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pro vyhledávání: '"Hong, Yige"'
We consider the infinite-horizon average-reward restless bandit problem. We propose a novel \emph{two-set policy} that maintains two dynamic subsets of arms: one subset of arms has a nearly optimal state distribution and takes actions according to an
Externí odkaz:
http://arxiv.org/abs/2405.17882
In many important real-world queueing settings, arrival and service rates fluctuate over time. We consider the MAMS system, where the arrival and service rates each vary according to an arbitrary finite-state Markov chain, allowing intermittent overl
Externí odkaz:
http://arxiv.org/abs/2405.04102
We consider the infinite-horizon, average-reward restless bandit problem in discrete time. We propose a new class of policies that are designed to drive a progressively larger subset of arms toward the optimal distribution. We show that our policies
Externí odkaz:
http://arxiv.org/abs/2402.05689
Multiserver-job (MSJ) systems, where jobs need to run concurrently across many servers, are increasingly common in practice. The default service ordering in many settings is First-Come First-Served (FCFS) service. Virtually all theoretical work on MS
Externí odkaz:
http://arxiv.org/abs/2310.01621
We study the infinite-horizon restless bandit problem with the average reward criterion, in both discrete-time and continuous-time settings. A fundamental goal is to efficiently compute policies that achieve a diminishing optimality gap as the number
Externí odkaz:
http://arxiv.org/abs/2306.00196
Autor:
Hong, Yige, Scully, Ziv
Publikováno v:
Performance Evaluation 163 (2024), 102377
How should we schedule jobs to minimize mean queue length? In the preemptive M/G/1 queue, we know the optimal policy is the Gittins policy, which uses any available information about jobs' remaining service times to dynamically prioritize jobs. For m
Externí odkaz:
http://arxiv.org/abs/2304.13231
In modern computing systems, jobs' resource requirements often vary over time. Accounting for this temporal variability during job scheduling is essential for meeting performance goals. However, theoretical understanding on how to schedule jobs with
Externí odkaz:
http://arxiv.org/abs/2209.04123
Autor:
Hong, Yige, Wang, Weina
Multiserver jobs, which are jobs that occupy multiple servers simultaneously during service, are prevalent in today's computing clusters. But little is known about the delay performance of systems with multiserver jobs. We consider queueing models fo
Externí odkaz:
http://arxiv.org/abs/2109.05343
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