A Hybrid Population-Based Incremental Learning algorithm for load balancing in RPR

Abstract

When managed properly, the ring networks are uniquely suited to deliver a large amount of bandwidth in a reliable and inexpensive way. An optimal load balancing is very important, because it increases the system capacity and improves the overall ring performance. An important optimisation problem in this context is the Weighted Ring Arc Loading Problem (WRALP). It consists of the design, in a communication network of a transmission route (direct path) for each request, such that high load on the ring arcs will be avoided. WRALP asks for a routing scheme such that the maximum load on the ring arcs will be minimum. In this paper we study WRALP without demand splitting and we propose a Hybrid Population-based Incremental Learning (HPBIL) to solve it. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.