A comparison study of MABC, ACO, ABC and PSO load balancing algorithms
S. Shivani Reddy, B. Shravani, K. Sreeja, Madala Mourya · IET conference proceedings. · 2022
This paper shows a comparison study of dynamic load balancing algorithms using a CloudSim simulator. As we know technology is growing rapidly and every software requires some kind of information or data, and other resources as input, these resources might not be present locally. The resources are provided to various users using cloud computing and virtual data centres all over the world. Many organizations have migrated to cloud to provide their services on a global level, thus becoming cloud service providers. When they become global they receive huge number of requests from user all over the world and to handle those requests they need to manage their data bases efficiently and effectively. And here comes the concept of load balancing, which is used by these service providers. Load balancing comes under the NP-hard which is further regarded as optimization problem. Many researchers tried to propose load balancing algorithms based on different theories, logics, strategies and approaches. Aiming to minimize makespan time which in turn helps in reducing the overall response time, the paper provides detailed approach for a comparison study to determine the algorithm that best fits for our requirement. The algorithm improves the fitness function by minimizing the makespan time. The proposed comparison study compares modified algorithm with different algorithms already present and the results also show that the algorithm performs with lower response time in a decentralized environment with dynamic tasks.