Admission Control for Elastic Cloud Services

Konstanteli, Kleopatra; Cucinotta, Tommaso; Psychas, Konstantinos; Varvarigou, Theodora

doi:10.1109/cloud.2012.63

Cited by 44 publications

(34 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The availability of resources and admission control is also discussed in [131]. The work uses a probabilistic approach to find an optimized allocation of services on virtualized physical resources.…”

Section: Infrastructure-provider Admission Controlmentioning

confidence: 99%

Quality-of-service in cloud computing: modeling techniques and their applications

Ardagna

Casale

Ciavotta

et al. 2014

J Internet Serv Appl

212

View full text Add to dashboard Cite

Recent years have seen the massive migration of enterprise applications to the cloud. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocating resources to the application to guarantee a service level along dimensions such as performance, availability and reliability. This paper aims at supporting research in this area by providing a survey of the state of the art of QoS modeling approaches suitable for cloud systems. We also review and classify their early application to some decision-making problems arising in cloud QoS management.

show abstract

Section: Infrastructure-provider Admission Controlmentioning

confidence: 99%

Quality-of-service in cloud computing: modeling techniques and their applications

Ardagna

Casale

Ciavotta

et al. 2014

J Internet Serv Appl

212

View full text Add to dashboard Cite

show abstract

“…However, admission control within cloud environments is not trivial due to different reasons, specially the elastic nature of services and uncertainty about future needs/behaviors. Among recent approaches to this multi-faceted problem, Konstanteli et al [27] present a probabilistic method for a combined scheduling and admission control problem formulated using mixed-integer non-linear programming. They model the elastic service demand by using cumulative distribution functions.…”

Section: Admission Controlmentioning

confidence: 99%

An Autonomic Approach to Risk-Aware Data Center Overbooking

Tomás

Tordsson

2014

IEEE Trans. Cloud Comput.

View full text Add to dashboard Cite

Abstract-Elasticity is a key characteristic of cloud computing that increases the flexibility for cloud consumers, allowing them to adapt the amount of physical resources associated to their services over time in an on-demand basis. However, elasticity creates problems for cloud providers as it may lead to poor resource utilization, specially in combination with other factors, such as user overestimations and pre-defined VM sizes. Admission control mechanisms are thus needed to increase the number of services accepted, raising the utilization without affecting services performance. This work focuses on implementing an autonomic risk-aware overbooking architecture capable of increasing the resource utilization of cloud data centers by accepting more virtual machines than physical available resources. Fuzzy logic functions are used to estimate the associated risk to each overbooking decision. By using a distributed PID controller approach, the system is capable of self-adapting over time -changing the acceptable level of risk -depending on the current status of the cloud data center. The suggested approach is extensively evaluated using a combination of simulations and experiments executing real cloud applications with real-life available workloads. Our results show a 50% increment at both resource utilization and capacity allocated with acceptable performance degradation and more stable resource utilization over time.

show abstract

“…Konstanteli et al take a probabilistic approach to a combined scheduling and admission control problem formulated using mixed-integer non-linear programming [17]. In their work, the elastic service demand is modeled using cumulative distribution functions.…”

Section: Related Workmentioning

confidence: 99%

Cloudy with a Chance of Load Spikes: Admission Control with Fuzzy Risk Assessments

Tomás

Tordsson

2013

2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing

View full text Add to dashboard Cite

Abstract-Elasticity is key for the cloud paradigm, where the pay-per use nature provides great flexibility for end-users. However, elasticity complicates long-term capacity planning for cloud providers as the exact amount of resources required over time becomes uncertain. Admission control techniques are thus needed to handle the trade-off between resource utilization and potential overload. We define a set of admission control algorithms that combine risk assessment methods with a fuzzy aggregation framework. An experimental evaluation using a mixture of bursty and steady applications demonstrate that our algorithms can increase resource utilization by a factor of two while limiting overload problems to a few percent.

show abstract

Admission Control for Elastic Cloud Services

Cited by 44 publications

References 16 publications

Quality-of-service in cloud computing: modeling techniques and their applications

Quality-of-service in cloud computing: modeling techniques and their applications

An Autonomic Approach to Risk-Aware Data Center Overbooking

Cloudy with a Chance of Load Spikes: Admission Control with Fuzzy Risk Assessments

Contact Info

Product

Resources

About