Vehicular Cloud

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Hussein T. Mouftah - One of the best experts on this subject based on the ideXlab platform.

  • a continuous diversified Vehicular Cloud service availability framework for smart cities
    Computer Networks, 2018
    Co-Authors: Ismaeel Al Ridhawi, Burak Kantarci, Moayad Aloqaily, Yaser Jararweh, Hussein T. Mouftah
    Abstract:

    Abstract The intelligent and connected transportation system (ICTS) is a significant and mandatory component of the smart city architecture. Multimedia content sharing, vehicle power management, and road navigation are all examples of ICTS services. As smart cities continue to deploy different technologies to improve the performance and diversity of Vehicular Cloud services, one of the main issues that prevails is efficient and reliable service discovery and selection for smart vehicles. Furthermore, Cloud service providers (SPs) are limited to the availability, variety and quality of services made available to Vehicular Cloud subscribers. Smart vehicles rely on a number of SPs to acquire the required services while moving. It therefore becomes challenging for Vehicular Cloud subscribers to acquire services that meet their quality of experience (QoE) preferences. This paper introduces a new service provision scheme to provide continuous availability of diversified Cloud services targeting Vehicular Cloud users through a cluster-based trusted third party (TTP) framework. TTPs act as Cloud service mediators between Cloud service subscribers and providers. Vehicles that are considered to have similar patterns of movement and service acquisition characteristics are grouped into service-specific clusters. TTPs communicate with service providers and cluster heads to negotiate for services with high QoE characteristics. A location prediction method is adopted to determine a vehicle's future location and allow services to be negotiated for before the vehicle's arrival. We provide simulation results to show that our approach can adequately discover and deliver Cloud services with increased QoE results, minimal overhead burden and reduced end-to-end latency.

  • multiagent multiobjective interaction game system for service provisioning in Vehicular Cloud
    IEEE Access, 2016
    Co-Authors: Moayad Aloqaily, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    The increasing number of applications based on the Internet of Things, as well as advances in wireless communication, information and communication technology, and mobile Cloud computing, has allowed mobile users to access a wider range of resources when mobile. As the use of Vehicular Cloud computing has become more popular due to its ability to improve driver and vehicle safety, researchers and industry have a growing interest in the design and development of Vehicular networks for emerging applications. Vehicle drivers can now access a variety of on demand resources en route via Vehicular network service providers. The adaptation of Vehicular Cloud services faces many challenges, including cost, privacy, and latency. The contributions of this paper are as follows. First, we propose a game theory-based framework to manage on-demand service provision in a Vehicular Cloud. We present three different game approaches, each of which helps drivers minimize their service costs and latency, and maximize their privacy. Second, we propose a quality-of-experience framework for service provision in a Vehicular Cloud for various types of users, a simple but effective model to determine driver preferences. Third, we propose using the trusted third party concept to represent drivers and service providers, and ensure fair game treatment. We develop and evaluate simulations of the proposed approaches under different network scenarios with respect to privacy, service cost, and latency, by varying the vehicle density and driver preferences. The results show that the proposed approach outperforms conventional models, since the game theory system introduces a bounded latency of ≤3%, achieves service cost savings up to 65%, and preserves driver privacy by reducing revealed information by up to 47%.

  • a generalized framework for quality of experience qoe based provisioning in a Vehicular Cloud
    IEEE International Conference on Ubiquitous Wireless Broadband, 2015
    Co-Authors: Moayad Aloqaily, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    Recently, Vehicular Cloud Computing (VCC) are promising to convey relatively more communication, on-demand and based on pay-as-you-go fashion. Such environment concept's is being widely adopted, which is resulting in several research issues and challenges. Privacy, service cost and provisioning delay are identified as the most crucial challenges to be addressed. This paper extends our previous work [10] and builds a generalized of quality-of-experience (QoE) design. QoE requirements are collected via numerous Vehicular nodes in the Vehicular Cloud and re-formulated by a weighted combination of these factors, i.e., delay, price and information revealed to the Trusted Third Party (TTP). Extensive simulations are run in order to evaluate the performance of our proposed framework. Through simulations, we show that QoE-based service provisioning in a Vehicular Cloud fulfils the service requirements by making a compromise between delay, service cost and information revealed to the TTP.

  • On the impact of quality of experience (QoE) in a Vehicular Cloud with various providers
    2014 11th Annual High Capacity Optical Networks and Emerging Enabling Technologies (Photonics for Energy) HONET-PfE 2014, 2014
    Co-Authors: Moayad Aloqaily, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    With the acceleration of mobile applications, mobile Cloud computing is envisioned to be the best fit solution to make a compromise between users' and service providers' benefits. An extension of mobile Cloud computing, Vehicular Cloud computing, provides another viable solution, by consolidating the benefits of mobile Cloud computing and Vehicular communications. Among several challenges in this environment, privacy, service price and provision delay are the most important. In this paper, we propose a framework to address these challenges in a Vehicular Cloud based on a quality-of-experience (QoE) approach, discuss the drawbacks of existing architectures, and propose and validate a new architecture. This architecture is an extension of a system [1] we proposed in previous work. QoE is obtained via other mobile nodes in the Vehicular Cloud, and re-formulated according to a weighted combination of the three key factors: privacy, price and delay. Privacy is defined as a function of the information revealed to the service provider. We evaluate our proposal via simulations, and based on the numerical results, we show that QoE-based service provisioning in a Vehicular Cloud improves upon a nai�ve service provision approach, as well as other approaches that address only one of the factors.

  • Dynamic Virtual Machine Migration in a Vehicular Cloud
    2014 IEEE Symposium on Computers and Communications (ISCC), 2014
    Co-Authors: Tarek K. Refaat, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    Vehicular Clouds are formed by incorporating Cloud-based services into Vehicular ad hoc networks. Amongst the several challenges in a Vehicular Cloud network, virtual machine migration (VMM) may be one of the most crucial issues that need addressing. In this paper, a novel solution for VMM in a Vehicular Cloud is presented. The Vehicular Cloud is modeled as a small corporate data center with mobile hosts, equipped with limited computational and storage capacities. The proposed scheme is called Vehicular Virtual Machine Migration (VVMM). The VVMM aims to achieve efficient handling of frequent changes in the data center topology, host heterogeneity, all while doing so with minimum Roadside Unit (RU) intervention. Three modes of VVMM are studied. The first mode, VVMM-U uniformly selects the destinations for VM migrations, which will take place shortly prior to a vehicle's departure from the coverage of the RU. The second mode, VVMM-LW aims at migrating the VM to the vehicle with the least workload, and the third mode, VVMM-MA incorporates mobility awareness by migrating the VM to the vehicle with the least workload and forecasted to be within the geographic boundaries of the Vehicular Cloud. We evaluate the performance of our proposed framework through simulations. Simulation results show that VVMM-MA introduces significant reduction in unsuccessful migration attempts and results in an increased fairness in vehicle capacity utilization across the Vehicular Cloud system.

Azzedine Boukerche - One of the best experts on this subject based on the ideXlab platform.

  • avarac an availability based resource allocation scheme for Vehicular Cloud
    IEEE Transactions on Intelligent Transportation Systems, 2019
    Co-Authors: Rodolfo I Meneguette, Azzedine Boukerche, Adinovam H M Pimenta
    Abstract:

    Intelligent transportation systems (ITSs) are comprised of multiple technologies that are applied to improve the quality of transport, offering services and applications that will monitor, manage the transportation systems, and increase the level of comfort and safety for passengers and drivers. ITSs services are available for Vehicular users through the infrastructure, based on the Vehicular network. Furthermore, they can use a Vehicular Cloud to take advantage of all the resources that a Cloud can provide. To achieve this, the ITSs require a mechanism that will aggregate and manage all the available resources provided by the vehicles. Moreover, the aggregation and allocation resource schemes must address the characteristics of the Vehicular network to attempt all the quality of service requirements. Therefore, one of the greatest challenges lies in managing the allocation and aggregation of vehicle resources when there is no external infrastructure that will support the system. Hence, we propose an aggregate and allocate resource approach to maximize the availability of service. For this, we formulate the problem through the semi-Markov decision process (SMDP) that will provide an optimal solution for the aggregation and allocation problem. Moreover, we use an average reward function and iterative algorithm to solve the SMDP. The results show that the proposed approach showed stable behavior regardless of the frequency of receiving requests for service. Furthermore, the proposed solution has high average reward when compared to other work in the paper.

  • Vehicular Cloud computing architectures applications and mobility
    Computer Networks, 2018
    Co-Authors: Azzedine Boukerche, Robson Eduardo De Grande
    Abstract:

    Abstract Intelligent transportation systems are designed to provide innovative applications and services relating to traffic management, as well as to facilitate the access to information for other systems and users. The compelling motivation for employing underutilized onboard resources for transportation systems and the advancements in management technology for Cloud computing resources has promoted the concept of Vehicular Clouds. This work gathers and describes the most recent approaches and solutions for Vehicular Clouds, featuring applications, services, and traffic models that can enable Vehicular Cloud in a more dynamic environment. We have considered a large number of applications and services that showed relevance in the scope of the transportation system, benefiting its management, drivers, passengers, and pedestrians. Nevertheless, the high traffic mobility imposes as a significant challenge in implementing a Vehicular Cloud on continually changing physical resources. The dynamics of the environment bring fundamental issues and increase the complexity of building this new type of Cloud. By analyzing the existing traffic models, we found that Vehicular Cloud computing is technologically feasible not just in the static environment, like a parking lot or garage where vehicles are stationary, but also the dynamic scenarios, such as highways or streets where vehicles move.

  • Vehicular Cloud network a new challenge for resource management based systems
    International Conference on Wireless Communications and Mobile Computing, 2017
    Co-Authors: Azzedine Boukerche, Rodolfo I Meneguette
    Abstract:

    Vehicular Cloud is defined as a set of vehicles that share their computation resource in a Cloud, these resources are scheduled on demand based on cooperation between vehicles and vehicles with the roadside. These Clouds can adapt dynamically according to application quality of service requirements. Thus, resource management is very crucial for this kind of Cloud. In this work, we address relevant issues about of the concepts related to the resource management in the Vehicular Cloud; and techniques that require consideration are discussed in the context of resource management for the Vehicular Cloud. Finally, we discuss challenges and issues for potential future work.

  • Peer-to-Peer Protocol for Allocated Resources in Vehicular Cloud Based on V2V Communication
    2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017
    Co-Authors: Rodolfo Ipolito Meneguette, Azzedine Boukerche
    Abstract:

    Intelligent transport systems (ITS) may take advantage of the mobile Cloud, in other words, the Vehicular Cloud may provide a lot of services for assisting traffic, accident prevention, and content delivery, among others. However, search and allocation resources in the Vehicular Cloud has become challenging, due to Vehicular network characteristics, and also to the necessity of attempting the QoS requirements of service independently of the external condition. Thus, one of the biggest obstacles in these environments is to allocate and share resources available in vehicles without the need for external infrastructure. With this challenge in mind, we propose a new protocol designed to facilitate resource sharing via mobile Cloud in the Vehicular network. Simulation results show that the proposed approach introduces a short search time of approximately 0.7 (ms) to query resources in one hop, and about 1.0 (ms) to seek resources in more than one hop. Furthermore, the proposed protocol enables a high availability of resources, about 95%.

  • SERVitES: An efficient search and allocation resource protocol based on V2V communication for Vehicular Cloud
    Computer Networks, 2017
    Co-Authors: Rodolfo Ipolito Meneguette, Azzedine Boukerche
    Abstract:

    Intelligent Transportation Systems (ITS) aim to streamline the operation of vehicles and manage vehicle traffic, while other information ITS can strengthen Cloud computing by storing and processing the collected information. Resource management is a particularly challenging issue for Vehicular Cloud development. In this paper, we propose a protocol to assist in the search and management of resources in a Vehicular Cloud without depending on the support of roadside infrastructure. Thus, vehicles are expected to organize themselves and establish collaborations to manage and share their resources. Simulation results show that, in comparison to other works, the proposed protocol achieved an increase in the average cluster head duration of around 18%, an increase of 13% of member vehicles, a decrease of 3% of cluster head changes, and a reduced amount of clusters by around 11%. The proposed protocol also achieved a higher availability of resources, by about 96%, and a lower time for search and allocation (around 0.5 (ms) to search 1 hop, and 1(ms) to search 3 or 2 hops).

Mohsen Guizani - One of the best experts on this subject based on the ideXlab platform.

  • svcc hsr providing secure Vehicular Cloud computing for intelligent high speed rail
    IEEE Network, 2018
    Co-Authors: Ping Dong, Tao Zheng, Hongke Zhang, Mohsen Guizani
    Abstract:

    VCC can bring many benefits to intelligent transportation systems. Meanwhile, HSR, an increasingly efficient means of transportation, faces several challenges in terms of high-frequency handover at speeds over 300 km/h. This includes large volumes of data of different types and different degrees of importance. Therefore, a secure and comprehensive Cloud computing solution is attractive to improve the safety and efficiency of intelligent HSR. In this article, we present a novel and practical SVCC-HSR based on our long-term research and practice in this field. SVCC-HSR not only considers the various technical features of Vehicular Cloud computing, but also addresses several special demands in the HSR context. We perform extensive experiments using various scenarios, including frequent handover scenarios in high-speed trains running at 300 km/h with large-volume data transmission scenarios in locomotive depots. The real-world experimental results demonstrate that SVCC-HSR achieves better performance in fast authentication, hierarchical attribute-based data encryption, and transmission efficiency compared to its counterparts.

  • reinforcement learning for resource provisioning in Vehicular Cloud
    arXiv: Networking and Internet Architecture, 2018
    Co-Authors: Mohammad Ali Salahuddin, Ala Alfuqaha, Mohsen Guizani
    Abstract:

    This article presents a concise view of Vehicular Clouds that incorporates various Vehicular Cloud models, which have been proposed, to date. Essentially, they all extend the traditional Cloud and its utility computing functionalities across the entities in the Vehicular ad hoc network (VANET). These entities include fixed road-side units (RSUs), on-board units (OBUs) embedded in the vehicle and personal smart devices of the driver and passengers. Cumulatively, these entities yield abundant processing, storage, sensing and communication resources. However, Vehicular Clouds require novel resource provisioning techniques, which can address the intrinsic challenges of (i) dynamic demands for the resources and (ii) stringent QoS requirements. In this article, we show the benefits of reinforcement learning based techniques for resource provisioning in the Vehicular Cloud. The learning techniques can perceive long term benefits and are ideal for minimizing the overhead of resource provisioning for Vehicular Clouds.

  • an efficient anonymous authentication scheme for internet of vehicles
    International Conference on Communications, 2018
    Co-Authors: Jingwei Liu, Rong Sun, Mohsen Guizani
    Abstract:

    Internet of Vehicles (IoV) is an intelligent application of IoT in smart transportation, which can make intelligent decisions for passengers. It has drawn extensive attention to improve traffic safety and efficiency and create a more comfortable driving and riding environment. Vehicular Cloud computing is a variant of mobile Cloud computing, which can process local information quickly. The cooperation of the Internet and Vehicular Cloud can make the communication more efficient in IoV. In this paper, we mainly focus on the secure communication between vehicles and roadside units. We first propose a new certificateless short signature scheme (CLSS) and prove the unforgeability of it in random oracle model. Then, by combining CLSS and a regional management strategy we design an efficient anonymous mutual quick authentication scheme for IoV. Additionally, the quantitative performance analysis shows that the proposed scheme achieves higher efficiency in terms of interaction between vehicles and roadside units compared with other existing schemes.

  • reinforcement learning for resource provisioning in the Vehicular Cloud
    IEEE Wireless Communications, 2016
    Co-Authors: Mohammad Ali Salahuddin, Ala Alfuqaha, Mohsen Guizani
    Abstract:

    This article presents a concise view of Vehicular Clouds that incorporates various Vehicular Cloud models that have been proposed to date. Essentially, they all extend the traditional Cloud and its utility computing functionalities across the entities in the Vehicular ad hoc network. These entities include fixed roadside units, onboard units embedded in the vehicle, and personal smart devices of drivers and passengers. Cumulatively, these entities yield abundant processing, storage, sensing, and communication resources. However, Vehicular Clouds require novel resource provisioning techniques that can address the intrinsic challenges of dynamic demands for the resources and stringent QoS requirements. In this article, we show the benefits of reinforcement-learning-based techniques for resource provisioning in the Vehicular Cloud. The learning techniques can perceive long-term benefits and are ideal for minimizing the overhead of resource provisioning for Vehicular Clouds.

Burak Kantarci - One of the best experts on this subject based on the ideXlab platform.

  • a continuous diversified Vehicular Cloud service availability framework for smart cities
    Computer Networks, 2018
    Co-Authors: Ismaeel Al Ridhawi, Burak Kantarci, Moayad Aloqaily, Yaser Jararweh, Hussein T. Mouftah
    Abstract:

    Abstract The intelligent and connected transportation system (ICTS) is a significant and mandatory component of the smart city architecture. Multimedia content sharing, vehicle power management, and road navigation are all examples of ICTS services. As smart cities continue to deploy different technologies to improve the performance and diversity of Vehicular Cloud services, one of the main issues that prevails is efficient and reliable service discovery and selection for smart vehicles. Furthermore, Cloud service providers (SPs) are limited to the availability, variety and quality of services made available to Vehicular Cloud subscribers. Smart vehicles rely on a number of SPs to acquire the required services while moving. It therefore becomes challenging for Vehicular Cloud subscribers to acquire services that meet their quality of experience (QoE) preferences. This paper introduces a new service provision scheme to provide continuous availability of diversified Cloud services targeting Vehicular Cloud users through a cluster-based trusted third party (TTP) framework. TTPs act as Cloud service mediators between Cloud service subscribers and providers. Vehicles that are considered to have similar patterns of movement and service acquisition characteristics are grouped into service-specific clusters. TTPs communicate with service providers and cluster heads to negotiate for services with high QoE characteristics. A location prediction method is adopted to determine a vehicle's future location and allow services to be negotiated for before the vehicle's arrival. We provide simulation results to show that our approach can adequately discover and deliver Cloud services with increased QoE results, minimal overhead burden and reduced end-to-end latency.

  • multiagent multiobjective interaction game system for service provisioning in Vehicular Cloud
    IEEE Access, 2016
    Co-Authors: Moayad Aloqaily, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    The increasing number of applications based on the Internet of Things, as well as advances in wireless communication, information and communication technology, and mobile Cloud computing, has allowed mobile users to access a wider range of resources when mobile. As the use of Vehicular Cloud computing has become more popular due to its ability to improve driver and vehicle safety, researchers and industry have a growing interest in the design and development of Vehicular networks for emerging applications. Vehicle drivers can now access a variety of on demand resources en route via Vehicular network service providers. The adaptation of Vehicular Cloud services faces many challenges, including cost, privacy, and latency. The contributions of this paper are as follows. First, we propose a game theory-based framework to manage on-demand service provision in a Vehicular Cloud. We present three different game approaches, each of which helps drivers minimize their service costs and latency, and maximize their privacy. Second, we propose a quality-of-experience framework for service provision in a Vehicular Cloud for various types of users, a simple but effective model to determine driver preferences. Third, we propose using the trusted third party concept to represent drivers and service providers, and ensure fair game treatment. We develop and evaluate simulations of the proposed approaches under different network scenarios with respect to privacy, service cost, and latency, by varying the vehicle density and driver preferences. The results show that the proposed approach outperforms conventional models, since the game theory system introduces a bounded latency of ≤3%, achieves service cost savings up to 65%, and preserves driver privacy by reducing revealed information by up to 47%.

  • a generalized framework for quality of experience qoe based provisioning in a Vehicular Cloud
    IEEE International Conference on Ubiquitous Wireless Broadband, 2015
    Co-Authors: Moayad Aloqaily, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    Recently, Vehicular Cloud Computing (VCC) are promising to convey relatively more communication, on-demand and based on pay-as-you-go fashion. Such environment concept's is being widely adopted, which is resulting in several research issues and challenges. Privacy, service cost and provisioning delay are identified as the most crucial challenges to be addressed. This paper extends our previous work [10] and builds a generalized of quality-of-experience (QoE) design. QoE requirements are collected via numerous Vehicular nodes in the Vehicular Cloud and re-formulated by a weighted combination of these factors, i.e., delay, price and information revealed to the Trusted Third Party (TTP). Extensive simulations are run in order to evaluate the performance of our proposed framework. Through simulations, we show that QoE-based service provisioning in a Vehicular Cloud fulfils the service requirements by making a compromise between delay, service cost and information revealed to the TTP.

  • On the impact of quality of experience (QoE) in a Vehicular Cloud with various providers
    2014 11th Annual High Capacity Optical Networks and Emerging Enabling Technologies (Photonics for Energy) HONET-PfE 2014, 2014
    Co-Authors: Moayad Aloqaily, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    With the acceleration of mobile applications, mobile Cloud computing is envisioned to be the best fit solution to make a compromise between users' and service providers' benefits. An extension of mobile Cloud computing, Vehicular Cloud computing, provides another viable solution, by consolidating the benefits of mobile Cloud computing and Vehicular communications. Among several challenges in this environment, privacy, service price and provision delay are the most important. In this paper, we propose a framework to address these challenges in a Vehicular Cloud based on a quality-of-experience (QoE) approach, discuss the drawbacks of existing architectures, and propose and validate a new architecture. This architecture is an extension of a system [1] we proposed in previous work. QoE is obtained via other mobile nodes in the Vehicular Cloud, and re-formulated according to a weighted combination of the three key factors: privacy, price and delay. Privacy is defined as a function of the information revealed to the service provider. We evaluate our proposal via simulations, and based on the numerical results, we show that QoE-based service provisioning in a Vehicular Cloud improves upon a nai�ve service provision approach, as well as other approaches that address only one of the factors.

  • Dynamic Virtual Machine Migration in a Vehicular Cloud
    2014 IEEE Symposium on Computers and Communications (ISCC), 2014
    Co-Authors: Tarek K. Refaat, Burak Kantarci, Hussein T. Mouftah
    Abstract:

    Vehicular Clouds are formed by incorporating Cloud-based services into Vehicular ad hoc networks. Amongst the several challenges in a Vehicular Cloud network, virtual machine migration (VMM) may be one of the most crucial issues that need addressing. In this paper, a novel solution for VMM in a Vehicular Cloud is presented. The Vehicular Cloud is modeled as a small corporate data center with mobile hosts, equipped with limited computational and storage capacities. The proposed scheme is called Vehicular Virtual Machine Migration (VVMM). The VVMM aims to achieve efficient handling of frequent changes in the data center topology, host heterogeneity, all while doing so with minimum Roadside Unit (RU) intervention. Three modes of VVMM are studied. The first mode, VVMM-U uniformly selects the destinations for VM migrations, which will take place shortly prior to a vehicle's departure from the coverage of the RU. The second mode, VVMM-LW aims at migrating the VM to the vehicle with the least workload, and the third mode, VVMM-MA incorporates mobility awareness by migrating the VM to the vehicle with the least workload and forecasted to be within the geographic boundaries of the Vehicular Cloud. We evaluate the performance of our proposed framework through simulations. Simulation results show that VVMM-MA introduces significant reduction in unsuccessful migration attempts and results in an increased fairness in vehicle capacity utilization across the Vehicular Cloud system.

Mario Gerla - One of the best experts on this subject based on the ideXlab platform.

  • Vehicular Cloud networking architecture and design principles
    IEEE Communications Magazine, 2014
    Co-Authors: Euisin Lee, Eun-kyu Lee, Mario Gerla
    Abstract:

    Over the past several decades, VANET has been a core networking technology to provide safety and comfort to drivers in Vehicular environments. Emerging applications and services, however, require major changes to its underlying computing and networking models, which demand new network planning for VANET. This article especially examines how VANET evolves with two emerging paradigms: Vehicular Cloud computing and information-centric networking. VCC brings the mobile Cloud model to Vehicular networks and thus changes the way of network service provisioning, whereas ICN changes the notion of data routing and dissemination. We envision a new Vehicular networking system, Vehicular Cloud networking, on top of them. This article scrutinizes its architecture and operations, and discusses its design principles.

  • Internet of vehicles: From intelligent grid to autonomous cars and Vehicular Clouds
    2014 IEEE World Forum on Internet of Things WF-IoT 2014, 2014
    Co-Authors: Mario Gerla, Eun-kyu Lee, Grégoire Pau, Uichin Lee
    Abstract:

    Traditionally, the vehicle has been the extension of the man's ambulatory system, docile to the driver's commands. Recent advances in communications, controls and embedded systems have changed this model, paving the way to the Intelligent Vehicle Grid. The car is now a formidable sensor platform, absorbing information from the environment (and from other cars) and feeding it to drivers and infrastructure to assist in safe navigation, pollution control and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Pioneered by the Google car, the Internet of Vehicles will be a distributed transport fabric capable to make its own decisions about driving customers to their destinations. Like other important instantiations of the Internet of Things (e.g., the smart building), the Internet of Vehicles will have communications, storage, intelligence, and learning capabilities to anticipate the customers' intentions. The concept that will help transition to the Internet of Vehicles is the Vehicular Cloud, the equivalent of Internet Cloud for vehicles, providing all the services required by the autonomous vehicles. In this article, we discuss the evolution from Intelligent Vehicle Grid to Autonomous, Internet-connected Vehicles, and Vehicular Cloud.

  • Cognitive radios and the Vehicular Cloud
    1st ACM Workshop on Cognitive Radio Architectures for Broadband CRAB 2013, 2013
    Co-Authors: Mario Gerla
    Abstract:

    Cognitive Radios can sense the radio environment and can dynamically reconfigure their parameters to best support the user needs. This "intelligence" has been made possible in part by recent advances in Software Defined Radios. An important motivation for using Cognitive Radios has been mobility. Mobile Cognitive Radios can dynamically adjust to new environments and mission needs. An example is the multibillion dollar JTRS (Joint Tactical Radio System) project. Recently, Cognitive Radios have been engaged in making efficient use of the scarce spectrum, for example, exploiting White Spectrum and opportunistically sharing allocated but underutilized spectrum (Dynamic Spectrum Sharing). The crowded spectrum is a critical problem in urban environment and effects the deployment of new Vehicular Applications. In this talk we briefly review the evolution of cognitive radios in commercial environments. We then propose the aggressive use of Cognitive Radio technologies to allow vehicles to open "radio trails" in the urban grid and advocate the development of a "cognitive spectrum service" for the Vehicular Cloud.

  • Pics-on-wheels: Photo surveillance in the Vehicular Cloud
    2013 International Conference on Computing Networking and Communications ICNC 2013, 2013
    Co-Authors: Mario Gerla, Jui Ting Weng, Grégoire Pau
    Abstract:

    Cloud computing allows user to access remote hardware, data and software through the network. However, many of these resources today are found on mobiles. For example, modern vehicles provide powerful platforms for computation, data delivery, storage, and sensing. This paper introduces the notion of Mobile Cloud computing to tap mobile resources. As an example, we describe the Pies-on-Wheels service, a Vehicular Cloud service that delivers images on demand to citizens by using vehicles' on board cameras. A server (eg taxi dispatcher or Navigator Server) accepts requests from members and assigns the photo clicking task to vehicles close to the target. The feasibility of the Pies-on-Wheels service is demonstrated in a San Francisco scenario using published taxicab routes.

  • Vehicular Cloud computing
    2012 the 11th Annual Mediterranean Ad Hoc Networking Workshop Med-Hoc-Net 2012, 2012
    Co-Authors: Mario Gerla
    Abstract:

    Mobile Cloud Computing is a new field of research that aims to study mobile agents (people, vehicles, robots) as they interact and collaborate to sense the environment, process the data, propagate the results and more generally share resources. Mobile agents collectively operate as Mobile Clouds that enable environment modeling, content discovery, data collection and dissemination and other mobile applications in a way not possible, or not efficient, with conventional Internet Cloud models and mobile computing approaches. In this paper, we discuss design principles and research issues in mobile Cloud computing. We then focus on the Mobile Vehicular Cloud and review Cloud applications ranging from urban sensing to intelligent transportation.