Collaborative Vehicular Edge Computing Networks: Architecture Design and Research Challenges

The emergence of augmented reality (AR), autonomous driving and other new applications have greatly enriched the functionality of the vehicular networks. However, these applications usually require complex calculations and large amounts of storage, which puts tremendous pressure on traditional vehicular networks. Mobile edge computing (MEC) is proposed as a prospective technique to extend computing and storage resources to the edge of the network. Combined with MEC, the computing and storage capabilities of the vehicular network can be further enhanced. Therefore, in this paper, we explore the novel collaborative vehicular edge computing network (CVECN) architecture. We first review the work related to MEC and vehicular networks. Then we discuss the design principles of CVECN. Based on the principles, we present the detailed CVECN architecture, and introduce the corresponding functional modules, communication process, as well as the installation and deployment ideas. Furthermore, the promising technical challenges, including collaborative coalition formation, collaborative task offloading and mobility management, are presented. And some potential research issues for future research are highlighted. Finally, simulation results are verified that the proposed CVECN can significantly improve network performance

Resource allocation and user association for HTTP adaptive streaming in heterogeneous cellular networks with small cells

Video streaming, especially hypertext transfer protocol based (HTTP) adaptive streaming (HAS) of video, has been expected to be a dominant application over mobile networks in the near future, which brings huge challenge for the mobile networks. Although some works have been done for video streaming delivery in heterogeneous cellular networks, most of them focus on the video streaming scheduling or the caching strategy design. The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users is largely ignored. In this paper, the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied, we model the optimization problem as a mixed integer programming problem. And to reduce the computational complexity, an optimal rate allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved. Then we use the many-to-one matching model to analyze the user association problem, and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed. Finally, extensive simulation results are illustrated to demonstrate the performance of the proposed scheme

Service-aware optimal caching placement for named data networking

Built-in caching in Named Data Networking (NDN) promises to provide efficient content delivery, where the dedicated on-path caching scheme is deployed to serve users' requests on the forwarding path. In this work, to utilize limited caching resources to achieve optimal performance, the caching placement decision is made by jointly considering the content popularity, underlying network topology, forwarding strategy and caching service mechanism in NDN. More specifically, we propose a service-aware caching model. In the model, we first define the Cache Service Matrix (CSM), which describes the position where each user's request is served for each piece of content. In order to make CSM compl

A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges

In recent years, with the rapid development of current Internet and mobile communication technologies, the infrastructure, devices and resources in networking systems are becoming more complex and heterogeneous. In order to efficiently organize, manage, maintain and optimize networking systems, more intelligence needs to be deployed. However, due to the inherently distributed feature of traditional networks, machine learning techniques are ha

Service-aware optimal caching placement for named data networking

Built-in caching in Named Data Networking (NDN) promises to provide efficient content delivery, where the dedicated on-path caching scheme is deployed to serve users’ requests on the forwarding path. In this work, in order to utilize limited caching resources to achieve optimal performance, the caching placement decis

Joint Resource Allocation for Software-Defined Networking, Caching, and Computing

Although some excellent works have been done on networking, caching, and computing, these three important areas have traditionally been addressed separately in the literature. In this paper, we describe the recent advances in jointing networking, caching, and computing and present a novel integrated framework: software-defined networking, caching, and computing (SD-NCC). SD-NCC enables dynamic orchestration of networking

Joint resource allocation for software defined networking, caching and computing

Recently, there are significant advances in the areas of networking, caching and computing. Nevertheless, these three important areas have traditionally been addressed separately in the existing research. In this paper, we present a novel framework that integrates networking, caching and computing in a systematic way and enables dynamic orchestration of these three resources to improve the end-to-end system performance and meet the requirements of different applications. Then, we consider the bandwidth, caching and computing resource allocation issue and formulate it as a joint caching/computing strategy and servers selection problem to minimize the combination cost of network usage and energy consumption in the framework. To minimize the combination cost of network usage and energy consumption in the framework, we formulate it as a joint caching/computing strategy and servers selection problem. In addition, we solve the joint caching/computing strategy and servers selection problem using an exhaustive-search algorithm. Simulation results show that our proposed framework significantly outperforms the traditional network without in-network caching/computing in terms of network usage and energy consumption

Software Defined Networking, Caching, and Computing for Green Wireless Networks

Recent advances in networking, caching, and computing will have a profound impact on the development of next generation green wireless networks. Nevertheless, these three important areas have traditionally been addressed separately in existing works. In this article, we propose a novel framework that jointly considers networking, caching, and computing techniques in a systematic way to naturally support energy-efficient information retrieval and computing services in green wireless networks. This integrated framework can enable dynamic orchestration of different resources to meet the requirements of next generation green wireless networks. Simulation results are presented to show the effectiveness of the proposed framework. In addition, we discuss a number of challenges in implementing the proposed framework in next generation green wireless networks

Green Symbiotic Cloud Communications

Cloud computing, a TCP/IP based development, is essentially an integration of computer technologies such as HPC, massive memory resource handling, high-speed networks and reliable system architecture. A unified definition of cloud computing doesn’t exist with researchers and industrialists globally having listed up to 22 definitions to provide a comprehensive analysis of all the characteristics of Cloud Computing. However Cloud Computing mainly entails as a service that is outsourced, and does not symbolically represent a cloud as we observe in Nature. Classified exhaustively, clouds fit into the following categories—public, private, community and hybrid—however, without much exclusivity. This chapter views the emblem of cloud computing from a different perspective by emulating the geographical cloud as it appears in nature with properties of abstraction and virtualization. The chapter further introduces a first of its kind concept of Cloud Communications. To the best of our knowledge this is an archetype approach of incorporating the communications infrastructure into the cloud. The chapter proposes a Green Symbiotic Cloud (GSC) paradigm, which is an amalgamation of all sorts of clouds, with the elimination/minimization of reliance on data-centers, agent-based cooperative approaches and self-managed platforms inherent to systems of the future. Backed by concepts of abstraction and virtualized infrastructure and shared resource pools in one’s own local area network, the proposed paradigm offers impetus to revolutionize cloud computing. Taking virtualization to an entirely new level by offering a more local, energy-efficient, synergistic system comprised of individual agents sharing not just resources but knowledge/intelligence in the cloud, it basically emulates the cloud as it appears in nature