1. Asymptotic optimality of power-of-d load balancing in large-scale systems
- Author
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Debankur Mukherjee, Sem Borst, Philip Whiting, Johan S. H. van Leeuwaarden, Research Group: Operations Research, Econometrics and Operations Research, and Stochastic Operations Research
- Subjects
Mathematical optimization ,Scale (ratio) ,General Mathematics ,power-of-d scheme ,load balancing ,02 engineering and technology ,Management Science and Operations Research ,join the shortest queue ,diffussion limit ,FOS: Mathematics ,0202 electrical engineering, electronic engineering, information engineering ,Diffusion limit ,many-server asymptotics ,fluid limit ,Mathematics ,020203 distributed computing ,Fluid limit ,stochastic coupling ,Probability (math.PR) ,020206 networking & telecommunications ,Load balancing (computing) ,Computer Science Applications ,Power (physics) ,Computer Science::Performance ,functional limit theorems ,Mathematics - Probability - Abstract
We consider a system of $N$ identical server pools and a single dispatcher where tasks arrive as a Poisson process of rate $\lambda(N)$. Arriving tasks cannot be queued, and must immediately be assigned to one of the server pools to start execution, or discarded. The execution times are assumed to be exponentially distributed with unit mean, and do not depend on the number of other tasks receiving service. However, the experienced performance (e.g. in terms of received throughput) does degrade with an increasing number of concurrent tasks at the same server pool. The dispatcher therefore aims to evenly distribute the tasks across the various server pools. Specifically, when a task arrives, the dispatcher assigns it to the server pool with the minimum number of tasks among $d(N)$ randomly selected server pools. This assignment strategy is called the JSQ$(d(N))$ scheme, as it resembles the power-of-$d$ version of the Join-the-Shortest-Queue (JSQ) policy, and will also be referred to as such in the special case $d(N) = N$. We construct a stochastic coupling to bound the difference in the system occupancy processes between the JSQ policy and a scheme with an arbitrary value of $d(N)$. We use the coupling to derive the fluid limit in case $d(N) \to \infty$ and $\lambda(N)/N \to \lambda$ as $N \to \infty$, along with the associated fixed point. The fluid limit turns out to be insensitive to the exact growth rate of $d(N)$, and coincides with that for the JSQ policy. We further leverage the coupling to establish that the diffusion limit corresponds to that for the JSQ policy as well, as long as $d(N)/\sqrt{N} \log(N) \to \infty$, and characterize the common limiting diffusion process. These results indicate that the JSQ optimality can be preserved at the fluid-level and diffusion-level while reducing the overhead by nearly a factor O($N$) and O($\sqrt{N}/\log(N)$), respectively., Comment: 48 pages, 3 figures, companion paper of arXiv:1612.00723
- Published
- 2020