Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey (original) (raw)
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Journal of Network and Computer Applications, 2013
Vehicular networking has become a significant research area due to its specific features and applications such as standardization, efficient traffic management, road safety and infotainment. Vehicles are expected to carry relatively more communication systems, on board computing facilities, storage and increased sensing power. Hence, several technologies have been deployed to maintain and promote Intelligent Transportation Systems (ITS). Recently, a number of solutions were proposed to address the challenges and issues of vehicular networks. Vehicular Cloud Computing (VCC) is one of the solutions. VCC is a new hybrid technology that has a remarkable impact on traffic management and road safety by instantly using vehicular resources, such as computing, storage and internet for decision making. This paper presents the state-of-theart survey of vehicular cloud computing. Moreover, we present a taxonomy for vehicular cloud in which special attention has been devoted to the extensive applications, cloud formations, key management, inter cloud communication systems, and broad aspects of privacy and security issues. Through an extensive review of the literature, we design an architecture for VCC, itemize the properties required in vehicular cloud that support this model. We compare this mechanism with normal Cloud Computing (CC) and discuss open research issues and future directions. By reviewing and analyzing literature, we found that VCC is a technologically feasible and economically viable technological shifting paradigm for converging intelligent vehicular networks towards autonomous traffic, vehicle control and perception systems. Systems (ITS) (Al-Sultan et al. , 2013, Hartenstein and. The promise of vehicular networking has led to a fast convergence with ITS and to the advent of Intelligent Vehicular Networks , which are anticipated to transform driving styles by creating a secure, safe and healthy environment that will ultimately encompass our busy city streets and highways. Thus, the intelligent vehicular networks will provide infotainment and will enable a new versatile system that enhances transportation efficiency and safety . Although many efforts have been made to reach these objectives, VANET has several drawbacks, such as the high cost of the service constrained communications due to the high mobility of the vehicle .
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Recently vehicular Ad hoc Networks (VANET) has attracted the attention of research communities, leading car manufactures and governments due to its potential applications and specific characteristics. Their research outcome was started with awareness between vehicles for collision avoidance to internet access and then expanded to vehicular multimedia communications. Moreover, vehicle's high computation, communication and storage resources are set a ground for vehicular networks to deploy these applications in the near future. Nevertheless, onboard resources in vehicles are mostly underutilized. Vehicular Cloud Computing (VCC) is developed to utilize the VANET resources efficiently and hence provide subscribers safe and infotainment services. In this article, we perform a survey of state-of-the-art vehicular cloud computing as well as the existing techniques that utilizes cloud computing for performance improvements in VANET. We then classified the VCC based on the applications, services types and vehicular cloud organization. We present the detail for each VCC application and formation. Lastly, we discussed the open issues and research directions related to VANET cloud computing.
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During the last decade, Vehicular Ad-hoc Network (VANET) research area has been a prime focus for the researchers and developers owing to its important applications, including efficient traffic management, road safety, and entertainment. Vehicles are increasingly equipped with extensive resources in terms of computing power, data storage, and sensing capabilities and these resources are typically underutilized, due to the constrained service and resource management models. With the emergence of highly developed vehicular applications, the issues such as low latency, security, quality of service and uninterrupted services have also been increasing which demands for the powerful communication and computation facilities. To satisfy the requirements of VANETs, Vehicular Cloud Computing (VCC) has come up as a solution. The research community needs to take these issues into consideration and they should be solved for the continuance of the development in this area. Vehicular Cloud Computi...
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IEEE Access, 2019
The emergence of computation-intensive and delay-sensitive vehicular applications poses a great challenge for individual vehicles with limited computation resources. Mobile edge computing (MEC) is a new paradigm shift that can enhance vehicular services through computation offloading. However, the high mobility of vehicles will affect offloading performance. In this paper, we investigate the vehicular user (VU) computation overhead minimization problem in MEC-enabled vehicular networks by jointly optimizing the computation and communication resources' allocation (transmit power and uploading time for communication, and the offloading ratio and local CPU frequency for computation). This optimization problem is nonconvex and difficult to solve directly. To deal with this issue, we first transform the original problem into an equivalent one. Then, we decompose the equivalent problem into a two-level problem. In addition, we develop a low-complexity algorithm to obtain the optimal solution. The numerical results demonstrate that the proposed algorithm can significantly outperform benchmark algorithms in terms of computation overhead. INDEX TERMS Mobile edge computing, vehicular networks, computation offloading, resource allocation.
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A new networking paradigm, Vehicular Edge Computing (VEC), has been introduced in recent years to the vehicular network to augment its computing capacity. The ultimate challenge to fulfill the requirements of both communication and computation is increasingly prominent, with the advent of ever-growing modern vehicular applications. With the breakthrough of VEC, service providers directly host services in close proximity to smart vehicles for reducing latency and improving quality of service (QoS). This paper illustrates the VEC architecture, coupled with the concept of the smart vehicle, its services, communication, and applications. Moreover, we categorized all the technical issues in the VEC architecture and reviewed all the relevant and latest solutions. We also shed some light and pinpoint future research challenges. This article not only enables naive readers to get a better understanding of this latest research field but also gives new directions in the field of VEC to the oth...
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Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular applications and high mobility scenarios, cost-efficient task offloading in the vehicular environment is still a challenging problem. In this paper, we study the partial task offloading problem in vehicular edge computing in an urban scenario. Where the vehicle computes some part of a task locally, and offload the remaining task to a nearby vehicle and to VEC server subject to the maximum tolerable delay and vehicle’s stay time. To make it cost-efficient, including the cost of the required communication and computing resources, we consider to fully exploit the vehicular available resources. We estimate the transmission rates for the vehicle to vehicle and vehicle to infrastructure communication based on practical assumptions. Moreover, we present a mobility-aware partial task offloading algorithm, taking into acco...
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With the development of electrification, automation, and interconnection of the automobile industry, the demand for vehicular computing has entered an explosive growth era. Massive low time-constrained and computation-intensive vehicular computing operations bring new challenges to vehicles, such as excessive computing power and energy consumption. Computation offloading technology provides a sustainable and low-cost solution to these problems. In this article, we study an adaptive wireless resource allocation strategy of computation offloading service under a three-layered vehicular edge cloud computing framework. We model the computation offloading process at the minimum assignable wireless resource block level, which can better adapt to vehicular computation offloading scenarios and can also rapidly evolve to the 5G network. Subsequently, we propose a method to measure the cost-effectiveness of allocated resources and energy savings, named value density function. Interestingly, with respect to the amount of allocation resource, it can obtain the maximum value density when offloading energy consumption equals to half of local energy consumption. Finally, we propose a low-complexity heuristic resource allocation algorithm based on this novel theoretical discovery. Numerical results corroborate that our designed algorithm can gain above 80% execution time conservation and 62% conservation on energy consumption, and it exhibits fast convergence and superior performance compared to benchmark solutions.
Mobile Edge Computing versus Fog Computing in Internet of Vehicles
The Tenth International Conference on Advances in Future Internet AFIN 2018, 2018
Vehicular networks and the recent Internet of Vehicles (IoV) are continuously developing, aiming to solve the current and novel challenging needs in the domain of transportation systems. Edge computing offers a natural support for Internet of Vehicles, supporting fast response, context awareness, and minimization of the data transfer to the centralized data centers-all these being allowed by the edge computing availability close to mobile vehicles. Multi-access (Mobile) Edge Computing, fog computing, cloudlets, etc., are such candidates to support IoV; their architectures and technologies have overlapping characteristics but also differences in approach. A full convergence between them has not yet been achieved. Also, it is still not completely clarified which solution could be the best trade-off to be adopted in the Internet of vehicles context and for which use cases. This paper is not a complete survey, but attempts a preliminary evaluation of some of the currently proposed Mobile Edge Computing and fog computing solutions for vehicular networks.
CODE-V: Multi-hop computation offloading in Vehicular Fog Computing
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Information-Centric Mobile Edge Computing for Connected Vehicle Environments
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Connected vehicle systems form the basis for future features of functions and applications within the automotive domain. In order to allow resource intensive services, cloud offloading and especially Mobile Edge Computing is a promising approach. In this paper, we present a detailed futuristic vehicular scenario-Electronic Horizon-and list the challenges. We argue that the resulting challenges are representative of many of the envisioned use-cases of Mobile Edge Computing. We then present how Information-Centric Networking in combination with Mobile Edge Computing has the potential to support such a futuristic scenario. Finally, we present research directions that could enhance the solution space.