ANT Algorithm for Load Balancing Problem in FTP Server

Abstract — The system describes a method of achieving load balancing in distributed networks. A network models a typical distribution of files between nodes; nodes carrying an excess of traffic can become congested, causing data to be lost. The network also supports behaviors modeled on the trail laying abilities of ants. The performance of the network is measured by the average no of hops taken to complete the file transfer. Scheduling onto the network is NP-complete, so there is no exact scheduling algorithm for all computing systems. The project aims at proposing an ant colony optimization (ACO) algorithm to schedule large-scale workflows of file with various QoS parameters. The objective of this algorithm is to find a optimal solution that meets all constraints and optimizes the time and space parameter. Based on the characteristics of workflow scheduling, we design new heuristics for the ACO approach and propose an adaptive scheme that allows artificial ants to select heuristics based on pheromone values. The project aims to find the shortest path between two nodes i.e. Client and server. We solve this problem by simulating the functioning of Ants. After searching for food when an ant returns back to its colony, chemical called pheromone is laid on path which evaporates over time and eventually, the trails along all other paths except the shortest route evaporates. This causes almost all ants to follow the current shortest path until another ant found an even shorter path than previously encountered path. Thus the ACO system gives the optimal result for file transfer routes than the other algorithms, while many features can be added to distributed system environment