5G Data Offloading Using Fuzzification with Grasshopper Optimization Technique

作     者：V.R.Balaji T.Kalavathi J.Vellingiri N.Rajkumar Venkat Prasad Padhy 

作者机构：Department of ECESri Krishna College of Engineering and TechnologyCoimbatore641008India Department of EIEKongu Engineering CollegeErode638060India School of Information Technology and EngineeringVellore Institute of TechnologyVellore632014India Department of CSESchool of EngineeringPresidency UniversityBangalore560064India School of Computing Science and EngineeringVIT Bhopal UniversityBhopal466114India 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2022年第42卷第7期

页      面：289-301页

核心收录：

学科分类：0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0713[理学-生态学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The authors received no specific funding for this study. 

主　　题：5G energy consumption task offloading fuzzification grasshopper optimization QoS mobile IoT 

摘      要：Data offloading at the network with less time and reduced energy con-sumption are highly important for every technology.Smart applications process the data very quickly with less power consumption.As technology grows towards 5G communication architecture,identifying a solution for QoS in 5G through energy-efficient computing is important.In this proposed model,we perform data offloading at 5G using the fuzzification concept.Mobile IoT devices create tasks in the network and are offloaded in the cloud or mobile edge nodes based on energy consumption.Two base stations,small(SB)and macro(MB)stations,are initialized and thefirst tasks randomly computed.Then,the tasks are pro-cessed using a fuzzification algorithm to select SB or MB in the central server.The optimization is performed using a grasshopper algorithm for improving the QoS of the 5G network.The result is compared with existing algorithms and indi-cates that the proposed system improves the performance of the system with a cost of 44.64 J for computing 250 benchmark tasks.