5G Data Offloading Using Fuzzification with Grasshopper Optimization Technique

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