Resource Scheduling in Edge Computing: A Survey

With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless networks, the surging demand for data communications and computing calls for the emerging edge computing paradigm. By moving the services and functions located in the cloud to the proximity of users, edge computing can provide powerful communication, storage, networking, and communication capacity. The resource scheduling in edge computing, which is the key to the success of edge computing systems, has attracted increasing research interests. In this paper, we survey the state-of-the-art research findings to know the research progress in this field. Specifically, we present the architecture of edge computing, under which different collaborative manners for resource scheduling are discussed. Particularly, we introduce a unified model before summarizing the current works on resource scheduling from three research issues, including computation offloading, resource allocation, and resource provisioning. Based on two modes of operation, i.e., centralized and distributed modes, different techniques for resource scheduling are discussed and compared. Also, we summarize the main performance indicators based on the surveyed literature. To shed light on the significance of resource scheduling in real-world scenarios, we discuss several typical application scenarios involved in the research of resource scheduling in edge computing. Finally, we highlight some open research challenges yet to be addressed and outline several open issues as the future research direction.

[1]  F. Richard Yu,et al.  Energy-efficient resource allocation in software-defined mobile networks with mobile edge computing and caching , 2017, 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[2]  Lei Shu,et al.  Parked Vehicle Edge Computing: Exploiting Opportunistic Resources for Distributed Mobile Applications , 2018, IEEE Access.

[3]  Haijian Sun,et al.  UAV-Enabled Mobile Edge Computing: Offloading Optimization and Trajectory Design , 2018, 2018 IEEE International Conference on Communications (ICC).

[4]  Choong Seon Hong,et al.  Decentralized Computation Offloading and Resource Allocation for Mobile-Edge Computing: A Matching Game Approach , 2018, IEEE Access.

[5]  Qiuping Li,et al.  Cooperative Computation Offloading and Resource Allocation for Mobile Edge Computing , 2019, 2019 IEEE International Conference on Communications Workshops (ICC Workshops).

[6]  Xinghui Zhao,et al.  Supporting Multi-Provider Serverless Computing on the Edge , 2018, ICPP Workshops.

[7]  Keqin Li,et al.  Multi-User Multi-Task Computation Offloading in Green Mobile Edge Cloud Computing , 2019, IEEE Transactions on Services Computing.

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

[9]  Atay Ozgovde,et al.  EdgeCloudSim: An environment for performance evaluation of Edge Computing systems , 2017, 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC).

[10]  Fei Dai,et al.  Dynamic resource provisioning for workflow scheduling under uncertainty in edge computing environment , 2020, Concurr. Comput. Pract. Exp..

[11]  Ching-Hsien Hsu,et al.  Edge server placement in mobile edge computing , 2019, J. Parallel Distributed Comput..

[12]  Fei Dai,et al.  Trust-Oriented IoT Service Placement for Smart Cities in Edge Computing , 2020, IEEE Internet of Things Journal.

[13]  Bruno Volckaert,et al.  Resource Provisioning in Fog Computing: From Theory to Practice † , 2019, Sensors.

[14]  Md Zakirul Alam Bhuiyan,et al.  Joint Optimization of Offloading Utility and Privacy for Edge Computing Enabled IoT , 2020, IEEE Internet of Things Journal.

[15]  Janick Edinger,et al.  Context-Aware Data and Task Placement in Edge Computing Environments , 2019, 2019 IEEE International Conference on Pervasive Computing and Communications (PerCom.

[16]  G. Amdhal,et al.  Validity of the single processor approach to achieving large scale computing capabilities , 1967, AFIPS '67 (Spring).

[17]  Peilin Hong,et al.  Virtual network function placement and resource optimization in NFV and edge computing enabled networks , 2019, Comput. Networks.

[18]  Junlong Zhu,et al.  A Computing Offloading Game for Mobile Devices and Edge Cloud Servers , 2018, Wirel. Commun. Mob. Comput..

[19]  Yi Lin,et al.  Enhancing Edge Computing with Database Replication , 2007, 2007 26th IEEE International Symposium on Reliable Distributed Systems (SRDS 2007).

[20]  Ke Zhang,et al.  Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks , 2019, IEEE Transactions on Vehicular Technology.

[21]  Hong-Ning Dai,et al.  A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing , 2019, IEEE Transactions on Industrial Informatics.

[22]  Weisong Shi,et al.  EdgeABC: An architecture for task offloading and resource allocation in the Internet of Things , 2020, Future Gener. Comput. Syst..

[23]  Jie Xu,et al.  Risk-Aware Edge Computation Offloading Using Bayesian Stackelberg Game , 2020, IEEE Transactions on Network and Service Management.

[24]  Lei Guo,et al.  Green Survivable Collaborative Edge Computing in Smart Cities , 2018, IEEE Transactions on Industrial Informatics.

[25]  Victor C. M. Leung,et al.  Joint Resource Allocation for Latency-Sensitive Services Over Mobile Edge Computing Networks With Caching , 2019, IEEE Internet of Things Journal.

[26]  Hyunsik Yang,et al.  Usage Aware VNF Placement for Improved QoS in Edge Computing , 2019, 2019 International Conference on Information and Communication Technology Convergence (ICTC).

[27]  F. Richard Yu,et al.  Resource Allocation for Information-Centric Virtualized Heterogeneous Networks With In-Network Caching and Mobile Edge Computing , 2017, IEEE Transactions on Vehicular Technology.

[28]  Qiang Ye,et al.  DMRA: A Decentralized Resource Allocation Scheme for Multi-SP Mobile Edge Computing , 2019, 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS).

[29]  Qun Li,et al.  Efficient service handoff across edge servers via docker container migration , 2017, SEC.

[30]  Jakub Konecný,et al.  Federated Optimization: Distributed Optimization Beyond the Datacenter , 2015, ArXiv.

[31]  Xiang-Yang Li,et al.  Joint Heterogeneous Server Placement and Application Configuration in Edge Computing , 2019, 2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS).

[32]  Yong Wang,et al.  Joint Deployment and Task Scheduling Optimization for Large-Scale Mobile Users in Multi-UAV-Enabled Mobile Edge Computing , 2020, IEEE Transactions on Cybernetics.

[33]  Ke Zhang,et al.  Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics , 2019, IEEE Internet of Things Journal.

[34]  Wei Ni,et al.  Optimal Schedule of Mobile Edge Computing for Internet of Things Using Partial Information , 2017, IEEE Journal on Selected Areas in Communications.

[35]  Victor C. M. Leung,et al.  Adaptive Resource Allocation in Future Wireless Networks With Blockchain and Mobile Edge Computing , 2020, IEEE Transactions on Wireless Communications.

[36]  Jukka K. Nurminen,et al.  Energy Efficiency of Mobile Clients in Cloud Computing , 2010, HotCloud.

[37]  Hai Jin,et al.  Computation Offloading Toward Edge Computing , 2019, Proceedings of the IEEE.

[38]  Zheng Chang,et al.  Adaptive Service Offloading for Revenue Maximization in Mobile Edge Computing With Delay-Constraint , 2019, IEEE Internet of Things Journal.

[39]  Bo Yang,et al.  A Stackelberg game approach to multiple resources allocation and pricing in mobile edge computing , 2020, Future Gener. Comput. Syst..

[40]  Mohsen Guizani,et al.  When Mobile Crowd Sensing Meets UAV: Energy-Efficient Task Assignment and Route Planning , 2018, IEEE Transactions on Communications.

[41]  Xu Chen,et al.  Learning Driven Computation Offloading for Asymmetrically Informed Edge Computing , 2019, IEEE Transactions on Parallel and Distributed Systems.

[42]  Xu Chen,et al.  Adaptive User-managed Service Placement for Mobile Edge Computing: An Online Learning Approach , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[43]  Xiaoming Tao,et al.  Latency Minimization for D2D-Enabled Partial Computation Offloading in Mobile Edge Computing , 2020, IEEE Transactions on Vehicular Technology.

[44]  Xiongwen Zhao,et al.  Learning-Based Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT , 2020, IEEE Internet of Things Journal.

[45]  Xuemin Shen,et al.  Air-Ground Integrated Vehicular Network Slicing With Content Pushing and Caching , 2018, IEEE Journal on Selected Areas in Communications.

[46]  Tao Huang,et al.  An energy-aware computation offloading method for smart edge computing in wireless metropolitan area networks , 2019, J. Netw. Comput. Appl..

[47]  Rajkumar Buyya,et al.  Profit-aware application placement for integrated Fog-Cloud computing environments , 2020, J. Parallel Distributed Comput..

[48]  Zhaohui Yang,et al.  Efficient Resource Allocation for Mobile-Edge Computing Networks With NOMA: Completion Time and Energy Minimization , 2019, IEEE Transactions on Communications.

[49]  Hyundong Shin,et al.  Learning for Computation Offloading in Mobile Edge Computing , 2018, IEEE Transactions on Communications.

[50]  Wessam Ajib,et al.  Joint Container Placement and Task Provisioning in Dynamic Fog Computing , 2019, IEEE Internet of Things Journal.

[51]  Samson Lasaulce,et al.  Game Theory and Learning for Wireless Networks: Fundamentals and Applications , 2011 .

[52]  Jie Xu,et al.  Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications.

[53]  Changle Li,et al.  Minimizing the Delay and Cost of Computation Offloading for Vehicular Edge Computing , 2021, IEEE Transactions on Services Computing.

[54]  Rong Yu,et al.  Social Welfare Maximization in Container-Based Task Scheduling for Parked Vehicle Edge Computing , 2019, IEEE Communications Letters.

[55]  Zhu Han,et al.  Minimization of Offloading Delay for Two-Tier UAV with Mobile Edge Computing , 2019, 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC).

[56]  Jun Guo,et al.  Mobile Edge Computing Empowered Energy Efficient Task Offloading in 5G , 2018, IEEE Transactions on Vehicular Technology.

[57]  Victor C. M. Leung,et al.  Virtual Resource Allocation for Heterogeneous Services in Full Duplex-Enabled SCNs With Mobile Edge Computing and Caching , 2017, IEEE Transactions on Vehicular Technology.

[58]  Ying Cui,et al.  2017 Energy-Efficient Resource Allocation for Cache-Assisted Mobile Edge Computing , 2017 .

[59]  Ali Selamat,et al.  AZSPM: Autonomic Zero-Knowledge Security Provisioning Model for Medical Control Systems in Fog Computing Environments , 2017, 2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops).

[60]  Dusit Niyato,et al.  Social Welfare Maximization Auction in Edge Computing Resource Allocation for Mobile Blockchain , 2017, 2018 IEEE International Conference on Communications (ICC).

[61]  Lajos Hanzo,et al.  Efficient Resource Allocation for Relay-Assisted Computation Offloading in Mobile-Edge Computing , 2019, IEEE Internet of Things Journal.

[62]  Jiabin Wang,et al.  A Survey on Mobile Edge Computing: Focusing on Service Adoption and Provision , 2018, Wirel. Commun. Mob. Comput..

[63]  Gyorgy Dan,et al.  Computation Offloading Scheduling for Periodic Tasks in Mobile Edge Computing , 2020, IEEE/ACM Transactions on Networking.

[64]  Danny H. K. Tsang,et al.  NOMA-Enabled Mobile Edge Computing for Internet of Things via Joint Communication and Computation Resource Allocations , 2020, IEEE Internet of Things Journal.

[65]  Qun Li,et al.  A Survey of Virtual Machine Management in Edge Computing , 2019, Proceedings of the IEEE.

[66]  Mengyu Liu,et al.  Price-Based Distributed Offloading for Mobile-Edge Computing With Computation Capacity Constraints , 2017, IEEE Wireless Communications Letters.

[67]  Weimin Li,et al.  A fault-tolerant dynamic scheduling method on hierarchical mobile edge cloud computing , 2019, Comput. Intell..

[68]  Zhenyu Zhou,et al.  Energy-Efficient Edge Computing Service Provisioning for Vehicular Networks: A Consensus ADMM Approach , 2019, IEEE Transactions on Vehicular Technology.

[69]  Daniel Grosu,et al.  Energy-Aware Capacity Provisioning and Resource Allocation in Edge Computing Systems , 2019, EDGE.

[70]  Weisong Shi,et al.  Collaborative Data Scheduling for Vehicular Edge Computing via Deep Reinforcement Learning , 2020, IEEE Internet of Things Journal.

[71]  Fei Xu,et al.  Winning at the Starting Line: Joint Network Selection and Service Placement for Mobile Edge Computing , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[72]  Song Guo,et al.  A Deep Reinforcement Learning Based Offloading Game in Edge Computing , 2020, IEEE Transactions on Computers.

[73]  Tom H. Luan,et al.  Optimal Utility of Vehicles in LTE-V Scenario: An Immune Clone-Based Spectrum Allocation Approach , 2019, IEEE Transactions on Intelligent Transportation Systems.

[74]  Jun Cai,et al.  An Online Incentive Mechanism for Collaborative Task Offloading in Mobile Edge Computing , 2020, IEEE Transactions on Wireless Communications.

[75]  Yanhua Zhang,et al.  Delay-Tolerant Data Traffic to Software-Defined Vehicular Networks With Mobile Edge Computing in Smart City , 2018, IEEE Transactions on Vehicular Technology.

[76]  Weihua Zhuang,et al.  A Comprehensive Simulation Platform for Space-Air-Ground Integrated Network , 2020, IEEE Wireless Communications.

[77]  Jie Zhang,et al.  Computation Offloading for Multi-Access Mobile Edge Computing in Ultra-Dense Networks , 2018, IEEE Communications Magazine.

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

[79]  Yue Wang,et al.  Effective Capacity-Based Resource Allocation in Mobile Edge Computing With Two-Stage Tandem Queues , 2019, IEEE Transactions on Communications.

[80]  Depeng Jin,et al.  Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures , 2016, IEEE Transactions on Vehicular Technology.

[81]  Richeng Jin,et al.  Peace: Privacy-Preserving and Cost-Efficient Task Offloading for Mobile-Edge Computing , 2020, IEEE Transactions on Wireless Communications.

[82]  Long Hu,et al.  Privacy-aware service placement for mobile edge computing via federated learning , 2019, Inf. Sci..

[83]  Jie Wu,et al.  Cost-Efficient Resource Provision for Multiple Mobile Users in Fog Computing , 2019, 2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS).

[84]  Yan Zhang,et al.  Joint Offloading and Resource Allocation in Vehicular Edge Computing and Networks , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[85]  Changchuan Yin,et al.  Joint resource allocation and computation offloading in mobile edge computing for SDN based wireless networks , 2020, Journal of Communications and Networks.

[86]  George Mastorakis,et al.  Edge Caching Architecture for Media Delivery over P2P Networks , 2018, 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD).

[87]  Jie Xu,et al.  Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks , 2017, IEEE/ACM Transactions on Networking.

[88]  Yong Ren,et al.  Energy-Efficient Computation Offloading for Secure UAV-Edge-Computing Systems , 2019, IEEE Transactions on Vehicular Technology.

[89]  Khaled Ben Letaief,et al.  Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices , 2016, IEEE Journal on Selected Areas in Communications.

[90]  Sherali Zeadally,et al.  Energy-efficient Workload Allocation and Computation Resource Configuration in Distributed Cloud/Edge Computing Systems With Stochastic Workloads , 2020, IEEE Journal on Selected Areas in Communications.

[91]  Xuemin Shen,et al.  Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization , 2020, IEEE Transactions on Vehicular Technology.

[92]  Fu Jiang,et al.  An Energy-Aware Task Offloading Mechanism in Multiuser Mobile-Edge Cloud Computing , 2018, Mob. Inf. Syst..

[93]  Francesco Chiti,et al.  Virtual Functions Placement With Time Constraints in Fog Computing: A Matching Theory Perspective , 2019, IEEE Transactions on Network and Service Management.

[94]  Marwan Krunz,et al.  QoE and power efficiency tradeoff for fog computing networks with fog node cooperation , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[95]  Tie Qiu,et al.  Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach , 2021, IEEE Journal on Selected Areas in Communications.

[96]  Ben Liang,et al.  Fair multi-resource allocation with external resource for mobile edge computing , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[97]  Zhangdui Zhong,et al.  Optimal Offloading with Non-Orthogonal Multiple Access in Mobile Edge Computing , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[98]  George Mastorakis,et al.  Vulnerability assessment as a service for fog-centric ICT ecosystems: A healthcare use case , 2019, Peer-to-Peer Netw. Appl..

[99]  Luiz Fernando Bittencourt,et al.  MyiFogSim: A Simulator for Virtual Machine Migration in Fog Computing , 2017, UCC.

[100]  Xuyun Zhang,et al.  A blockchain‐based computation offloading method for edge computing in 5G networks , 2019, Softw. Pract. Exp..

[101]  Ying Jun Zhang,et al.  Computation Rate Maximization for Wireless Powered Mobile-Edge Computing With Binary Computation Offloading , 2017, IEEE Transactions on Wireless Communications.

[102]  Taewon Hwang,et al.  Joint Task Scheduling and Containerizing for Efficient Edge Computing , 2021, IEEE Transactions on Parallel and Distributed Systems.

[103]  Rajkumar Buyya,et al.  iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments , 2016, Softw. Pract. Exp..

[104]  Xiao Zheng,et al.  Task scheduling using edge computing system in smart city , 2020, Int. J. Commun. Syst..

[105]  Xiaojiang Du,et al.  Toward Reinforcement-Learning-Based Service Deployment of 5G Mobile Edge Computing with Request-Aware Scheduling , 2020, IEEE Wireless Communications.

[106]  Weisong Shi,et al.  EdgeVCD: Intelligent Algorithm-Inspired Content Distribution in Vehicular Edge Computing Network , 2020, IEEE Internet of Things Journal.

[107]  Wu Jigang,et al.  Efficient task scheduling for servers with dynamic states in vehicular edge computing , 2020, Comput. Commun..

[108]  Qianbin Chen,et al.  Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing , 2017, IEEE Transactions on Wireless Communications.

[109]  Weisong Shi,et al.  LAVEA: latency-aware video analytics on edge computing platform , 2017, SEC.

[110]  A. Tulino,et al.  Joint Service Placement and Request Routing in Multi-cell Mobile Edge Computing Networks , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[111]  Nuno Santos,et al.  HomePad: A Privacy-Aware Smart Hub for Home Environments , 2018, 2018 IEEE/ACM Symposium on Edge Computing (SEC).

[112]  Yacine Ghamri-Doudane,et al.  Optimized Placement of Scalable IoT Services in Edge Computing , 2019, 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).

[113]  Tang Jianhang,et al.  Joint optimization of data placement and scheduling for improving user experience in edge computing , 2019, J. Parallel Distributed Comput..

[114]  Mahadev Satyanarayanan,et al.  Early Implementation Experience with Wearable Cognitive Assistance Applications , 2015, WearSys@MobiSys.

[115]  Blesson Varghese,et al.  A Survey on Edge Benchmarking , 2020, ArXiv.

[116]  Xin Yao,et al.  Parallel Offloading in Green and Sustainable Mobile Edge Computing for Delay-Constrained IoT System , 2019, IEEE Transactions on Vehicular Technology.

[117]  Chang Wang,et al.  Energy-efficient Offloading Policy for Resource Allocation in Distributed Mobile Edge Computing , 2018, 2018 IEEE Symposium on Computers and Communications (ISCC).

[118]  Yue Zhang,et al.  A Distributed Framework for Task Offloading in Edge Computing Networks of Arbitrary Topology , 2020, IEEE Transactions on Wireless Communications.

[119]  Xi Li,et al.  Joint load management and resource allocation in the energy harvesting powered small cell networks with mobile edge computing , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[120]  Haibin Zhang,et al.  Double Auction-Based Resource Allocation for Mobile Edge Computing in Industrial Internet of Things , 2018, IEEE Transactions on Industrial Informatics.

[121]  Choong Seon Hong,et al.  Edge-of-things computing framework for cost-effective provisioning of healthcare data , 2019, J. Parallel Distributed Comput..

[122]  Sungrae Cho,et al.  Frequency Resource Allocation and Interference Management in Mobile Edge Computing for an Internet of Things System , 2019, IEEE Internet of Things Journal.

[123]  Fei Dai,et al.  Multi-objective computation offloading for Internet of Vehicles in cloud-edge computing , 2019, Wireless Networks.

[124]  Ali Ghrayeb,et al.  Optimized Provisioning of Edge Computing Resources With Heterogeneous Workload in IoT Networks , 2019, IEEE Transactions on Network and Service Management.

[125]  F. Richard Yu,et al.  Virtual resource allocation for information-centric heterogeneous networks with mobile edge computing , 2017, 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[126]  Huimin Yu,et al.  Deep Reinforcement Learning for Offloading and Resource Allocation in Vehicle Edge Computing and Networks , 2019, IEEE Transactions on Vehicular Technology.

[127]  Prashant Pandey,et al.  Cloud computing , 2010, ICWET.

[128]  Tony Q. S. Quek,et al.  Computation Offloading for Mobile Edge Computing Enabled Vehicular Networks , 2019, IEEE Access.

[129]  Yanlin Yue,et al.  AI-Enhanced Offloading in Edge Computing: When Machine Learning Meets Industrial IoT , 2019, IEEE Network.

[130]  Yan Zhang,et al.  Joint Computation Offloading and User Association in Multi-Task Mobile Edge Computing , 2018, IEEE Transactions on Vehicular Technology.

[131]  Peng Liu,et al.  ParaDrop: Enabling Lightweight Multi-tenancy at the Network’s Extreme Edge , 2016, 2016 IEEE/ACM Symposium on Edge Computing (SEC).

[132]  Victor C. M. Leung,et al.  An Efficient Computation Offloading Management Scheme in the Densely Deployed Small Cell Networks With Mobile Edge Computing , 2018, IEEE/ACM Transactions on Networking.

[133]  Wenjie Li,et al.  Joint Resource Allocation and Computation Offloading With Time-Varying Fading Channel in Vehicular Edge Computing , 2020, IEEE Transactions on Vehicular Technology.

[134]  Kai Lin,et al.  Task offloading and resource allocation for edge-of-things computing on smart healthcare systems , 2018, Comput. Electr. Eng..

[135]  Wei Song,et al.  Auction Mechanisms Toward Efficient Resource Sharing for Cloudlets in Mobile Cloud Computing , 2016, IEEE Transactions on Services Computing.

[136]  Gaofeng Nie,et al.  Context-Aware TDD Configuration and Resource Allocation for Mobile Edge Computing , 2020, IEEE Transactions on Communications.

[137]  Rajkumar Buyya,et al.  Quality of Experience (QoE)-aware placement of applications in Fog computing environments , 2019, J. Parallel Distributed Comput..

[138]  Jiajia Liu,et al.  Collaborative Computation Offloading for Multiaccess Edge Computing Over Fiber–Wireless Networks , 2018, IEEE Transactions on Vehicular Technology.

[139]  Claudia Canali,et al.  GASP: Genetic Algorithms for Service Placement in Fog Computing Systems , 2019, Algorithms.

[140]  Ming Chen,et al.  Energy-Efficient NOMA-Based Mobile Edge Computing Offloading , 2019, IEEE Communications Letters.

[141]  Ching-Hsien Hsu,et al.  User allocation‐aware edge cloud placement in mobile edge computing , 2020, Softw. Pract. Exp..

[142]  Weimin Li,et al.  A fault‐tolerant dynamic scheduling method on hierarchical mobile edge cloud computing , 2019, Computational Intelligence.

[143]  Miao Pan,et al.  Task-Oriented Intelligent Networking Architecture for the Space–Air–Ground–Aqua Integrated Network , 2020, IEEE Internet of Things Journal.

[144]  Jörg Henkel,et al.  Computation offloading and resource allocation for low-power IoT edge devices , 2016, 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT).

[145]  Zhi Zhou,et al.  Efficient Resource Allocation for On-Demand Mobile-Edge Cloud Computing , 2018, IEEE Transactions on Vehicular Technology.

[146]  Hee Yong Youn,et al.  Task Classification and Scheduling Based on K-Means Clustering for Edge Computing , 2020, Wirel. Pers. Commun..

[147]  Qi Zhang,et al.  Reliability and Latency Aware Code-Partitioning Offloading in Mobile Edge Computing , 2019, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

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

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

[150]  Zibin Zheng,et al.  Multi-Hop Cooperative Computation Offloading for Industrial IoT–Edge–Cloud Computing Environments , 2019, IEEE Transactions on Parallel and Distributed Systems.

[151]  Alireza Souri,et al.  Resource Management Approaches in Fog Computing: a Comprehensive Review , 2019, Journal of Grid Computing.

[152]  Weizhe Zhang,et al.  Resource allocation and computation offloading with data security for mobile edge computing , 2019, Future Gener. Comput. Syst..

[153]  Lei Lei,et al.  Resource Allocation Based on Deep Reinforcement Learning in IoT Edge Computing , 2020, IEEE Journal on Selected Areas in Communications.

[154]  Tao Luo,et al.  A new replica placement mechanism for mobile media streaming in edge computing , 2019 .

[155]  Tony Q. S. Quek,et al.  Online Resource Procurement and Allocation in a Hybrid Edge-Cloud Computing System , 2020, IEEE Transactions on Wireless Communications.

[156]  Cristina Cervelló-Pastor,et al.  Network-Aware Placement Optimization for Edge Computing Infrastructure Under 5G , 2020, IEEE Access.

[157]  Yuan-Cheng Lai,et al.  Workload and Capacity Optimization for Cloud-Edge Computing Systems with Vertical and Horizontal Offloading , 2020, IEEE Transactions on Network and Service Management.

[158]  K. K. Ramakrishnan,et al.  Over the top video: the gorilla in cellular networks , 2011, IMC '11.

[159]  Shuai Zheng,et al.  Federated Learning-Based Computation Offloading Optimization in Edge Computing-Supported Internet of Things , 2019, IEEE Access.

[160]  H. Vincent Poor,et al.  Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing , 2018, IEEE Transactions on Communications.

[161]  Xuemin Shen,et al.  Multi-Agent Reinforcement Learning Based Resource Management in MEC- and UAV-Assisted Vehicular Networks , 2021, IEEE Journal on Selected Areas in Communications.

[162]  Yan Zhang,et al.  Optimal delay constrained offloading for vehicular edge computing networks , 2017, 2017 IEEE International Conference on Communications (ICC).

[163]  Min Sheng,et al.  Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling , 2016, IEEE Transactions on Communications.

[164]  Stefano Secci,et al.  ULOOF: A User Level Online Offloading Framework for Mobile Edge Computing , 2018, IEEE Transactions on Mobile Computing.

[165]  Anshul Gandhi,et al.  FnSched: An Efficient Scheduler for Serverless Functions , 2019, WOSC@Middleware.

[166]  Honggang Zhang,et al.  Performance and Stability of Application Placement in Mobile Edge Computing System , 2018, 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC).

[167]  Xu Chen,et al.  In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning , 2018, IEEE Network.

[168]  Yunlong Cai,et al.  Mobile Edge Computing Meets mmWave Communications: Joint Beamforming and Resource Allocation for System Delay Minimization , 2020, IEEE Transactions on Wireless Communications.

[169]  Weihua Zhuang,et al.  Software Defined Space-Air-Ground Integrated Vehicular Networks: Challenges and Solutions , 2017, IEEE Communications Magazine.

[170]  Tom H. Luan,et al.  Self-Learning Based Computation Offloading for Internet of Vehicles: Model and Algorithm , 2021, IEEE Transactions on Wireless Communications.

[171]  Jeongho Kwak,et al.  Dual-Side Optimization for Cost-Delay Tradeoff in Mobile Edge Computing , 2017, IEEE Transactions on Vehicular Technology.

[172]  Yan Wang,et al.  Computation Offloading with Multiple Agents in Edge-Computing–Supported IoT , 2019, ACM Trans. Sens. Networks.

[173]  Weiwei Lin,et al.  A Latency-Aware Multiple Data Replicas Placement Strategy for Fog Computing , 2019, J. Signal Process. Syst..

[174]  Victor C. M. Leung,et al.  An energy- and cost-aware computation offloading method for workflow applications in mobile edge computing , 2019, EURASIP J. Wirel. Commun. Netw..

[175]  Xi Wang,et al.  FOGPLAN: A Lightweight QoS-Aware Dynamic Fog Service Provisioning Framework , 2019, IEEE Internet of Things Journal.

[176]  Yusheng Ji,et al.  AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling , 2017, IEEE Transactions on Vehicular Technology.

[177]  Fu-Chun Zheng,et al.  Joint Optimal Software Caching, Computation Offloading and Communications Resource Allocation for Mobile Edge Computing , 2020, IEEE Transactions on Vehicular Technology.

[178]  Yue Gao,et al.  Resource Allocation With Edge Computing in IoT Networks via Machine Learning , 2020, IEEE Internet of Things Journal.

[179]  Setareh Maghsudi,et al.  Computation Offloading and Activation of Mobile Edge Computing Servers: A Minority Game , 2017, IEEE Wireless Communications Letters.

[180]  Klervie Toczé,et al.  A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing , 2018, Wirel. Commun. Mob. Comput..

[181]  Fagui Liu,et al.  Energy-Efficient Collaborative Task Computation Offloading in Cloud-Assisted Edge Computing for IoT Sensors , 2019, Sensors.

[182]  Guanghui Li,et al.  Dynamic Request Scheduling Optimization in Mobile Edge Computing for IoT Applications , 2020, IEEE Internet of Things Journal.

[183]  M. Shamim Hossain,et al.  Energy Efficient Task Caching and Offloading for Mobile Edge Computing , 2018, IEEE Access.

[184]  Zhe Yu,et al.  Joint Task Offloading and Resource Allocation in UAV-Enabled Mobile Edge Computing , 2020, IEEE Internet of Things Journal.

[185]  Junzhou Luo,et al.  Cooperative storage by exploiting graph‐based data placement algorithm for edge computing environment , 2018, Concurr. Comput. Pract. Exp..

[186]  Nirwan Ansari,et al.  On cost aware cloudlet placement for mobile edge computing , 2019, IEEE/CAA Journal of Automatica Sinica.

[187]  Der-Jiunn Deng,et al.  Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network , 2019, IEEE Transactions on Industrial Informatics.

[188]  Yu Liu,et al.  Performance Guaranteed Partial Offloading for Mobile Edge Computing , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

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

[190]  Hossam S. Hassanein,et al.  Vehicle as a resource (VaaR) , 2014, IEEE Network.

[191]  Kai-Kit Wong,et al.  UAV-Assisted Relaying and Edge Computing: Scheduling and Trajectory Optimization , 2018, IEEE Transactions on Wireless Communications.

[192]  Sanglu Lu,et al.  Joint Server Assignment and Resource Management for Edge-Based MAR System , 2020, IEEE/ACM Transactions on Networking.

[193]  Heiko Ludwig,et al.  Zenith: Utility-Aware Resource Allocation for Edge Computing , 2017, 2017 IEEE International Conference on Edge Computing (EDGE).

[194]  Haifeng Lu,et al.  Optimization of lightweight task offloading strategy for mobile edge computing based on deep reinforcement learning , 2020, Future Gener. Comput. Syst..

[195]  Jiaqing Chen,et al.  A Time-Driven Data Placement Strategy for a Scientific Workflow Combining Edge Computing and Cloud Computing , 2019, IEEE Transactions on Industrial Informatics.

[196]  Ahmed Ghoneim,et al.  Intelligent task prediction and computation offloading based on mobile-edge cloud computing , 2020, Future Gener. Comput. Syst..

[197]  Jie Gao,et al.  Partial Offloading Scheduling and Power Allocation for Mobile Edge Computing Systems , 2019, IEEE Internet of Things Journal.

[198]  David A. Patterson,et al.  Cloud Programming Simplified: A Berkeley View on Serverless Computing , 2019, ArXiv.

[199]  Toby Velte,et al.  Cloud Computing, A Practical Approach , 2009 .

[200]  Victor C. M. Leung,et al.  A Distributed Computation Offloading Strategy in Small-Cell Networks Integrated With Mobile Edge Computing , 2018, IEEE/ACM Transactions on Networking.

[201]  Dusit Niyato,et al.  Optimal Auction for Edge Computing Resource Management in Mobile Blockchain Networks: A Deep Learning Approach , 2017, 2018 IEEE International Conference on Communications (ICC).

[202]  Suresh Subramaniam,et al.  Deadline-Aware Task Scheduling in a Tiered IoT Infrastructure , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

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

[204]  Pengfei Wang,et al.  Joint Task Assignment, Transmission, and Computing Resource Allocation in Multilayer Mobile Edge Computing Systems , 2019, IEEE Internet of Things Journal.

[205]  Khaled Ben Letaief,et al.  UAV-Assisted Wireless Powered Cooperative Mobile Edge Computing: Joint Offloading, CPU Control, and Trajectory Optimization , 2020, IEEE Internet of Things Journal.

[206]  Shang Gao,et al.  An End-to-End Load Balancer Based on Deep Learning for Vehicular Network Traffic Control , 2019, IEEE Internet of Things Journal.

[207]  Liang Liu,et al.  Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing , 2019, IEEE Transactions on Communications.

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

[209]  Chadi Assi,et al.  Dynamic Task Offloading and Scheduling for Low-Latency IoT Services in Multi-Access Edge Computing , 2019, IEEE Journal on Selected Areas in Communications.

[210]  Katinka Wolter,et al.  An Efficient Application Partitioning Algorithm in Mobile Environments , 2019, IEEE Transactions on Parallel and Distributed Systems.

[211]  Xumin Huang,et al.  Optimal Task Assignment With Delay Constraint for Parked Vehicle Assisted Edge Computing: A Stackelberg Game Approach , 2020, IEEE Communications Letters.

[212]  P. Wan,et al.  Near-Optimal and Truthful Online Auction for Computation Offloading in Green Edge-Computing Systems , 2020, IEEE Transactions on Mobile Computing.

[213]  Weiwei Xia,et al.  Joint Computation Offloading and Resource Allocation Optimization in Heterogeneous Networks With Mobile Edge Computing , 2018, IEEE Access.

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

[215]  Gueyoung Jung,et al.  FocusStack: Orchestrating Edge Clouds Using Location-Based Focus of Attention , 2016, 2016 IEEE/ACM Symposium on Edge Computing (SEC).

[216]  Qi Zhang,et al.  Offloading Schemes in Mobile Edge Computing for Ultra-Reliable Low Latency Communications , 2018, IEEE Access.

[217]  Weisong Shi,et al.  EdgeOS_H: A Home Operating System for Internet of Everything , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[218]  Haoyu Wang,et al.  HealthEdge: Task scheduling for edge computing with health emergency and human behavior consideration in smart homes , 2017, 2017 IEEE International Conference on Big Data (Big Data).

[219]  Qi Zhang,et al.  Code-Partitioning Offloading Schemes in Mobile Edge Computing for Augmented Reality , 2019, IEEE Access.

[220]  Marimuthu Palaniswami,et al.  An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments , 2021, IEEE Transactions on Mobile Computing.

[221]  Kezhi Wang,et al.  Energy Efficient Resource Allocation in UAV-Enabled Mobile Edge Computing Networks , 2019, IEEE Transactions on Wireless Communications.

[222]  Xin Wang,et al.  Computation offloading for mobile edge computing: A deep learning approach , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[223]  Pan Zhou,et al.  Collaborative Service Placement for Edge Computing in Dense Small Cell Networks , 2019, IEEE Transactions on Mobile Computing.

[224]  Yang Yang,et al.  Task Offloading and Resources Allocation based on Fairness in Edge Computing , 2019, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

[225]  Nirwan Ansari,et al.  Hierarchical Capacity Provisioning for Fog Computing , 2018, IEEE/ACM Transactions on Networking.

[226]  Bo Gu,et al.  Task Offloading in Vehicular Mobile Edge Computing: A Matching-Theoretic Framework , 2019, IEEE Vehicular Technology Magazine.

[227]  Tian Zhang,et al.  Data Offloading in Mobile Edge Computing: A Coalition and Pricing Based Approach , 2018, IEEE Access.

[228]  Roberto Morabito,et al.  Virtualization on Internet of Things Edge Devices With Container Technologies: A Performance Evaluation , 2017, IEEE Access.

[229]  Hossein Badri,et al.  Energy-Aware Application Placement in Mobile Edge Computing: A Stochastic Optimization Approach , 2020, IEEE Transactions on Parallel and Distributed Systems.

[230]  Yuezhi Zhou,et al.  A Truthful Online Mechanism for Collaborative Computation Offloading in Mobile Edge Computing , 2020, IEEE Transactions on Industrial Informatics.

[231]  Peng Liu,et al.  Low-Cost Video Transcoding at the Wireless Edge , 2016, 2016 IEEE/ACM Symposium on Edge Computing (SEC).

[232]  Jie Wu,et al.  Big Data Reduction for a Smart City’s Critical Infrastructural Health Monitoring , 2018, IEEE Communications Magazine.

[233]  Chunming Qiao,et al.  Offloading Tasks With Dependency and Service Caching in Mobile Edge Computing , 2021, IEEE Transactions on Parallel and Distributed Systems.

[234]  Yanning Zhang,et al.  Task Offloading in Vehicular Edge Computing Networks: A Load-Balancing Solution , 2020, IEEE Transactions on Vehicular Technology.

[235]  George Mastorakis,et al.  EXEGESIS: Extreme Edge Resource Harvesting for a Virtualized Fog Environment , 2017, IEEE Communications Magazine.

[236]  Wei Li,et al.  A Dynamic Service Migration Mechanism in Edge Cognitive Computing , 2018, ACM Trans. Internet Techn..

[237]  Walid Saad,et al.  Matching theory for future wireless networks: fundamentals and applications , 2014, IEEE Communications Magazine.

[238]  Paramvir Bahl,et al.  VideoEdge: Processing Camera Streams using Hierarchical Clusters , 2018, 2018 IEEE/ACM Symposium on Edge Computing (SEC).

[239]  Youlong Luo,et al.  Dynamic multi-user computation offloading for wireless powered mobile edge computing , 2019, J. Netw. Comput. Appl..

[240]  Zhiwei Zhao,et al.  Multi-User Offloading for Edge Computing Networks: A Dependency-Aware and Latency-Optimal Approach , 2020, IEEE Internet of Things Journal.

[241]  Kin K. Leung,et al.  Online Placement of Multi-Component Applications in Edge Computing Environments , 2016, IEEE Access.

[242]  Ying Wang,et al.  Multivessel Computation Offloading in Maritime Mobile Edge Computing Network , 2019, IEEE Internet of Things Journal.

[243]  Zdenek Becvar,et al.  Dynamic resource allocation exploiting mobility prediction in mobile edge computing , 2016, 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[244]  Wenxiao Shi,et al.  Share-Based Edge Computing Paradigm With Mobile-to-Wired Offloading Computing , 2019, IEEE Communications Letters.

[245]  Hui Tian,et al.  Selective Offloading in Mobile Edge Computing for the Green Internet of Things , 2018, IEEE Network.

[246]  Yuanyuan Yang,et al.  Efficient and Secure Multi-User Multi-Task Computation Offloading for Mobile-Edge Computing in Mobile IoT Networks , 2020, IEEE Transactions on Network and Service Management.

[247]  Chuan Pham,et al.  A proximal algorithm for joint resource allocation and minimizing carbon footprint in geo-distributed fog computing , 2014, 2015 International Conference on Information Networking (ICOIN).

[248]  Jiacheng Chen,et al.  Dynamic Task Offloading and Resource Allocation for Mobile-Edge Computing in Dense Cloud RAN , 2020, IEEE Internet of Things Journal.

[249]  Xuyun Zhang,et al.  A computation offloading method over big data for IoT-enabled cloud-edge computing , 2019, Future Gener. Comput. Syst..

[250]  Xiangjie Kong,et al.  A Cooperative Partial Computation Offloading Scheme for Mobile Edge Computing Enabled Internet of Things , 2019, IEEE Internet of Things Journal.

[251]  Rongke Liu,et al.  Space-Air-Ground IoT Network and Related Key Technologies , 2020, IEEE Wireless Communications.

[252]  Gunasekaran Manogaran,et al.  Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System , 2019, Sensors.

[253]  Adel Nadjaran Toosi,et al.  Serverless Edge Computing: Vision and Challenges , 2021, ACSW.

[254]  Xianghan Zheng,et al.  Resource Allocation for Cloud-Based Software Services Using Prediction-Enabled Feedback Control With Reinforcement Learning , 2022, IEEE Transactions on Cloud Computing.

[255]  Jie Xu,et al.  Mobile Edge Computing for Cellular-Connected UAV: Computation Offloading and Trajectory Optimization , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[256]  M. Herbster,et al.  Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[257]  Qin Zhang,et al.  Edge Computing in IoT-Based Manufacturing , 2018, IEEE Communications Magazine.

[258]  Shangguang Wang,et al.  An Energy-Aware Edge Server Placement Algorithm in Mobile Edge Computing , 2018, 2018 IEEE International Conference on Edge Computing (EDGE).

[259]  Adeeb Noor,et al.  Agent-enabled task offloading in UAV-aided mobile edge computing , 2020, Comput. Commun..

[260]  Thar Baker,et al.  A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing , 2019, IEEE Access.

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

[262]  Xuyun Zhang,et al.  An edge computing-enabled computation offloading method with privacy preservation for internet of connected vehicles , 2019, Future Gener. Comput. Syst..

[263]  Yong Wang,et al.  A Bilevel Optimization Approach for Joint Offloading Decision and Resource Allocation in Cooperative Mobile Edge Computing , 2020, IEEE Transactions on Cybernetics.

[264]  Xing Chen,et al.  Effective data placement for scientific workflows in mobile edge computing using genetic particle swarm optimization , 2019, Concurr. Comput. Pract. Exp..

[265]  Vincent K. N. Lau,et al.  Closed-Form Delay-Optimal Computation Offloading in Mobile Edge Computing Systems , 2019, IEEE Transactions on Wireless Communications.

[266]  Long Bao Le,et al.  Computation Offloading in MIMO Based Mobile Edge Computing Systems under Perfect and Imperfect CSI Estimation , 2018, 2018 IEEE International Conference on Communications (ICC).

[267]  Ting Han,et al.  Energy-efficient task offloading, load balancing, and resource allocation in mobile edge computing enabled IoT networks , 2018, Science China Information Sciences.

[268]  Fei Wang,et al.  Dynamic interface-selection and resource allocation over heterogeneous mobile edge-computing wireless networks with energy harvesting , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[269]  Felix Wortmann,et al.  Internet of Things , 2015, Business & Information Systems Engineering.

[270]  Lei Gao,et al.  Application specific data replication for edge services , 2003, WWW '03.

[271]  Blesson Varghese,et al.  Resource Management in Fog/Edge Computing , 2018, ACM Comput. Surv..

[272]  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.

[273]  Shuguang Cui,et al.  Optimal Energy Allocation and Task Offloading Policy for Wireless Powered Mobile Edge Computing Systems , 2019, IEEE Transactions on Wireless Communications.

[274]  Xu Zhou,et al.  A Code-Oriented Partitioning Computation Offloading Strategy for Multiple Users and Multiple Mobile Edge Computing Servers , 2020, IEEE Transactions on Industrial Informatics.

[275]  Zibin Zheng,et al.  Online Deep Reinforcement Learning for Computation Offloading in Blockchain-Empowered Mobile Edge Computing , 2019, IEEE Transactions on Vehicular Technology.

[276]  Pengfei Wang,et al.  HetMEC: Latency-Optimal Task Assignment and Resource Allocation for Heterogeneous Multi-Layer Mobile Edge Computing , 2019, IEEE Transactions on Wireless Communications.

[277]  Fuhui Zhou,et al.  Computation-Efficient Offloading and Trajectory Scheduling for Multi-UAV Assisted Mobile Edge Computing , 2020, IEEE Transactions on Vehicular Technology.

[278]  Geyong Min,et al.  Computation Offloading in Multi-Access Edge Computing Using a Deep Sequential Model Based on Reinforcement Learning , 2019, IEEE Communications Magazine.

[279]  Sanghyun Ahn,et al.  Scalable Service Placement in the Fog Computing Environment for the IoT-Based Smart City , 2019, J. Inf. Process. Syst..

[280]  Xu Chen,et al.  Follow Me at the Edge: Mobility-Aware Dynamic Service Placement for Mobile Edge Computing , 2018, 2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS).

[281]  Alagan Anpalagan,et al.  Joint Multi-User Computation Offloading and Data Caching for Hybrid Mobile Cloud/Edge Computing , 2019, IEEE Transactions on Vehicular Technology.

[282]  Yang Yang,et al.  A Heuristic Algorithm Based on Resource Requirements Forecasting for Server Placement in Edge Computing , 2018, 2018 IEEE/ACM Symposium on Edge Computing (SEC).

[283]  Yu Wang,et al.  Cloudlet Placement and Task Allocation in Mobile Edge Computing , 2019, IEEE Internet of Things Journal.

[284]  Yuanyuan Yang,et al.  Resource Allocation and Consensus of Blockchains in Pervasive Edge Computing Environments , 2021, IEEE Transactions on Mobile Computing.

[285]  Jun Zhang,et al.  Stochastic Joint Radio and Computational Resource Management for Multi-User Mobile-Edge Computing Systems , 2017, IEEE Transactions on Wireless Communications.

[286]  Xiaoli Chu,et al.  Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee , 2018, IEEE Transactions on Communications.

[287]  Sheyda Zarandi,et al.  Joint Resource Allocation and Offloading Decision in Mobile Edge Computing , 2019, IEEE Communications Letters.

[288]  Dusit Niyato,et al.  Hierarchical Game-Theoretic and Reinforcement Learning Framework for Computational Offloading in UAV-Enabled Mobile Edge Computing Networks With Multiple Service Providers , 2019, IEEE Internet of Things Journal.

[289]  Min Chen,et al.  Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network , 2018, IEEE Journal on Selected Areas in Communications.

[290]  Zhu Han,et al.  Computation Offloading With Data Caching Enhancement for Mobile Edge Computing , 2018, IEEE Transactions on Vehicular Technology.

[291]  Ali Kashif Bashir,et al.  Context-Aware Task Offloading for Multi-Access Edge Computing: Matching with Externalities , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).