Analysis and Autonomic Elasticity Control for Multi-Server Queues under Traffic Surges

Tadakamalla, Venkat; Menascé, Daniel A.

doi:10.1109/iccac.2017.16

Cited by 6 publications

References 24 publications

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On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study

Gosavi

2022

Oper Res Int J

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We consider the multi-server, single-channel queue, i.e., a G / G / k queue with k identical servers in parallel, under the first-come-first-served discipline in which the inter-arrival process is non-Poisson, the service time has any given distribution, and traffic is of medium intensity. Such queues are common in factories, airports, and hospitals, where the inter-arrival times and service times are typically not exponentially distributed, but rather have double-tapering distributions whose probability density functions taper on both sides, e.g., gamma, triangular etc. For these conditions, a new closed-form approximation based on only the mean and variance of the two inputs, the inter-arrival and service times, is presented. Determining distributions of inputs typically requires additional human effort in terms of histogram-fitting and running a goodness-of-fit test, which is avoided here. The new approximation is tested on a variety of scenarios and its performance is benchmarked against simulation. Further, the new approximation is also implemented on a ventilator case study from the recent COVID-19 pandemic to demonstrate its utility in optimizing server capacity. The approximation provides errors typically in the range 1–15% and 31% in the worst case. In systems where data change rapidly and decisions must be made quickly, this approximation will be particularly useful.

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On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study

Gosavi

2022

Oper Res Int J

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An Analytic Model of Traffic Surges for Multi-Server Queues in Cloud Environments

Tadakamalla¹,

Menascé

2018

2018 IEEE 11th International Conference on Cloud Computing (CLOUD)

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Model-Driven Elasticity Control for Multi-Server Queues under Traffic Surges in Cloud Environments

Tadakamalla¹,

Menascé

2018

2018 IEEE International Conference on Autonomic Computing (ICAC)

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Analysis and Autonomic Elasticity Control for Multi-Server Queues under Traffic Surges

Cited by 6 publications

References 24 publications

On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study

On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study

An Analytic Model of Traffic Surges for Multi-Server Queues in Cloud Environments

Model-Driven Elasticity Control for Multi-Server Queues under Traffic Surges in Cloud Environments

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