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20172022
most citedExploiting Data Locality to Improve Performance of Heterogeneous Server Clusters

3 citations · 3 across the 3 of their papers we have counts for

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math.PR20223 cited

Exploiting Data Locality to Improve Performance of Heterogeneous Server Clusters

Zhisheng Zhao, Debankur Mukherjee, Ruoyu Wu

We consider load balancing in large-scale heterogeneous server systems in the presence of data locality that imposes constraints on which tasks can be assigned to which servers. Th…

math.PR2020

Load Balancing Under Strict Compatibility Constraints

Daan Rutten, Debankur Mukherjee

We study large-scale systems operating under the JSQ policy in the presence of stringent task-server compatibility constraints. Consider a system with identical single-ser…

math.PR2018

Scalable Load Balancing Algorithms in Networked Systems

Debankur Mukherjee

A fundamental challenge in large-scale networked systems viz., data centers and cloud networks is to distribute tasks to a pool of servers, using minimal instantaneous state inform…

math.PR2018

Join-the-Shortest Queue Diffusion Limit in Halfin-Whitt Regime: Sensitivity on the Heavy-traffic Parameter

Sayan Banerjee, Debankur Mukherjee

Consider a system of parallel single-server queues with unit-exponential service time distribution and a single dispatcher where tasks arrive as a Poisson process of rate $λ(N)…

math.PR2018

Join-Idle-Queue with Service Elasticity: Large-Scale Asymptotics of a Non-monotone System

Debankur Mukherjee, Alexander Stolyar

We consider the model of a token-based joint auto-scaling and load balancing strategy, proposed in a recent paper by Mukherjee, Dhara, Borst, and van Leeuwaarden (SIGMETRICS '17, a…

math.PR2018

Large deviations analysis for the queue in the Halfin-Whitt regime

David A. Goldberg, Debankur Mukherjee, Yuan Li

We consider the FCFS queue in the Halfin-Whitt heavy traffic regime. It is known that the normalized sequence of steady-state queue length distributions is tight and…