Fuzzy Based Collaborative Task Offloading Scheme in the Densely Deployed Small-Cell Networks with Multi-Access Edge Computing

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

[2]  Abdul Hanan Abdullah,et al.  A Secure Trust Model Based on Fuzzy Logic in Vehicular Ad Hoc Networks With Fog Computing , 2017, IEEE Access.

[3]  Lazim Abdullah,et al.  Fuzzy Multi Criteria Decision Making and its Applications: A Brief Review of Category , 2013 .

[4]  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).

[5]  Dario Pompili,et al.  Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks , 2017, IEEE Transactions on Vehicular Technology.

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

[7]  V. Vidhya,et al.  Performance Measures of State Dependent MMPP/M/1 Queue , 2018, International Journal of Engineering & Technology.

[8]  Lingyang Song,et al.  Load Balancing for 5G Ultra-Dense Networks Using Device-to-Device Communications , 2018, IEEE Transactions on Wireless Communications.

[9]  Haibin Zhang,et al.  When Smart Wearables Meet Intelligent Vehicles: Challenges and Future Directions , 2017, IEEE Wireless Communications.

[10]  U. OmKumarC.,et al.  Fuzzy based energy efficient workload management system for flash crowd , 2019, Comput. Commun..

[11]  Amr M. Youssef,et al.  Ultra-Dense Networks: A Survey , 2016, IEEE Communications Surveys & Tutorials.

[12]  Arun Kumar Sangaiah,et al.  A Hesitant Fuzzy Based Security Approach for Fog and Mobile-Edge Computing , 2018, IEEE Access.

[13]  Zhaona Wang,et al.  Eardrum‐Inspired Active Sensors for Self‐Powered Cardiovascular System Characterization and Throat‐Attached Anti‐Interference Voice Recognition , 2015, Advanced materials.

[14]  Jung-Tae Lee,et al.  Multi-Access Edge Computing Empowered Heterogeneous Networks: A Novel Architecture and Potential Works , 2019, Symmetry.

[15]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[16]  Yu Song,et al.  Wearable and Implantable Electronics: Moving toward Precision Therapy. , 2019, ACS nano.

[17]  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.

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

[19]  Zhong Lin Wang,et al.  Triboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring. , 2017, ACS nano.

[20]  Atay Ozgovde,et al.  Fuzzy Workload Orchestration for Edge Computing , 2019, IEEE Transactions on Network and Service Management.

[21]  Der-Jiunn Deng,et al.  Wireless Big Data Computing in Smart Grid , 2017, IEEE Wireless Communications.

[22]  Delowar Hossain,et al.  Efficient Computation Offloading in Multi-Tier Multi-Access Edge Computing Systems: A Particle Swarm Optimization Approach , 2019 .

[23]  Marcos Jesus dos Santos,et al.  Cloud Computing management using Fuzzy Logic , 2015 .

[24]  Min Chen,et al.  Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies , 2015, Mob. Networks Appl..

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

[26]  Linda Doyle,et al.  Effect of LOS/NLOS propagation on 5G ultra-dense networks , 2017, Comput. Networks.

[27]  Wenzhong Li,et al.  Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing , 2015, IEEE/ACM Transactions on Networking.

[28]  Jie Xu,et al.  EMM: Energy-Aware Mobility Management for Mobile Edge Computing in Ultra Dense Networks , 2017, IEEE Journal on Selected Areas in Communications.

[29]  Rajkumar Buyya,et al.  A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing , 2013, IEEE Communications Surveys & Tutorials.

[30]  G. Zhu,et al.  Membrane‐Based Self‐Powered Triboelectric Sensors for Pressure Change Detection and Its Uses in Security Surveillance and Healthcare Monitoring , 2014 .

[31]  Schahram Dustdar,et al.  Mobile web augmented reality in 5G and beyond: Challenges, opportunities, and future directions , 2019, China Communications.

[32]  Nannan Zhang,et al.  Progress in triboelectric nanogenerators as self-powered smart sensors , 2017 .

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

[34]  Jie Zhang,et al.  Mobile-Edge Computation Offloading for Ultradense IoT Networks , 2018, IEEE Internet of Things Journal.

[35]  Xuemin Shen,et al.  Energy-Sustainable Traffic Steering for 5G Mobile Networks , 2017, IEEE Communications Magazine.

[36]  J. Mendel Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

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

[38]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

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

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

[41]  Li Fu,et al.  A Novel Fuzzy Approach for Combining Uncertain Conflict Evidences in the Dempster-Shafer Theory , 2019, IEEE Access.

[42]  Hongda Chen,et al.  Point-of-care testing based on smartphone: The current state-of-the-art (2017-2018). , 2019, Biosensors & bioelectronics.

[43]  Tarik Taleb,et al.  "Anything as a Service" for 5G Mobile Systems , 2016, IEEE Network.