Multi-objective cloud load-balancing with hybrid optimization

Abstract

In this study, the cloud computing platform is equipped with a hybrid multi-objective meta-heuristic optimization-based load balancing model. Physical Machine (PM) allocates a specific virtual machine (VM) depending on multiple criteria, such as the amount of memory used, migration expenses, power usage, and the load balancing settings, upon receiving a request to handle a cloud user's duties (‘Response time, Turnaround time, and Server load’). Additionally, the optimal virtual machine (VM) is chosen for efficient load balancing by utilizing the recently proposed hybrid optimization approach. The Cat and Mouse-Based Optimizer (CMBO) and Standard Dingo Optimizer (DXO) are conceptually blended together to get the proposed hybridization method known as Dingo Customized Cat mouse Optimization (DCCO). The developed method achieves the lowest server load in cloud environment 1 is 33.3%, 40%, 42.3%, 40.2%, 36.8%, 42.5%, 50%, 40.2%, 39.2% improved over MOA, ABC, CSO, SSO, SSA, ACSO, SMO, CMBO, BOA, DOX, and FF-PSO, respectively. Finally, the projected DCCO model has been evaluated in terms of makespan, memory usage, migration cost, response time, usage of power server load, turnaround time, throughput, and convergence. ABBREVIATION: CDC, cloud data center; CMODLB, Clustering-based Multiple Objective Dynamic Load Balancing As A Load Balancing; CSP, Cloud service providers; CSSA, Chaotic Squirrel Search Algorithm; DA, Dragonfly Algorithm; ED, Euclidean Distance; EDA-GA, Estimation Of Distribution Algorithm And GA; FF, FireFly algorithm; GA, Genetic Algorithm; HHO, Harris Hawk Optimization; IaaS, Infrastructure-as-a-Service; MGWO, Modified Mean Grey Wolf Optimization Algorithm; MMHHO, Mantaray modified multi-objective Harris Hawk optimization; MRFO, Manta Ray Forging Optimization; PaaS, Platform-as-a-Service; PM, Physical Machine; PSO, Particle Swarm Optimization; SaaS, Software-as-a-Service; SAW, Sample additive weighting; SLA-LB, Service Level Agreement-Based Load Balancing; TBTS, Threshold-Based Task Scheduling Algorithm; TS, Task Scheduling