Quasi Oppositional Dragonfly Algorithm for Load Balancing in Cloud Computing Environment

In cloud computing (CC), load balancing tasks remain a critical problem in distributing resources from data center. Ensure that every virtual machine (VM) has balanced to maximize capacity utilization. the CC world, is Non-Polynomial (NP) resolved with metaheuristic algorithms. A new Quasi-Oppositional Dragonfly Algorithm for Load Balancing (QODA-LB) been developed obtain optimum resource scheduling configuration. The proposed QODA-LB algorithm uses three variables calculate an objective function: execution time, cost, and charge. assigns VM according its potential resulting function. Also, employs Based Learning principle increase standard convergence rate of (DA) algorithm. complete series experiments were conducted, results analyzed various ways ensure increased efficiency Simulation demonstrated optimal outperformed key approaches.