Ant Colony Optimization in Cloud for Load Balancing

Mayuri R. Popalghat; Sonali S. Pandhare; Shweta U. Shinde; Sukanya S. Pathak

doi:10.37591/rtpc.v1i1.63

Abstract

There is an increase in the demand of cloud these days, as more and more people are looking for virtual storage of data rather than investing in physical storage. Cloud has many advantages like it focuses on maximizing the effectiveness of the shared resources. Cloud resources are shared by multiple users and these resources are dynamically allocated as per the demand. One of the major issues faced by cloud computing these days are that, demands for resources are continuously increasing as well as are irregularly distributed. To overcome this, it is very essential that there is a proper load distribution. In our paper, we propose Ant Colony Optimization algorithm for implementing load balancing amongst nodes. This is a modified algorithm over the existing ones as in this method, the ants continuously update a single global result set, whereas in the previous ones, each ant had their own result set. Here we use the concept of foraging and trailing pheromones. This helps to create an efficient result set which helps in load balancing.Keywords: Ant colony optimization; load balancing; cloud computing; foraging and trailing pheromones.