PERFORMANCE ENHANCEMENT THROUGH COMMUNICATION OFFLOADING FOR ENERGY EFFICIENCY ON MOBILE CLOUD COMPUTATION

RECENTLY, THERE HAS BEEN AN ENORMOUS INCREASE IN MOBILE DATA USAGE WITH WIDESPREAD SMARTPHONE PROLIFERATION SIMILAR DEVICES AND THE GROWING POPULARITY OF VIDEO STREAMING SERVICES. CLOUD COMPUTING IS THE STRUCTURAL DESIGN IN WHICH VIRTUAL MACHINES, CLOUD SERVERS, HOSTS, AND TRADERS PARTICIPATE TO EXECUTE ANY JOB ON THE CLOUD. THE MIGRATION OF THE VIRTUAL MACHINE IS THE MAJOR PROBLEM THAT HAS BEEN EMPHASIZED DURING THIS SECTION. BECAUSE OF THE OVERHEAD OF VIRTUAL MACHINES, THE TASK'S EXECUTION TIME IS INCREASED. INFORMATION AND COMMUNICATION TECHNOLOGY HAVE EMERGED TREMENDOUSLY IN THE PAST FEW YEARS, MAINLY DUE TO THE INTRODUCTION OF SMARTPHONES. HOWEVER, LIKE ITS PREDECESSORS, THE NEW TECHNOLOGY CAME WITH ITS LIMITATIONS AS WELL. THE HANDHELD GADGETS WE CALL SMARTPHONES FACE SOME SEVERE CHALLENGES IN PERFORMANCE (COMPUTATION), STORAGE, AND ENERGY. FIRST, TWO CHALLENGES ARE SOMEHOW ELIMINATED BY THE INCREASE IN PROCESSING POWER AND IMPROVEMENT IN OPERATING SYSTEMS. ENERGY MANAGEMENT IS ONE OF THE MOST DEMANDING PROBLEMS IN SMARTPHONE. THIS RESEARCH AIMS TO TACKLE THE ISSUE BY USING THE CLOUD COMPUTING CONCEPT. THE PRIMARY FEATURE OF SMARTPHONE IS TO COMMUNICATE. THE LARGER THE COMMUNICATION IS, THE HIGHER WOULD BE THE ENERGY CONSUMPTION. IN THIS RESEARCH, WE PROPOSE A NOVEL APPROACH FOR OFFLOADING, AND THIS METHOD IS THE RIGHT SOLUTION TO RESOLVE THE ENERGY CONSUMPTION ISSUE FOR COMMUNICATION-INTENSIVE APPLICATIONS. TO DEMONSTRATE OUR PROPOSED METHOD'S EFFECTIVENESS, WE PERFORMED DIFFERENT ANALYSIS TESTS.

[1]  Khizar Abbas,et al.  An efficient SDN‐based LTE‐WiFi spectrum aggregation system for heterogeneous 5G networks , 2020, Trans. Emerg. Telecommun. Technol..

[2]  Sukhpal Singh Gill,et al.  EFFORT: Energy efficient framework for offload communication in mobile cloud computing , 2020, Softw. Pract. Exp..

[3]  Prince Waqas Khan,et al.  Energy Efficient Computation Offloading Mechanism in Multi-Server Mobile Edge Computing—An Integer Linear Optimization Approach , 2020, Electronics.

[4]  K. Win,et al.  Effectiveness of Internet-Based Electronic Technology Interventions on Breastfeeding Outcomes: Systematic Review , 2019, Journal of medical Internet research.

[5]  Prince Waqas Khan,et al.  IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning , 2020, Sensors.

[6]  Yi Sun,et al.  Energy-Efficient Decision Making for Mobile Cloud Offloading , 2020, IEEE Transactions on Cloud Computing.

[7]  Khizar Abbas,et al.  An LTE-WiFi Spectrum Aggregation System for 5G Network: A Testbed , 2020, 2020 International Conference on Information Networking (ICOIN).

[8]  Andrey Koucheryavy,et al.  Advanced Deep Learning-Based Computational Offloading for Multilevel Vehicular Edge-Cloud Computing Networks , 2020, IEEE Access.

[9]  T. Francis,et al.  A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing , 2018, International Journal of Electrical and Computer Engineering (IJECE).

[10]  Bhekisipho Twala,et al.  An adaptive Cuckoo search algorithm for optimisation , 2018, Applied Computing and Informatics.

[11]  Prince Waqas Khan,et al.  A Systematic Review of Cyber Security and Classification of Attacks in Networks , 2018 .

[12]  Mohammad Shojafar,et al.  Mobile Cloud Computing: Challenges and Future Research Directions , 2017, 2017 10th International Conference on Developments in eSystems Engineering (DeSE).

[13]  Alexandru Iosup,et al.  Mirror: A computation-offloading framework for sophisticated mobile games , 2017, 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM).

[14]  Bhaskar Prasad Rimal,et al.  Cloudlet Enhanced Fiber-Wireless Access Networks for Mobile-Edge Computing , 2017, IEEE Transactions on Wireless Communications.

[15]  Feng Xia,et al.  Cloudlet deployment in local wireless networks: Motivation, architectures, applications, and open challenges , 2016, J. Netw. Comput. Appl..

[16]  Feng Xia,et al.  Phone2Cloud: Exploiting computation offloading for energy saving on smartphones in mobile cloud computing , 2013, Information Systems Frontiers.

[17]  Narseo Vallina-Rodriguez,et al.  Energy Management Techniques in Modern Mobile Handsets , 2013, IEEE Communications Surveys & Tutorials.

[18]  Henri E. Bal,et al.  Energy Efficient Information Monitoring Applications on Smartphones through Communication Offloading , 2011, MobiCASE.

[19]  Byung-Gon Chun,et al.  CloneCloud: elastic execution between mobile device and cloud , 2011, EuroSys '11.

[20]  Alec Wolman,et al.  MAUI: making smartphones last longer with code offload , 2010, MobiSys '10.

[21]  Tharam S. Dillon,et al.  Cloud Computing: Issues and Challenges , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[22]  Arthur C. Sanderson,et al.  JADE: Adaptive Differential Evolution With Optional External Archive , 2009, IEEE Transactions on Evolutionary Computation.

[23]  Hiroshi Yokota,et al.  A proposal of DNS-based adaptive load balancing method for mirror server systems and its implementation , 2004, 18th International Conference on Advanced Information Networking and Applications, 2004. AINA 2004..