Multiple ant-bee colony optimization for load balancing in packet-switched networks

TL;DR

This paper introduces a novel multi colony ant-bee swarm intelligence algorithm to improve load balancing in packet-switched networks by efficiently finding multiple routes between source and destination.

Contribution

It proposes an enhanced MACO algorithm utilizing multiple colonies of ants and bees as intelligent agents for better network load balancing.

Findings

Improved routing efficiency demonstrated in simulations.

Tangible performance improvements over existing MACO algorithms.

Enhanced load distribution in network simulations.

Abstract

One of the important issues in computer networks is "Load Balancing" which leads to efficient use of the network resources. To achieve a balanced network it is necessary to find different routes between the source and destination. In the current paper we propose a new approach to find different routes using swarm intelligence techniques and multi colony algorithms. In the proposed algorithm that is an improved version of MACO algorithm, we use different colonies of ants and bees and appoint these colony members as intelligent agents to monitor the network and update the routing information. The survey includes comparison and critiques of MACO. The simulation results show a tangible improvement in the aforementioned approach.