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

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.

[1]  Pradipta De,et al.  HotDASH: Hotspot Aware Adaptive Video Streaming Using Deep Reinforcement Learning , 2018, 2018 IEEE 26th International Conference on Network Protocols (ICNP).

[2]  Bharath Balasubramanian,et al.  Liv(e)-ing on the Edge: User-Uploaded Live Streams Driven by "First-Mile" Edge Decisions , 2019, 2019 IEEE International Conference on Edge Computing (EDGE).

[3]  Jacob Chakareski,et al.  VR/AR Immersive Communication: Caching, Edge Computing, and Transmission Trade-Offs , 2017, VR/AR Network@SIGCOMM.

[4]  Dario Sabella,et al.  MEC Support for Network Slicing: Status and Limitations from a Standardization Viewpoint , 2020, IEEE Communications Standards Magazine.

[5]  J. J. Garcia-Luna-Aceves,et al.  Joint Rate and FoV adaptation in immersive video streaming , 2018, VR/AR Network@SIGCOMM.

[6]  Hirley Alves,et al.  Network Slicing for URLLC and eMBB With Max-Matching Diversity Channel Allocation , 2020, IEEE Communications Letters.

[7]  Victor C. M. Leung,et al.  Distributed Resource Allocation in Blockchain-Based Video Streaming Systems With Mobile Edge Computing , 2019, IEEE Transactions on Wireless Communications.

[8]  Ananthram Swami,et al.  A Survey on Modeling and Optimizing Multi-Objective Systems , 2017, IEEE Communications Surveys & Tutorials.

[9]  Mahesh K. Marina,et al.  Network Slicing in 5G: Survey and Challenges , 2017, IEEE Communications Magazine.

[10]  Suman Banerjee,et al.  Hardware-Assisted, Low-Cost Video Transcoding Solution in Wireless Networks , 2020, IEEE Transactions on Mobile Computing.

[11]  Victor C. M. Leung,et al.  Resource Allocation for Video Transcoding and Delivery Based on Mobile Edge Computing and Blockchain , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[12]  Yezid Donoso,et al.  Multi-Objective Optimization in Computer Networks Using Metaheuristics , 2007 .

[13]  Xiaofeng Tao,et al.  Mobile Edge Computing Enhanced Adaptive Bitrate Video Delivery With Joint Cache and Radio Resource Allocation , 2017, IEEE Access.

[14]  Mugen Peng,et al.  Joint Radio Communication, Caching, and Computing Design for Mobile Virtual Reality Delivery in Fog Radio Access Networks , 2019, IEEE Journal on Selected Areas in Communications.

[15]  F. Richard Yu,et al.  Video Rate Adaptation and Traffic Engineering in Mobile Edge Computing and Caching-Enabled Wireless Networks , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[16]  Renchao Xie,et al.  Energy-Efficient Joint Caching and Transcoding for HTTP Adaptive Streaming in 5G Networks with Mobile Edge Computing , 2018, 2018 IEEE International Conference on Communications Workshops (ICC Workshops).

[17]  Jun-Ho Huh,et al.  Understanding Edge Computing: Engineering Evolution With Artificial Intelligence , 2019, IEEE Access.

[18]  Qing Wang,et al.  A Survey on Device-to-Device Communication in Cellular Networks , 2013, IEEE Communications Surveys & Tutorials.

[19]  Osvaldo Simeone,et al.  Energy-Efficient Resource Allocation for Mobile Edge Computing-Based Augmented Reality Applications , 2016, IEEE Wireless Communications Letters.

[20]  Bernd Girod,et al.  Analysis of video transmission over lossy channels , 2000, IEEE Journal on Selected Areas in Communications.

[21]  Lajos Hanzo,et al.  A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems , 2016, IEEE Communications Surveys & Tutorials.

[22]  Lothar Thiele,et al.  An evolutionary algorithm for multiobjective optimization: the strength Pareto approach , 1998 .

[23]  Dusit Niyato,et al.  Novel QoS-Guaranteed Orchestration Scheme for Energy-Efficient Mobile Augmented Reality Applications in Multi-Access Edge Computing , 2020, IEEE Transactions on Vehicular Technology.

[24]  Zhiguo Ding,et al.  A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art , 2019, IEEE Access.

[25]  Qichao Xu,et al.  Blockchain-Based Trustworthy Edge Caching Scheme for Mobile Cyber-Physical System , 2020, IEEE Internet of Things Journal.

[26]  Bruno Sinopoli,et al.  Toward a Principled Framework to Design Dynamic Adaptive Streaming Algorithms over HTTP , 2014, HotNets.

[27]  Songqing Chen,et al.  Software-Defined Networking Enhanced Edge Computing: A Network-Centric Survey , 2019, Proceedings of the IEEE.

[28]  Lu Wang,et al.  Quality-Oriented Perceptual HEVC Based on the Spatiotemporal Saliency Detection Model , 2019, Entropy.

[29]  Zhu Han,et al.  A Dynamic Edge Caching Framework for Mobile 5G Networks , 2018, IEEE Wireless Communications.

[30]  Dario Pompili,et al.  Adaptive Bitrate Video Caching and Processing in Mobile-Edge Computing Networks , 2019, IEEE Transactions on Mobile Computing.

[31]  Sujit Dey,et al.  Adaptive Bit Rate capable video caching and scheduling , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[32]  F. Richard Yu,et al.  MEC-Assisted Immersive VR Video Streaming Over Terahertz Wireless Networks: A Deep Reinforcement Learning Approach , 2020, IEEE Internet of Things Journal.

[33]  Tarik Taleb,et al.  On-the-Fly QoE-Aware Transcoding in the Mobile Edge , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[34]  Frank H. P. Fitzek,et al.  Demonstration of VR / AR offloading to Mobile Edge Cloud for low latency 5G gaming application , 2018, 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[35]  Ran Ju,et al.  VR is on the Edge: How to Deliver 360° Videos in Mobile Networks , 2017, VR/AR Network@SIGCOMM.

[36]  Filip De Turck,et al.  Network Function Virtualization: State-of-the-Art and Research Challenges , 2015, IEEE Communications Surveys & Tutorials.

[37]  Eui-Nam Huh,et al.  Edge Computing Assisted Joint Quality Adaptation for Mobile Video Streaming , 2019, IEEE Access.

[38]  Sujit Dey,et al.  Wireless VR/AR with Edge/Cloud Computing , 2017, 2017 26th International Conference on Computer Communication and Networks (ICCCN).

[39]  Truong Cong Thang,et al.  A subjective study on QoE of 360 video for VR communication , 2017, 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP).

[40]  Hang Liu,et al.  Wireless Adaptive Video Streaming with Edge Cloud , 2018, Wirel. Commun. Mob. Comput..

[41]  Wei Song,et al.  Collaborative Content Distribution in 5G Mobile Networks with Edge Caching , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[42]  Judy M. Vance,et al.  Industry use of virtual reality in product design and manufacturing: a survey , 2017, Virtual Reality.

[43]  Chen Zhang,et al.  A Survey on Large-Scale Software Defined Networking (SDN) Testbeds: Approaches and Challenges , 2017, IEEE Communications Surveys & Tutorials.

[44]  Amr Mohamed,et al.  Service-Less Video Multicast in 5G: Enablers and Challenges , 2020, IEEE Network.

[45]  Fuhong Lin,et al.  A New Resource Allocation Mechanism for Security of Mobile Edge Computing System , 2019, IEEE Access.

[46]  Tarik Taleb,et al.  On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration , 2017, IEEE Communications Surveys & Tutorials.

[47]  Petar Popovski,et al.  Minimizing Latency to Support VR Social Interactions Over Wireless Cellular Systems via Bandwidth Allocation , 2018, IEEE Wireless Communications Letters.

[48]  Tianyu Lu,et al.  QoE-Orientated Resource Allocation for Wireless VR over Small Cell Networks , 2018, 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP).

[49]  Yongdong Zhang,et al.  Dynamic Resource Allocation for Streaming Scalable Videos in SDN-Aided Dense Small-Cell Networks , 2019, IEEE Transactions on Communications.

[50]  Jiguo Yu,et al.  Edge Computing Security: State of the Art and Challenges , 2019, Proceedings of the IEEE.

[51]  Ronald Azuma,et al.  A Survey of Augmented Reality , 1997, Presence: Teleoperators & Virtual Environments.

[52]  Belghol Hibat Allah,et al.  MEC towards 5G: A Survey of Concepts, Use Cases, Location Tradeoffs , 2017 .

[53]  U. Rieder,et al.  Markov Decision Processes , 2010 .

[54]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[55]  Min Sheng,et al.  On the Interaction of Video Caching and Retrieving in Multi-Server Mobile-Edge Computing Systems , 2019, IEEE Wireless Communications Letters.

[56]  Mathias Wien,et al.  Standardization Status of Immersive Video Coding , 2019, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[57]  Yue Li,et al.  A Mobile Edge Computing-based architecture for improved adaptive HTTP video delivery , 2016, 2016 IEEE Conference on Standards for Communications and Networking (CSCN).

[58]  Abbas Mehrabi,et al.  D2D-Enabled Collaborative Edge Caching and Processing with Adaptive Mobile Video Streaming , 2019, 2019 IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).

[59]  Victor C. M. Leung,et al.  Intelligent Resource Allocation for Video Analytics in Blockchain-Enabled Internet of Autonomous Vehicles With Edge Computing , 2020, IEEE Internet of Things Journal.

[60]  Abbas Mehrabi,et al.  QoE-Traffic Optimization Through Collaborative Edge Caching in Adaptive Mobile Video Streaming , 2018, IEEE Access.

[61]  Yan Zhang,et al.  Mobile Edge Computing: A Survey , 2018, IEEE Internet of Things Journal.

[62]  Debargha Mukherjee,et al.  A Technical Overview of VP9—The Latest Open-Source Video Codec , 2013 .

[63]  Mohammed Samaka,et al.  Security Services Using Blockchains: A State of the Art Survey , 2018, IEEE Communications Surveys & Tutorials.

[64]  Mahmoud Al-Ayyoub,et al.  SDMEC: Software Defined System for Mobile Edge Computing , 2016, 2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW).

[65]  Guochu Shou,et al.  QoE analysis of NFV-based mobile edge computing video application , 2016, 2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC).

[66]  Cédric Westphal,et al.  Congestion-aware edge caching for adaptive video streaming in Information-Centric Networks , 2015, 2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC).

[67]  Li Bing,et al.  An MEC and NFV Integrated Network Architecture , 2019 .

[68]  Hari Kalva,et al.  The VC-1 Video Coding Standard , 2007, IEEE MultiMedia.

[69]  Xiaopei Wu,et al.  Edge Video Analytics for Public Safety: A Review , 2019, Proceedings of the IEEE.

[70]  Georgios Xilouris,et al.  An NFV-Based Video Quality Assessment Method over 5G Small Cell Networks , 2017, IEEE MultiMedia.

[71]  Rodrigo Roman,et al.  Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges , 2016, Future Gener. Comput. Syst..

[72]  Symeon Chatzinotas,et al.  Blockchain-based Content Delivery Networks: Content Transparency Meets User Privacy , 2019, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

[73]  F. Richard Yu,et al.  Enhancing Video Rate Adaptation With Mobile Edge Computing and Caching in Software-Defined Mobile Networks , 2018, IEEE Transactions on Wireless Communications.

[74]  Eirini Liotou,et al.  QoE-SDN APP: A Rate-guided QoE-aware SDN-APP for HTTP Adaptive Video Streaming , 2018, IEEE Journal on Selected Areas in Communications.

[75]  Hui Liu,et al.  Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff , 2018, IEEE Transactions on Communications.

[76]  Jon Montalban,et al.  MEC Proxy for Efficient Cache and Reliable Multi-CDN Video Distribution , 2018, 2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB).

[77]  Paolo Bellavista,et al.  Converging Mobile Edge Computing, Fog Computing, and IoT Quality Requirements , 2017, 2017 IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud).

[78]  Li Fan,et al.  Web caching and Zipf-like distributions: evidence and implications , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[79]  Tarik Taleb,et al.  Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions , 2018, IEEE Communications Surveys & Tutorials.

[80]  Halim Yanikomeroglu,et al.  Cooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks , 2018, IEEE Access.

[81]  Prasad Calyam,et al.  Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications , 2019, 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[82]  Shengqian Han,et al.  Proactive Edge Caching for Video on Demand With Quality Adaptation , 2020, IEEE Transactions on Wireless Communications.

[83]  Xing Zhang,et al.  Radio network-aware edge caching for video delivery in MEC-enabled cellular networks , 2018, 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[84]  Susana Sargento,et al.  Vehicle-to-Vehicle Real-Time Video Transmission through IEEE 802.11p for Assisted-Driving , 2018, 2018 IEEE 87th Vehicular Technology Conference (VTC Spring).

[85]  Tao Jiang,et al.  Multi-Bitrate Video Caching for D2D-Enabled Cellular Networks , 2019, IEEE MultiMedia.

[86]  Michela Ott,et al.  A LITERATURE REVIEW ON IMMERSIVE VIRTUAL REALITY IN EDUCATION: STATE OF THE ART AND PERSPECTIVES. , 2015, 11th International Conference eLearning and Software for Education.

[87]  Christopher Edwards,et al.  Adaptive Bitrate Selection: A Survey , 2017, IEEE Communications Surveys & Tutorials.

[88]  Rick S. Blum,et al.  A Survey of Caching Techniques in Cellular Networks: Research Issues and Challenges in Content Placement and Delivery Strategies , 2018, IEEE Communications Surveys & Tutorials.

[89]  Lillian Lee,et al.  Measures of Distributional Similarity , 1999, ACL.

[90]  Beng Chin Ooi,et al.  The Disruptions of 5G on Data-Driven Technologies and Applications , 2019, IEEE Transactions on Knowledge and Data Engineering.

[91]  Kazem Sohraby,et al.  Multimedia Sensing as a Service (MSaaS): Exploring Resource Saving Potentials of at Cloud-Edge IoT and Fogs , 2017, IEEE Internet of Things Journal.

[92]  K. R. Rao,et al.  VP6 Video Coding Standard , 2014 .

[93]  Abbas Mehrabi,et al.  Energy-Aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming , 2019, IEEE Transactions on Green Communications and Networking.

[94]  Yuan Cheng,et al.  Edge caching and computing in 5G for mobile augmented reality and haptic internet , 2020, Comput. Commun..

[95]  Dusit Niyato,et al.  Decentralized Caching for Content Delivery Based on Blockchain: A Game Theoretic Perspective , 2018, 2018 IEEE International Conference on Communications (ICC).

[96]  Zhou Su,et al.  Edge Caching for Layered Video Contents in Mobile Social Networks , 2017, IEEE Transactions on Multimedia.

[97]  Gian Paolo Rossi,et al.  A MEC Approach to Improve QoE of Video Delivery Service in Urban Spaces , 2018, 2018 IEEE International Conference on Smart Computing (SMARTCOMP).

[98]  Ayman I. Kayssi,et al.  Edge computing enabling the Internet of Things , 2015, 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT).

[99]  Minghua Chen,et al.  Understanding Performance of Edge Content Caching for Mobile Video Streaming , 2017, IEEE Journal on Selected Areas in Communications.

[100]  Nan Zhao,et al.  Integrated Networking, Caching, and Computing for Connected Vehicles: A Deep Reinforcement Learning Approach , 2018, IEEE Transactions on Vehicular Technology.

[101]  Hongbo Jiang,et al.  Adaptive Wireless Video Streaming Based on Edge Computing: Opportunities and Approaches , 2019, IEEE Transactions on Services Computing.

[102]  Adlen Ksentini,et al.  Toward Slicing-Enabled Multi-Access Edge Computing in 5G , 2020, IEEE Network.

[103]  Zdenek Becvar,et al.  Mobile Edge Computing: A Survey on Architecture and Computation Offloading , 2017, IEEE Communications Surveys & Tutorials.

[104]  Yue Cao,et al.  QoE-Driven DASH Video Caching and Adaptation at 5G Mobile Edge , 2016, ICN.

[105]  F. Richard Yu,et al.  Video Transcoding, Caching, and Multicast for Heterogeneous Networks Over Wireless Network Virtualization , 2018, IEEE Communications Letters.

[106]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[107]  F. Richard Yu,et al.  Blockchain-Enabled Cross-Domain Object Detection for Autonomous Driving: A Model Sharing Approach , 2020, IEEE Internet of Things Journal.

[108]  Atay Ozgovde,et al.  How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions , 2017, IEEE Communications Surveys & Tutorials.

[109]  Sujit Dey,et al.  Enhancing Mobile Video Capacity and Quality Using Rate Adaptation, RAN Caching and Processing , 2016, IEEE/ACM Transactions on Networking.

[110]  Christian Timmerer,et al.  A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP , 2019, IEEE Communications Surveys & Tutorials.

[111]  Xiong Xiong,et al.  Collaborative Edge Caching through Service Function Chaining: Architecture and Challenges , 2018, IEEE Wireless Communications.

[112]  Alex Pentland,et al.  Decentralizing Privacy: Using Blockchain to Protect Personal Data , 2015, 2015 IEEE Security and Privacy Workshops.

[113]  Zhu Han,et al.  When Mobile Blockchain Meets Edge Computing , 2017, IEEE Communications Magazine.

[114]  Bin Kang,et al.  MEC-enabled video streaming in device-to-device networks , 2020, IET Commun..

[115]  Xiantao Jiang,et al.  Low-Complexity and Hardware-Friendly H.265/HEVC Encoder for Vehicular Ad-Hoc Networks , 2019, Sensors.

[116]  Kenji Kanai,et al.  Overview of Multimedia Mobile Edge Computing , 2022 .

[117]  Iraj Sodagar,et al.  The MPEG-DASH Standard for Multimedia Streaming Over the Internet , 2011, IEEE MultiMedia.

[118]  Kyungbaek Kim,et al.  A Survey about Consensus Algorithms Used in Blockchain , 2018, J. Inf. Process. Syst..

[119]  Heiko Schwarz,et al.  Overview of the Scalable Video Coding Extension of the H.264/AVC Standard , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[120]  Mohsen Guizani,et al.  Proactive Video Chunks Caching and Processing for Latency and Cost Minimization in Edge Networks , 2018, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

[121]  Mehdi Bennis,et al.  Enhancing Video Streaming in Vehicular Networks via Resource Slicing , 2020, IEEE Transactions on Vehicular Technology.

[122]  Alex Graves,et al.  Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.

[123]  M. Siekkinen,et al.  Edge Computing Assisted Adaptive Mobile Video Streaming , 2019, IEEE Transactions on Mobile Computing.

[124]  Victor C. M. Leung,et al.  Decentralized Resource Allocation for Video Transcoding and Delivery in Blockchain-Based System With Mobile Edge Computing , 2019, IEEE Transactions on Vehicular Technology.

[125]  Mehmet Emin Aydin,et al.  QoE-Based Mobility-Aware Collaborative Video Streaming on the Edge of 5G , 2020, IEEE Transactions on Industrial Informatics.

[126]  Jianle Chen,et al.  Overview of SHVC: Scalable Extensions of the High Efficiency Video Coding Standard , 2016, IEEE Transactions on Circuits and Systems for Video Technology.

[127]  Muhanna Muhanna,et al.  Virtual reality and the CAVE: Taxonomy, interaction challenges and research directions , 2015, J. King Saud Univ. Comput. Inf. Sci..

[128]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[129]  Yanhua Zhang,et al.  Virtualization for Distributed Ledger Technology (vDLT) , 2018, IEEE Access.

[130]  Ning Zhang,et al.  A Survey of Distributed Consensus Protocols for Blockchain Networks , 2019, IEEE Communications Surveys & Tutorials.

[131]  Pascal Frossard,et al.  QoE-Driven Mobile Edge Caching Placement for Adaptive Video Streaming , 2018, IEEE Transactions on Multimedia.

[132]  Lifeng Sun,et al.  A Joint Online Transcoding and Delivery Approach for Dynamic Adaptive Streaming , 2015, IEEE Transactions on Multimedia.

[133]  Duy Trong Ngo,et al.  A Distributed Energy-Harvesting-Aware Routing Algorithm for Heterogeneous IoT Networks , 2018, IEEE Transactions on Green Communications and Networking.

[134]  F. Richard Yu,et al.  Joint Optimization of Radio and Computational Resources Allocation in Blockchain-Enabled Mobile Edge Computing Systems , 2020, IEEE Transactions on Wireless Communications.

[135]  Zhiyong Chen,et al.  Blockchain-Driven Contents Sharing Strategy for Wireless Cache-Enabled D2D Networks , 2019, 2019 IEEE International Conference on Communications Workshops (ICC Workshops).

[136]  A. Antony Franklin,et al.  Edge Assisted DASH Video Caching Mechanism for Multi-access Edge Computing , 2018, 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS).

[137]  Victor C. M. Leung,et al.  A Mobile Edge Computing (MEC)-Enabled Transcoding Framework for Blockchain-Based Video Streaming , 2020, IEEE Wireless Communications.

[138]  Tao Jiang,et al.  Edge Computing Framework for Cooperative Video Processing in Multimedia IoT Systems , 2018, IEEE Transactions on Multimedia.

[139]  Michael T. M. Emmerich,et al.  A tutorial on multiobjective optimization: fundamentals and evolutionary methods , 2018, Natural Computing.

[140]  Frank van Lingen,et al.  Toward a converged OpenFog and ETSI MANO architecture , 2017, 2017 IEEE Fog World Congress (FWC).

[141]  Ekram Hossain,et al.  A Blockchain Framework for Secure Task Sharing in Multi-Access Edge Computing , 2020, IEEE Network.

[142]  Xing Zhang,et al.  A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications , 2017, IEEE Access.

[143]  Tarik Taleb,et al.  Edge Computing for the Internet of Things: A Case Study , 2018, IEEE Internet of Things Journal.

[144]  Hong Wen,et al.  Security Enhancement for Mobile Edge Computing Through Physical Layer Authentication , 2019, IEEE Access.

[145]  Andrew Fecheyr-Lippens.  A Review of HTTP Live Streaming , 2010 .

[146]  K. B. Letaief,et al.  A Survey on Mobile Edge Computing: The Communication Perspective , 2017, IEEE Communications Surveys & Tutorials.

[147]  Lisheng Wang,et al.  Fast Coding Unit Size Decision Based on Probabilistic Graphical Model in High Efficiency Video Coding Inter Prediction , 2016, IEICE Trans. Inf. Syst..

[148]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[149]  Jiannong Cao,et al.  Joint Computation Partitioning and Resource Allocation for Latency Sensitive Applications in Mobile Edge Clouds , 2017, 2017 IEEE 10th International Conference on Cloud Computing (CLOUD).

[150]  Ali C. Begen,et al.  QoE-Aware Bandwidth Broker for HTTP Adaptive Streaming Flows in an SDN-Enabled HFC Network , 2018, IEEE Transactions on Broadcasting.

[151]  Zdravko Bozakov,et al.  Enable Advanced QoS-Aware Network Slicing in 5G Networks for Slice-Based Media Use Cases , 2019, IEEE Transactions on Broadcasting.

[152]  Evangelos Pallis,et al.  A View on Edge caching Applications , 2019, ArXiv.

[153]  Xinchang Zhang,et al.  An SDN-Based Video Multicast Orchestration Scheme for 5G Ultra-Dense Networks , 2017, IEEE Communications Magazine.

[154]  Abdulmotaleb El-Saddik,et al.  Edge Caching and Computing in 5G for Mobile AR/VR and Tactile Internet , 2019, IEEE MultiMedia.

[155]  Bing Chen,et al.  Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues , 2018, IEEE Access.

[156]  Ammar Muthanna,et al.  Optimization Algorithm for IPTV Video Service Delivery over SDN Using MEC Technology , 2018, NEW2AN.

[157]  Ke Zhang,et al.  Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading , 2017, IEEE Veh. Technol. Mag..

[158]  Mick Wilson,et al.  Toward QoE-Assured 4K Video-on-Demand Delivery Through Mobile Edge Virtualization With Adaptive Prefetching , 2017, IEEE Transactions on Multimedia.

[159]  Gary J. Sullivan,et al.  Overview of the High Efficiency Video Coding (HEVC) Standard , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[160]  Weihua Zhuang,et al.  Transmission Protocol Customization for Network Slicing: A Case Study of Video Streaming , 2019, IEEE Vehicular Technology Magazine.

[161]  S. Leela,et al.  LYAPUNOV THEORY FOR FRACTIONAL DIFFERENTIAL EQUATIONS , 2008 .

[162]  Ling Luo,et al.  Optimal Bandwidth Allocation with Edge Computing for Wireless VR Delivery , 2019, 2019 IEEE/CIC International Conference on Communications in China (ICCC).

[163]  Su Hu,et al.  Optimizing MEC Networks for Healthcare Applications in 5G Communications With the Authenticity of Users’ Priorities , 2019, IEEE Access.

[164]  Jasbir S. Arora,et al.  Survey of multi-objective optimization methods for engineering , 2004 .

[165]  Frank H. P. Fitzek,et al.  Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey , 2019, IEEE Access.

[166]  J. Hsu,et al.  Buffer Behavior with Poisson Arrival and Geometric Output Processes , 1974, IEEE Trans. Commun..

[167]  F. Richard Yu,et al.  Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues and Challenges , 2019, IEEE Communications Surveys & Tutorials.

[168]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.

[169]  Renwei Li,et al.  Latency Guarantee for Multimedia Streaming Service to Moving Subscriber with 5G Slicing , 2018, 2018 International Symposium on Networks, Computers and Communications (ISNCC).

[170]  Xing Zhang,et al.  Edge-assisted Adaptive Video Streaming with Deep Learning in Mobile Edge Networks , 2019, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

[171]  Hong Liu,et al.  Blockchain-Enabled Security in Electric Vehicles Cloud and Edge Computing , 2018, IEEE Network.

[172]  Yong Zhao,et al.  Communication-Constrained Mobile Edge Computing Systems for Wireless Virtual Reality: Scheduling and Tradeoff , 2018, IEEE Access.

[173]  Antonios Argyriou,et al.  MEC-Assisted Panoramic VR Video Streaming Over Millimeter Wave Mobile Networks , 2019, IEEE Transactions on Multimedia.

[174]  Jung-Min Park,et al.  IEEE 802.11bd & 5G NR V2X: Evolution of Radio Access Technologies for V2X Communications , 2019, IEEE Access.

[175]  Chan-Hyun Youn,et al.  Lightweight Online Profiling-Based Configuration Adaptation for Video Analytics System in Edge Computing , 2020, IEEE Access.

[176]  Juan Felipe Botero,et al.  Resource Allocation in NFV: A Comprehensive Survey , 2016, IEEE Transactions on Network and Service Management.

[177]  Federico Alvarez,et al.  An Edge-to-Cloud Virtualized Multimedia Service Platform for 5G Networks , 2019, IEEE Transactions on Broadcasting.

[178]  F. Richard Yu,et al.  Computation Offloading and Resource Allocation for Wireless Powered Mobile Edge Computing With Latency Constraint , 2019, IEEE Wireless Communications Letters.

[179]  Lin Tian,et al.  Mobile Edge Computing-Assisted Admission Control in Vehicular Networks: The Convergence of Communication and Computation , 2019, IEEE Vehicular Technology Magazine.

[180]  Federico Manuri,et al.  A Survey on Applications of Augmented Reality , 2016 .

[181]  Raihan Ur Rasool,et al.  Complementing IoT Services Through Software Defined Networking and Edge Computing: A Comprehensive Survey , 2020, IEEE Communications Surveys & Tutorials.

[182]  Victor C. M. Leung,et al.  A Deep Reinforcement Learning-Based Transcoder Selection Framework for Blockchain-Enabled Wireless D2D Transcoding , 2020, IEEE Transactions on Communications.

[183]  Tarik Taleb,et al.  Mobile Edge Computing Potential in Making Cities Smarter , 2017, IEEE Communications Magazine.

[184]  Thrasyvoulos Spyropoulos,et al.  Low Cost Video Streaming through Mobile Edge Caching: Modelling and Optimization , 2019, IEEE Transactions on Mobile Computing.

[185]  Jinsul Kim,et al.  NFV-Based Mobile Edge Computing for Lowering Latency of 4K Video Streaming , 2018, 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN).

[186]  Carlos J. Bernardos,et al.  On the integration of NFV and MEC technologies: architecture analysis and benefits for edge robotics , 2020, Comput. Networks.

[187]  Ali C. Begen,et al.  SDNHAS: An SDN-Enabled Architecture to Optimize QoE in HTTP Adaptive Streaming , 2017, IEEE Transactions on Multimedia.