Abstract
Motivated by applications to wireless networks, cloud computing, data centers, etc., stochastic processing networks have been studied in the literature under various asymptotic regimes. In the heavy traffic regime, the steady-state mean queue length is proved to be Θ(1/ϵ), where ϵ is the heavy traffic parameter (which goes to zero in the limit). The focus of this paper is on obtaining queue length bounds on pre-limit systems, thus establishing the rate of convergence to heavy traffic. For the generalized switch, operating under the MaxWeight algorithm, we show that the mean queue length is within O(log(1/ϵ)) of its heavy traffic limit. This result holds regardless of the complete resource pooling (CRP) condition being satisfied. Furthermore, when the CRP condition is satisfied, we show that the mean queue length under the MaxWeight algorithm is within O(log(1/ϵ)) of the optimal scheduling policy. Finally, we obtain similar results for the rate of convergence to heavy traffic of the total queue length in load balancing systems operating under the 'join the shortest queue' routeing algorithm.
Original language | English (US) |
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Pages (from-to) | 652-669 |
Number of pages | 18 |
Journal | Journal of Applied Probability |
Volume | 59 |
Issue number | 3 |
DOIs | |
State | Published - Sep 21 2022 |
Funding
This work was partially supported by the National Science Foundation grants CCF-1850439 and EPCN-2144316. Daniela Hurtado-Lange has partial funding from the Chilean National Agency for Research and Development ANID/DOCTORADO BECAS CHILE/2018-72190413.
Keywords
- Drift method
- MaxWeight
- generalized switch
- load balancing
- state space collapse
ASJC Scopus subject areas
- Statistics and Probability
- General Mathematics
- Statistics, Probability and Uncertainty