Modified Honey Bee Algorithm with Random Selection of Virtual Machines for Dynamic Load Balancing

Cloud workloads can overwhelm load balancers, leading to inefficiencies and performance issues. To address these challenges, the Honey Bee Load Balancing algorithm is highly effective in enhancing cloud resource allocation. Inspired by the foraging behavior of honey bees, this algorithm offers a dynamic approach to resource distribution, adapting to changing workloads in real-time. This paper delves into the key features and advantages of Honey Bee Load Balancing, focusing on its dynamic resource allocation, overall response time, and data center processing time. Through a comparative study of existing methodologies, we propose a modified Honey Bee Load Balancing algorithm that incorporates the random selection of virtual machines. Utilizing the CloudAnalyst tool for simulation, we compare traditional and proposed Honey Bee Load Balancing algorithms to evaluate overall response time and data center processing time. The proposed algorithm demonstrates superior performance in these parameters compared to the traditional approach.