task classification based on the deadline
and laxity of the task, (b) ordering of tasks for task admission based on the
expected profit of the task, (c) classification of vehicular units based in
expected residency time and reliability concerned redundant allocation of tasks
of vehicular units considering this classification and (d) handing dynamic
scenario of the vehicular unit leaving the cloud system by copying the maximum
percentage of executed virtual machine of the task to the substitute unit. We
compared our proposed profit maximization approach with the state of art
approach and showed that our approach outperforms the state of art approach
with an extra 10\% to 20\% profit margin
Characterizing the role of vehicular cloud computing in road traffic management
Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles
Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles
Vehicular Ad-hoc Networks (VANET) enable efficient communication between
vehicles with the aim of improving road safety. However, the growing number of
vehicles in dense regions and obstacle shadowing regions like Manhattan and
other downtown areas leads to frequent disconnection problems resulting in
disrupted radio wave propagation between vehicles. To address this issue and to
transmit critical messages between vehicles and drones deployed from service
vehicles to overcome road incidents and obstacles, we proposed a hybrid
technique based on fog computing called Hybrid-Vehfog to disseminate messages
in obstacle shadowing regions, and multi-hop technique to disseminate messages
in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to
changes in an environment and benefits in efficiency with robust drone
deployment capability as needed. Performance of Hybrid-Vehfog is carried out in
Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators.
The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message
Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP),
PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data
Networking (NDN) with mobility, and flooding schemes at all vehicle densities
and simulation times
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