An Intuitionistic Fuzzy Decision Intelligence Framework for Multi Objective SLA Aware and Energy Efficient Virtual Machine Migration in Federated Cloud Systems
TL;DR
IF-FLAME (Intuitionistic Fuzzy Firefly Lion Advanced Migration using Exploration and Exploitation) is found as a maintainable, SLA-compliant, and energy-aware migration model for federated clouds.
Abstract
The intelligible Virtual Machine (VM) migration in federated cloud systems is important for achieving energy conservation, workload balancing and Service Level Agreement (SLA) compliance. Traditional heuristics and hybrid metaheuristics though effective fail to address qualms and hesitation in workload assessment, leading to needless migrations and SLA violations. To these limitations this study makes known to IF-FLAME (Intuitionistic Fuzzy Firefly Lion Advanced Migration using Exploration and Exploitation) an improved hybrid optimization framework that fit in intuitionistic fuzzy logic with Firefly and Lion metaheuristics. Different conservative fuzzy systems the intuitionistic fuzzy model books for truth, falsity and hesitation degrees in task prioritization, safeguarding more robust migration results under hesitation. Experimental assessment in CloudSim demonstrates that IF-FLAME attains significant developments over F-FLAME as well as abridged SLA violation rate (from 90% to 8%), minimalized migration energy cost, better quality throughput, and better deadline adherence. These consequences found IF-FLAME as a maintainable, SLA-compliant, and energy-aware migration model for federated clouds.