A Predictive, Decentralized Load Balancing Approach

Abstract

The growth of load balancing system raises the issue of scalability, and decentralized load balancing architecture has been proposed to address this issue. In this paper, we investigate how a load balancing architecture can be built on decentralized policies based on CORBA and enhanced by predictive algorithm. The L/sub 2/E predictive filtering model was used to supply workstations with robust cluster load information, which allows them to make more accurate independent allocation decisions. Experimental results showed that our decentralized load balancing approach was able to suppress thrashing and oscillations compared to other load monitoring and prediction techniques, and it was able to achieve a highly balanced system than Sun Grid Engine.