Driven by the quality of experience (QoE) requirement of video streaming applications in the smart city, smart education, immersive service, and connected vehicle scenarios, the existing network poses significant challenges, including ultra-high bandwidth, ultra-large storage, and ultra-low latency requirements, etc. Multi-access edge computing (MEC) is a potential technology, which can provide computation-intensive and caching-intensive services for video streaming applications to satisfy the requirement of QoE. Thus, focusing on video streaming schemes, a comprehensive summary of the state of the art applying MEC to video streaming is surveyed. Firstly, the related overview and background knowledge are reviewed. Secondly, resource allocation issues have been discussed. Thirdly, the enabling technologies for video streaming are summarized by taking account of caching, computing, and networking. Then, a taxonomy of MEC enabled video streaming applications is classified. Finally, challenges and future research directions are given.

A Survey on Multi-Access Edge Computing Applied to Video Streaming: Some Research Issues and Challenges

PCCP: Proactive Video Chunks Caching and Processing in edge networks

With the development of telecommunication technologies and the proliferation of network applications in the past decades, the traditional cloud network architecture becomes unable to accommodate such demands due to the heavy burden on the backhaul links and long latency. Therefore, edge computing, which brings network functions close to end-users by providing caching, computing and communication resources at network edges, turns into a promising paradigm. Benefit from its nature, edge computing enables emerging scenarios and use cases like Augmented Reality (AR) and Internet of Things (IowT). However, it also creates complexities to efficiently orchestrate heterogeneous services and manage distributed resources in the edge network. In this survey, we make a comprehensive review of the research efforts on service orchestration and resource management for edge computing. We first give an overview of edge computing, including architectures, advantages, enabling technologies and standardization. Next, a comprehensive survey of state-of-the-art techniques in the management and orchestration of edge computing is presented. Subsequently, the state-of-the-art research on the infrastructure of edge computing is discussed in various aspects. Finally, open research challenges and future directions are presented as well. 

Management and Orchestration of Edge Computing for IoT: A Comprehensive Survey

Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication

Instead of only focusing on the hit ratio of the videos cached in Mobile Edge Computing (MEC) server, we propose a more refined video segment content and client statusbased MEC cache update strategy, to improve clients’ Quality of Experience (QoE). First, based on both the segment popularity and importance, we divide MEC cache into three parts which can be flexibly transformed into each other by combing the requested times of segments, transmission capability and clients’ playback status together. Furthermore, we present the client’s cache priority utility function and formulate a problem to maximize the utility function subject to the constraints of MEC cache size and transmission capacity. The brand and branch method is employed to obtain the optimal solution. Simulation results show that our algorithm can improve system throughput, hit ratio of video segment, playback frozen time as well as backhaul traffic.

pdf/a-more-refined-mobile-edge-cache-replacement-scheme-for-4eqlwguhf4.pdf

A More Refined Mobile Edge Cache Replacement Scheme For Adaptive Video Streaming With Mutual Cooperation In Multi-Mec Servers

With the rapid development of Mobile Internet, online Video-on-Demand (VoD) services, primarily 4K video, grow tremendously with the key performance indicators of lower latency, higher bandwidth, and higher bitrate. However, due to the long-distance between the user equipment (UE) and Internet Service Provider, Quality-of-Service (QoS) in terms of low playback delay and high transmission rate cannot be guaranteed. Therefore, Mobile Edge Computing (MEC), at the edge of the cellular network, is highly recommended with the benefits of lower uncertainty and end-to-end latency. The UE can enjoy better customized services with more appropriate bitrates as a result. In this paper, we propose a practical framework of MEC-enabled cellular network with radio network-aware edge cache and a radio network-aware cache updating algorithm. The framework uses Dynamic Adaptive Streaming over HTTP (DASH) and Radio Network Information Service (RNIS) is leveraged to accelerate multi-media services. Under this framework, RNIS collects information and delivers it to the MEC server based on the context. A testbed based on a real 4G Long Term Evolution (LTE) Base Station is developed carrying out experiments under this framework. Compared to traditional networks, the result shows that our approach maintains a smooth high quality of experience (QoE).

Radio network-aware edge caching for video delivery in MEC-enabled cellular networks

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Radio network-aware edge caching for video delivery in MEC-enabled cellular networks