Computing Offloading Strategy in Mobile Edge Computing Environment: A Comparison between Adopted Frameworks, Challenges, and Future Directions
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[1] L. Ismail,et al. HealthEdge: A Machine Learning-Based Smart Healthcare Framework for Prediction of Type 2 Diabetes in an Integrated IoT, Edge, and Cloud Computing System , 2023, ANT/EDI40.
[2] IoT Based Control Networks and Intelligent Systems , 2023, Lecture Notes in Networks and Systems.
[3] Keping Yu,et al. DRL-Based Partial Offloading for Maximizing Sum Computation Rate of Wireless Powered Mobile Edge Computing Network , 2022, IEEE Transactions on Wireless Communications.
[4] J. McArthur,et al. B-SMART: A Reference Architecture for Autonomic Smart Buildings. , 2022, IOP Conference Series: Earth and Environmental Science.
[5] Deze Zeng,et al. Stackelberg-Game-Based Computation Offloading Method in Cloud–Edge Computing Networks , 2022, IEEE Internet of Things Journal.
[6] Daisy Nkele Molokomme,et al. Edge Intelligence in Smart Grids: A Survey on Architectures, Offloading Models, Cyber Security Measures, and Challenges , 2022, J. Sens. Actuator Networks.
[7] Kuan-Ching Li,et al. Multiobjective Optimization for Joint Task Offloading, Power Assignment, and Resource Allocation in Mobile Edge Computing , 2022, IEEE Internet of Things Journal.
[8] J. Shuja,et al. Computation Offloading in Mobile Cloud Computing and Mobile Edge Computing: Survey, Taxonomy, and Open Issues , 2022, Mobile Information Systems.
[9] Lisha Hu,et al. Game-Theory-Based Task Offloading and Resource Scheduling in Cloud-Edge Collaborative Systems , 2022, Applied Sciences.
[10] Yan Zhang,et al. Joint Power Control and Computation Offloading for Energy-Efficient Mobile Edge Networks , 2022, IEEE Transactions on Wireless Communications.
[11] Weifa Liang,et al. Maximizing User Service Satisfaction for Delay-Sensitive IoT Applications in Edge Computing , 2022, IEEE Transactions on Parallel and Distributed Systems.
[12] Jorge Arthur Schneider Aranda,et al. Context-aware Edge Computing and Internet of Things in Smart Grids: A systematic mapping study , 2022, Comput. Electr. Eng..
[13] M. Ergen,et al. Mobility-Aware Offloading Decision for Multi-Access Edge Computing in 5G Networks , 2022, Sensors.
[14] Fei Xu,et al. Research on computing offloading strategy based on Genetic Ant Colony fusion algorithm , 2022, Simul. Model. Pract. Theory.
[15] K. Wolter,et al. Energy-Efficient Offloading for DNN-Based Smart IoT Systems in Cloud-Edge Environments , 2022, IEEE Transactions on Parallel and Distributed Systems.
[16] R. Hu,et al. Energy Efficiency and Delay Tradeoff in an MEC-Enabled Mobile IoT Network , 2022, IEEE Internet of Things Journal.
[17] Mohsen Guizani,et al. Privacy-Aware Collaborative Task Offloading in Fog Computing , 2022, IEEE Transactions on Computational Social Systems.
[18] Mohammad Hossein Rezvani,et al. Partial offloading with stable equilibrium in fog-cloud environments using replicator dynamics of evolutionary game theory , 2022, Clust. Comput..
[19] Chengsheng Pan,et al. Profit Maximization Incentive Mechanism for Resource Providers in Mobile Edge Computing , 2022, IEEE Transactions on Services Computing.
[20] Sajal K. Das,et al. An Efficient Online Computation Offloading Approach for Large-Scale Mobile Edge Computing via Deep Reinforcement Learning , 2021, IEEE Transactions on Services Computing.
[21] Handi Chen,et al. Joint Optimization of Task Offloading and Resource Allocation Based on Differential Privacy in Vehicular Edge Computing , 2021, IEEE Transactions on Computational Social Systems.
[22] Li Qing,et al. QoS Driven Task Offloading With Statistical Guarantee in Mobile Edge Computing , 2020, IEEE Transactions on Mobile Computing.
[23] Kezhi Wang,et al. Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-Assisted Mobile Edge Computing , 2019, IEEE Transactions on Mobile Computing.
[24] Fuliang Li,et al. RLbR: A reinforcement learning based V2V routing framework for offloading 5G cellular IoT , 2022, IET Commun..
[25] Sung-Uk Jung,et al. Strategy for Creating AR Applications in Static and Dynamic Environments Using SLAM- and Marker Detector-Based Tracking , 2022, Computer Modeling in Engineering & Sciences.
[26] A. Vladyko,et al. Distributed Edge Computing with Blockchain Technology to Enable Ultra -Reliable Low-Latency v2x Communications , 2021 .
[27] Danfeng Yan,et al. Deep reinforcement learning-based computation offloading for 5G vehicle-aware multi-access edge computing network , 2021, China Communications.
[28] Daniele Tarchi,et al. Multi-Objective Computation Sharing in Energy and Delay Constrained Mobile Edge Computing Environments , 2021, IEEE Transactions on Mobile Computing.
[29] Wei Huang,et al. Collaborative Cloud-Edge-End Task Offloading in Mobile-Edge Computing Networks With Limited Communication Capability , 2021, IEEE Transactions on Cognitive Communications and Networking.
[30] Wen Chen,et al. Enhancing Mobile Edge Computing with Efficient Load Balancing Using Load Estimation in Ultra-Dense Network , 2021, Sensors.
[31] Dimitrios P. Pezaros,et al. Data quality-aware task offloading in Mobile Edge Computing: An Optimal Stopping Theory approach , 2021, Future Gener. Comput. Syst..
[32] Shuchen Zhou,et al. Jointly Optimizing Offloading Decision and Bandwidth Allocation with Energy Constraint in Mobile Edge Computing Environment , 2021, Computing.
[33] Xiaofeng Wang,et al. A High Reliable Computing Offloading Strategy Using Deep Reinforcement Learning for IoVs in Edge Computing , 2021, Journal of Grid Computing.
[34] Harvinder Singh,et al. QRAS: efficient resource allocation for task scheduling in cloud computing , 2021, SN Applied Sciences.
[35] S. Sasikala,et al. RETRACTED ARTICLE: Multi-parameter optimization for load balancing with effective task scheduling and resource sharing , 2021, Journal of Ambient Intelligence and Humanized Computing.
[36] Huansheng Ning,et al. A Novel Framework for Mobile-Edge Computing by Optimizing Task Offloading , 2021, IEEE Internet of Things Journal.
[37] Md Zakirul Alam Bhuiyan,et al. Trust-Aware Service Offloading for Video Surveillance in Edge Computing Enabled Internet of Vehicles , 2021, IEEE Transactions on Intelligent Transportation Systems.
[38] Jiamei Shi,et al. An Efficient Computation Offloading Strategy with Mobile Edge Computing for IoT , 2021, Micromachines.
[39] Adel Nadjaran Toosi,et al. Serverless Edge Computing: Vision and Challenges , 2021, ACSW.
[40] Zheng Chang,et al. Dynamic Resource Allocation and Computation Offloading for IoT Fog Computing System , 2020, IEEE Transactions on Industrial Informatics.
[41] Junaid Shuja,et al. Machine Learning-Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks , 2021, Complex..
[42] Xiaolong Li,et al. Privacy-Enhanced Data Collection Based on Deep Learning for Internet of Vehicles , 2020, IEEE Transactions on Industrial Informatics.
[43] Waqas Jadoon,et al. The partial computation offloading strategy based on game theory for multi-user in mobile edge computing environment , 2020, Comput. Networks.
[44] Anfeng Liu,et al. A Unified Trustworthy Environment Establishment Based on Edge Computing in Industrial IoT , 2020, IEEE Transactions on Industrial Informatics.
[45] Mostafa Ghobaei-Arani,et al. A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective , 2020, Comput. Networks.
[46] Symeon Papavassiliou,et al. Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach , 2020, Sensors.
[47] Zhongfeng Wang,et al. Offloading Optimization for Low-Latency Secure Mobile Edge Computing Systems , 2020, IEEE Wireless Communications Letters.
[48] Zhiguo Shi,et al. Latency Optimization for Cellular Assisted Mobile Edge Computing via Non-Orthogonal Multiple Access , 2020, IEEE Transactions on Vehicular Technology.
[49] Xiaoming Tao,et al. Latency Minimization for D2D-Enabled Partial Computation Offloading in Mobile Edge Computing , 2020, IEEE Transactions on Vehicular Technology.
[50] Songlin Chen,et al. Multiuser Physical Layer Authentication in Internet of Things With Data Augmentation , 2020, IEEE Internet of Things Journal.
[51] Hao Luo,et al. MTES: An Intelligent Trust Evaluation Scheme in Sensor-Cloud-Enabled Industrial Internet of Things , 2020, IEEE Transactions on Industrial Informatics.
[52] Haojun Huang,et al. P3: Privacy-Preserving Scheme Against Poisoning Attacks in Mobile-Edge Computing , 2020, IEEE Transactions on Computational Social Systems.
[53] Qinglin Zhao,et al. Dependency-Aware Task Scheduling in Vehicular Edge Computing , 2020, IEEE Internet of Things Journal.
[54] Guojun Wang,et al. Edge-based differential privacy computing for sensor-cloud systems , 2020, J. Parallel Distributed Comput..
[55] Arun Kumar Sangaiah,et al. Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud , 2020, IEEE Transactions on Industrial Informatics.
[56] Shaoyong Guo,et al. Joint Computation Offloading and URLLC Resource Allocation for Collaborative MEC Assisted Cellular-V2X Networks , 2020, IEEE Access.
[57] Michael Stonebraker,et al. Pattern functional dependencies for data cleaning , 2020, Proc. VLDB Endow..
[58] Albert Y. Zomaya,et al. Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence , 2019, IEEE Internet of Things Journal.
[59] Long Hu,et al. Privacy-aware service placement for mobile edge computing via federated learning , 2019, Inf. Sci..
[60] 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.
[61] Xin Yao,et al. Parallel Offloading in Green and Sustainable Mobile Edge Computing for Delay-Constrained IoT System , 2019, IEEE Transactions on Vehicular Technology.
[62] Zhi Zhou,et al. Online Orchestration of Cross-Edge Service Function Chaining for Cost-Efficient Edge Computing , 2019, IEEE Journal on Selected Areas in Communications.
[63] Alireza Souri,et al. Multiobjective virtual machine placement mechanisms using nature‐inspired metaheuristic algorithms in cloud environments: A comprehensive review , 2019, Int. J. Commun. Syst..
[64] Zibin Zheng,et al. Online Deep Reinforcement Learning for Computation Offloading in Blockchain-Empowered Mobile Edge Computing , 2019, IEEE Transactions on Vehicular Technology.
[65] Xiong Li,et al. Privacy Preserving Data Aggregation Scheme for Mobile Edge Computing Assisted IoT Applications , 2019, IEEE Internet of Things Journal.
[66] Josep Domingo-Ferrer,et al. Privacy-preserving cloud computing on sensitive data: A survey of methods, products and challenges , 2019, Comput. Commun..
[67] R. N. Uma,et al. Optimal Joint Scheduling and Cloud Offloading for Mobile Applications , 2019, IEEE Transactions on Cloud Computing.
[68] Pan Hui,et al. Dandelion: A Unified Code Offloading System for Wearable Computing , 2019, IEEE Transactions on Mobile Computing.
[69] Yuan Wu,et al. Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing , 2019, Digit. Commun. Networks.
[70] Zhangdui Zhong,et al. Joint Job Partitioning and Collaborative Computation Offloading for Internet of Things , 2019, IEEE Internet of Things Journal.
[71] F. Richard Yu,et al. Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues and Challenges , 2019, IEEE Communications Surveys & Tutorials.
[72] Parmeet Kaur,et al. Efficient computation offloading using grey wolf optimization algorithm , 2019 .
[73] Xu Chen,et al. In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning , 2018, IEEE Network.
[74] Dario Pompili,et al. Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks , 2017, IEEE Transactions on Vehicular Technology.
[75] Hong Wen,et al. Security Enhancement for Mobile Edge Computing Through Physical Layer Authentication , 2019, IEEE Access.
[76] Rui L. Aguiar,et al. Network Functions Virtualization: The Long Road to Commercial Deployments , 2019, IEEE Access.
[77] Giancarlo Fortino,et al. Autonomic computation offloading in mobile edge for IoT applications , 2019, Future Gener. Comput. Syst..
[78] Jianghua Feng,et al. Comparative analysis of variable flux reluctance machines with double- and single-layer concentrated armature windings , 2019, 2018 Thirteenth International Conference on Ecological Vehicles and Renewable Energies (EVER).
[79] Haibin Zhang,et al. Double Auction-Based Resource Allocation for Mobile Edge Computing in Industrial Internet of Things , 2018, IEEE Transactions on Industrial Informatics.
[80] Huan Zhou,et al. V2V Data Offloading for Cellular Network Based on the Software Defined Network (SDN) Inside Mobile Edge Computing (MEC) Architecture , 2018, IEEE Access.
[81] Vinod Vokkarane,et al. A New Deep Learning-Based Food Recognition System for Dietary Assessment on An Edge Computing Service Infrastructure , 2018, IEEE Transactions on Services Computing.
[82] Anfeng Liu,et al. A Three-Layer Privacy Preserving Cloud Storage Scheme Based on Computational Intelligence in Fog Computing , 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.
[83] Joonhyuk Kang,et al. Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning , 2016, IEEE Transactions on Vehicular Technology.
[84] Zhigang Wen,et al. Joint Offloading and Computing Design in Wireless Powered Mobile-Edge Computing Systems With Full-Duplex Relaying , 2018, IEEE Access.
[85] Russell J. Clark,et al. Advancing Software-Defined Networks: A Survey , 2017, IEEE Access.
[86] Ilsun You,et al. Computational Offloading for Efficient Trust Management in Pervasive Online Social Networks Using Osmotic Computing , 2017, IEEE Access.
[87] Nirwan Ansari,et al. Toward Hierarchical Mobile Edge Computing: An Auction-Based Profit Maximization Approach , 2016, IEEE Internet of Things Journal.
[88] Dario Sabella,et al. Mobile-Edge Computing Architecture: The role of MEC in the Internet of Things , 2016, IEEE Consumer Electronics Magazine.
[89] Wenzhong Li,et al. Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing , 2015, IEEE/ACM Transactions on Networking.
[90] Jeongho Kwak,et al. DREAM: Dynamic Resource and Task Allocation for Energy Minimization in Mobile Cloud Systems , 2015, IEEE Journal on Selected Areas in Communications.
[91] Athanasios V. Vasilakos,et al. Information centric network: Research challenges and opportunities , 2015, J. Netw. Comput. Appl..
[92] Sergio Barbarossa,et al. Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing , 2014, IEEE Transactions on Signal and Information Processing over Networks.
[93] Bharat K. Bhargava,et al. A Survey of Computation Offloading for Mobile Systems , 2012, Mobile Networks and Applications.