Optimal routing into two heterogeneous service stations with delayed information

Artiges, Damien

doi:10.1109/cdc.1993.325693

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…In [24], along with the single server flow control problem with similar results as [23], they also showed that when k = 1, the optimal policy for minimizing the discounted number of jobs in a system of two parallel queues is join-theshortest-expected-length. In [25], the decision-making agent at time n, knows the number of jobs that were present in each (infinite) queue at time n-1, such that it takes decisions at a deterministic delay of one time slot. The state space at any time n is augmented and contains the actual queue filling at time n-1, the action taken at time n and if there was an arrival at time n.…”

Section: Related Workmentioning

confidence: 99%

Load Balancing in Compute Clusters With Delayed Feedback

Tahir

Alt

Rizk

et al. 2023

IEEE Trans. Comput.

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Load balancing arises as a fundamental problem, underlying the dimensioning and operation of many computing and communication systems, such as job routing in data center clusters, multipath communication, Big Data and queueing systems. In essence, the decision-making agent maps each arriving job to one of the possibly heterogeneous servers while aiming at an optimization goal such as load balancing, low average delay or low loss rate. One main difficulty in finding optimal load balancing policies here is that the agent only partially observes the impact of its decisions, e.g., through the delayed acknowledgements of the served jobs. In this paper, we provide a partially observable (PO) model that captures the load balancing decisions in parallel buffered systems under limited information of delayed acknowledgements. We present a simulation model for this PO system to find a load balancing policy in real-time using a scalable Monte Carlo tree search algorithm. We numerically show that the resulting policy outperforms other limited information load balancing strategies such as variants of Join-the-Most-Observations and has comparable performance to full information strategies like: Join-the-Shortest-Queue, Join-the-Shortest-Queue(d) and Shortest-Expected-Delay. Finally, we show that our approach can optimise the real-time parallel processing by using network data provided by Kaggle.

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Section: Related Workmentioning

confidence: 99%

Load Balancing in Compute Clusters With Delayed Feedback

Tahir

Alt

Rizk

et al. 2023

IEEE Trans. Comput.

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“…In [18], along with the single server flow control problem with similar results as [17], they also showed that when k = 1, the optimal policy for minimizing the discounted number of jobs in a system of two parallel queues is join-the-shortest-expected-length. In [19], the scheduler at time n knows the number of jobs that were present in each (infinite) queue at time n-1, such that it takes decisions at a deterministic delay of one time slot. The state space at any time n is augmented and contains the actual queue filling at time n-1, the action taken at time n and if there was an arrival at time n.…”

Section: Related Workmentioning

confidence: 99%

Scheduling in Parallel Finite Buffer Systems: Optimal Decisions under Delayed Feedback

Tahir¹,

Alt²,

Rizk³

et al. 2021

Preprint

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Scheduling decisions in parallel queuing systems arise as a fundamental problem, underlying the dimensioning and operation of many computing and communication systems, such as job routing in data center clusters, multipath communication, and Big Data systems. In essence, the scheduler maps each arriving job to one of the possibly heterogeneous servers while aiming at an optimization goal such as load balancing, low average delay or low loss rate. One main difficulty in finding optimal scheduling decisions here is that the scheduler only partially observes the impact of its decisions, e.g., through the delayed acknowledgements of the served jobs. In this paper, we provide a partially observable (PO) model that captures the scheduling decisions in parallel queuing systems under limited information of delayed acknowledgements. We present a simulation model for this PO system to find a near-optimal scheduling policy in real-time using a scalable Monte Carlo tree search algorithm. We numerically show that the resulting policy outperforms other limited information scheduling strategies such as variants of Join-the-Most-Observations and has comparable performance to full information strategies like: Join-the-Shortest-Queue, Join-the-Shortest-Queue(d) and Shortest-Expected-Delay. Finally, we show how our approach can optimise the real-time parallel processing by using network data provided by Kaggle.

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“…A problem of optimal priority assignment for access to a single channel with delay has been investigated in . Routing with delayed information has been investigated in Artiges (1995), Kuri and Kumar (1992) and Litvak and Yechiali (2001).…”

Section: Related Workmentioning

confidence: 99%

Admission and routing control with partial information and limited buffers

Altman

Márquez

Yechiali

2003

International Journal of Systems Science

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Problems of admission and routing control for loss systems comprised of a controller and C down-stream servers are studied. We focus on problems in which control actions have to be taken with either delayed or with no information on the state of the downstream servers. We first consider a problem of routing into C servers and compare the performance of two policies: a static round-robin policy, which does not wait for the delayed information at a risk of losing customers at the busy servers, and a Wait policy, that avoids losses at the servers but risks losses at the controller buffer. We identify regions in which each of the policies performs better. We then study the problem with no information on down-stream servers and propose a timer mechanism to decide when to dispatch an arriving customer. We optimize the value of the timer's parameter. Our study is accompanied with numerical investigations.

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Optimal routing into two heterogeneous service stations with delayed information

Cited by 4 publications

References 11 publications

Load Balancing in Compute Clusters With Delayed Feedback

Load Balancing in Compute Clusters With Delayed Feedback

Scheduling in Parallel Finite Buffer Systems: Optimal Decisions under Delayed Feedback

Admission and routing control with partial information and limited buffers

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