Video Caching, Analytics and Delivery at the Wireless Edge: A Survey and Future Directions

Future wireless networks will provide high bandwidth, low-latency, and ultra-reliable Internet connectivity to meet the requirements of different applications, ranging from mobile broadband to the Internet of Things. To this aim, mobile edge caching, computing, and communication (edge-C3) have emerged to bring network resources (i.e., bandwidth, storage, and computing) closer to end users. Edge-C3 allows improving the network resource utilization as well as the quality of experience (QoE) of end users. Recently, several video-oriented mobile applications (e.g., live content sharing, gaming, and augmented reality) have leveraged edge-C3 in diverse scenarios involving video streaming in both the downlink and the uplink. Hence, a large number of recent works have studied the implications of video analysis and streaming through edge-C3. This article presents an in-depth survey on video edge-C3 challenges and state-of-the-art solutions in next-generation wireless and mobile networks. Specifically, it includes: a tutorial on video streaming in mobile networks (e.g., video encoding and adaptive bitrate streaming); an overview of mobile network architectures, enabling technologies, and applications for video edge-C3; video edge computing and analytics in uplink scenarios (e.g., architectures, analytics, and applications); and video edge caching, computing and communication methods in downlink scenarios (e.g., collaborative, popularity-based, and context-aware). A new taxonomy for video edge-C3 is proposed and the major contributions of recent studies are first highlighted and then systematically compared. Finally, several open problems and key challenges for future research are outlined

A Survey on Mobile Edge Computing for Video Streaming : Opportunities and Challenges

5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowd-sourced video streaming, cloud gaming, virtual and augmented reality) are becoming more ambitious with high volume and low latency video streams putting strict demands on the already congested networks. Mobile Edge Computing (MEC) is an emerging paradigm that extends cloud computing capabilities to the edge of the network i.e., at the base station level. To meet the latency requirements and avoid the end-to-end communication with remote cloud data centers, MEC allows to store and process video content (e.g., caching, transcoding, pre-processing) at the base stations. Both video on demand and live video streaming can utilize MEC to improve existing services and develop novel use cases, such as video analytics, and targeted advertisements. MEC is expected to reshape the future of video streaming by providing ultra-reliable and low latency streaming (e.g., in augmented reality, virtual reality, and autonomous vehicles), pervasive computing (e.g., in real-time video analytics), and blockchain-enabled architecture for secure live streaming. This paper presents a comprehensive survey of recent developments in MEC-enabled video streaming bringing unprecedented improvement to enable novel use cases. A detailed review of the state-of-the-art is presented covering novel caching schemes, optimal computation offloading, cooperative caching and offloading and the use of artificial intelligence (i.e., machine learning, deep learning, and reinforcement learning) in MEC-assisted video streaming services.publishedVersionPeer reviewe

Computing on the Edge of the Network

Um Systeme der fünften Generation zellularer Kommunikationsnetze (5G) zu ermöglichen, sind Energie effiziente Architekturen erforderlich, die eine zuverlässige Serviceplattform für die Bereitstellung von 5G-Diensten und darüber hinaus bieten können. Device Enhanced Edge Computing ist eine Ableitung des Multi-Access Edge Computing (MEC), das Rechen- und Speicherressourcen direkt auf den Endgeräten bereitstellt. Die Bedeutung dieses Konzepts wird durch die steigenden Anforderungen von rechenintensiven Anwendungen mit extrem niedriger Latenzzeit belegt, die den MEC-Server allein und den drahtlosen Kanal überfordern. Diese Dissertation stellt ein Berechnungs-Auslagerungsframework mit Berücksichtigung von Energie, Mobilität und Anreizen in einem gerätegestützten MEC-System mit mehreren Benutzern und mehreren Aufgaben vor, das die gegenseitige Abhängigkeit der Aufgaben sowie die Latenzanforderungen der Anwendungen berücksichtigt.To enable fifth generation cellular communication network (5G) systems, energy efficient architectures are required that can provide a reliable service platform for the delivery of 5G services and beyond. Device Enhanced Edge Computing is a derivative of Multi-Access Edge Computing (MEC), which provides computing and storage resources directly on the end devices. The importance of this concept is evidenced by the increasing demands of ultra-low latency computationally intensive applications that overwhelm the MEC server alone and the wireless channel. This dissertation presents a computational offloading framework considering energy, mobility and incentives in a multi-user, multi-task device-based MEC system that takes into account task interdependence and application latency requirements

Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

Security for network services delivery of 5G enabled device-to-device communications mobile network

The increase in mobile traffic led to the development of Fifth Generation (5G) mobile network. 5G will provide Ultra Reliable Low Latency Communication (URLLC), Massive Machine Type Communication (mMTC), enhanced Mobile Broadband (eMBB). Device-to-Device (D2D) communications will be used as the underlaying technology to offload traffic from 5G Core Network (5GC) and push content closer to User Equipment (UE). It will be supported by a variety of Network Service (NS) such as Content-Centric Networking (CCN) that will provide access to other services and deliver content-based services. However, this raises new security and delivery challenges. Therefore, research was conducted to address the security issues in delivering NS in 5G enabled D2D communications network. To support D2D communications in 5G, this thesis introduces a Network Services Delivery (NSD) framework defining an integrated system model. It incorporates Cloud Radio Access Network (C-RAN) architecture, D2D communications, and CCN to support 5G’s objectives in Home Network (HN), roaming, and proximity scenarios. The research explores the security of 5G enabled D2D communications by conducting a comprehensive investigation on security threats. It analyses threats using Dolev Yao (DY) threat model and evaluates security requirements using a systematic approach based on X.805 security framework. Which aligns security requirements with network connectivity, service delivery, and sharing between entities. This analysis highlights the need for security mechanisms to provide security to NSD in an integrated system, to specify these security mechanisms, a security framework to address the security challenges at different levels of the system model is introduced. To align suitable security mechanisms, the research defines underlying security protocols to provide security at the network, service, and D2D levels. This research also explores 5G authentication protocols specified by the Third Generation Partnership Project (3GPP) for securing communication between UE and HN, checks the security guarantees of two 3GPP specified protocols, 5G-Authentication and Key Agreement (AKA) and 5G Extensive Authentication Protocol (EAP)-AKA’ that provide primary authentication at Network Access Security (NAC). The research addresses Service Level Security (SLS) by proposing Federated Identity Management (FIdM) model to integrate federated security in 5G, it also proposes three security protocols to provide secondary authentication and authorization of UE to Service Provider (SP). It also addresses D2D Service Security (DDS) by proposing two security protocols that secure the caching and sharing of services between two UEs in different D2D communications scenarios. All protocols in this research are verified for functional correctness and security guarantees using a formal method approach and semi-automated protocol verifier. The research conducts security properties and performance evaluation of the protocols for their effectiveness. It also presents how each proposed protocol provides an interface for an integrated, comprehensive security solution to secure communications for NSD in a 5G enabled D2D communications network. The main contributions of this research are the design and formal verification of security protocols. Performance evaluation is supplementary