Analysis of Load Balancing in Large Heterogeneous Processor Sharing Systems

We analyze randomized dynamic load balancing schemes for multi-server processor sharing systems when the number of servers in the system is large and the servers have heterogeneous service rates. In particular, we focus on the classical power-of-two load balancing scheme and a variant of it in which a newly arrived job is assigned to the server having the least instantaneous Lagrange shadow cost among two randomly chosen servers. The instantaneous Lagrange shadow cost at a server is given by the ratio of the number of unfinished jobs at the server to the capacity of the server. Two different approaches of analysis are presented for each scheme. For exponential job length distribution, the analysis is done using the mean field approach and for more general job length distributions the analysis is carried out assuming an asymptotic independence property. Analytical expressions to compute mean sojourn time of jobs are found for both schemes. Asymptotic insensitivity of the schemes to the type of job length distribution is established. Numerical results are presented to validate the theoretical results and to show that, unlike the homogeneous scenario, the power-of-two type schemes considered in this paper may not always result in better behaviour in terms of the mean sojourn time of jobs.