Load balancing in cloud computing environment based on an improved particle swarm optimization

Abstract

The next-generation of cloud computing will thrive on how effectively the infrastructure are instantiated and available resources are utilized dynamically. Load balancing, which is one of the main challenges in Cloud computing, distributes the dynamic workload across multiple nodes to ensure that no single resource is either overwhelmed or underutilized. An improved particle algorithm is proposed to achieve resource load balancing optimization in the cloud environment. This mechanism takes the characteristics of complex networks into consideration to establish a corresponding resource-task allocation model. The simulated experiments showed that this model can improve the load balancing and resource utilization in the cloud.