Energy‐efficient sender‐initiated threshold‐based load balancing (e‐STLB) in cloud computing environment

Abstract

SummaryCloud computing has transformed service delivery through its pay‐per‐use model, supporting diverse users with multiple heterogeneous Virtual Machines (VMs). However, energy consumption has emerged as a critical concern, necessitating cloud resource optimization for environment‐friendly practices. This research paper presents an innovative energy‐efficient threshold‐based sender‐initiated load‐balancing strategy (e‐STLB) to address this concern. The approach employs threshold values to trigger task migration between VMs, ensuring optimal performance while maximizing energy efficiency. The proposed strategy significantly reduces Makespan and increases Resource Utilization in an energy‐conscious manner. Experimental evaluations using Cloudsim 3.0 demonstrate that the e‐STLB outperforms other state‐of‐the‐art solutions, offering a compelling approach to sustainable cloud computing.

Systematic Review: Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms

“…The scalability and efficiency of the load balancing techniques in large-scale cloud deployments are critically significant considerations to ensure optimal resource utilization. Scalability considerations involve efficient management incoming requests from multiple data centers, intelligent decisionmaking capability while considering the real-time information of resources, ability to deal with a sudden spike in traffic, and auto-adjust server instances based on the incoming user requests [12,13]. While efficiency considerations entail preventing server overutilization or underutilization, continuously monitoring server health, tracking failed nodes, migrating resources, ensuring high availability for critical applications [14], minimizing overhead, and simplifying algorithm complexity.…”