SLA-based resource allocation in cluster computing systems

Xiong, Ke; Perros, Harry G.

doi:10.1109/ipdps.2008.4536272

Cited by 19 publications

(8 citation statements)

References 24 publications

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“…Xiong et al focused on SLA-based resource allocation in Cluster computing systems, where QoS metrics considered are response time, Cluster utilization, packet loss rate and Cluster availability [24]. We consider different QoS parameters (i.e., budget, deadline, and penalty rate), admission control and resource allocation, and multiple IaaS providers.…”

Section: Schedulingmentioning

confidence: 99%

SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments

Garg

Buyya

2012

Journal of Computer and System Sciences

190

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Software as a Service (SaaS) provides access to applications to end users over the Internet without upfront investment in infrastructure and software. To serve their customers, SaaS providers utilise resources of internal data centres or rent resources from a public Infrastructure as a Service (IaaS) provider. In-house hosting can increase administration and maintenance costs whereas renting from an IaaS provider can impact the service quality due to its variable performance. To overcome these limitations, we propose innovative admission control and scheduling algorithms for SaaS providers to effectively utilise public Cloud resources to maximize profit by minimizing cost and improving customer satisfaction level. Furthermore, we conduct an extensive evaluation study to analyse which solution suits best in which scenario to maximize SaaS provider's profit. Simulation results show that our proposed algorithms provide substantial improvement (up to 40% cost saving) over reference ones across all ranges of variation in QoS parameters.

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Section: Schedulingmentioning

confidence: 99%

SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments

Garg

Buyya

2012

Journal of Computer and System Sciences

190

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“…Thus, we are going to formulate the third problem of Section 1. As shown in Xiong and Perros [22], a percentile of the end-to-end delay can be quantified as a cumulative distribution function (CDF) of the end-to-end delay given by…”

Section: The Power-aware Resource Provisioning Problemsmentioning

confidence: 99%

“…Moreover, as discussed in Xiong and Perros [22], a customer is often inclined to request a statistical bound on its end-to-end delay than its average end-to-end delay. For instance, a customer can request that 95% of the time its endto-end delay should be less than a desired value.…”

Section: Introductionmentioning

confidence: 99%

“…Most of existing studies dealt with an average end-toend delay since a percentile of the end-to-end delay requires us to calculate a distribution of the end-to-end delay, which is not an easy task as shown in Xiong and Perros [22]. Optimizing static workload management based on an average delay and a mean miss rate has been studied for multi-cluster computing systems in He et al [11].…”

Section: Introductionmentioning

confidence: 99%

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Power-aware resource provisioning in cluster computing

Xiong

2010

2010 IEEE International Symposium on Parallel &Amp; Distributed Processing (IPDPS)

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The high power consumption of cluster computing infrastructures has become a major concern. It leads to the increased heat dissipation and decreased reliability of cluster servers. Power management becomes a critical issue in cluster computing. In this paper, we start with an analysis of the relationship between cluster performance and power consumption. We study both the problem of minimizing the average end-to-end delay with the constraint of average energy consumption and the problem of minimizing the average energy consumption of cluster service requests with the constraint of an average end-to-end delay for customer services. We propose novel approaches to solving these two problems. In an effort to maximize profits, a service provider only provides sufficient resources to ensure quality of services (QoS) but often avoid over provisioning to meet QoS defined in a service level agreement (SLA) which is a contract agreed between a customer and a service provider. We present an approach for optimizing SLA-based resource provisioning in cluster computing in that we minimize the total cost of cluster servers owned by a service provider while satisfying the requirements of both a percentile of the end-to-end delay and average energy consumption. Numerical experiments show that the proposed approach is efficient and accurate for the SLA-based resource provisioning problem in cluster computing.

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“…In Osterbo [4], the author proposed a dimensioning model of an access network using the bufferless Elrang loss model. Resource allocation in cluster computing has been studied for differentiated services in Xiong and Perros [5] and for multiple performance metrics in Xiong and Perros [6].…”

Section: Introductionmentioning

confidence: 99%

Bandwidth provisioning in ADSL access networks

Xiong¹,

Perros²,

Blake³

2009

Int J Network Mgmt

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SUMMARYWe consider an ADSL access network consisting of subscribers, digital subscriber line access multiplexers (DSLAMs), metro Ethernet switches and a broadband remote access aggregation server (BRAS). We obtain expressions for dimensioning the access network in the upstream direction. Specifi cally, we show that the bandwidth required at each DSLAM, metro Ethernet switch, and BRAS can be expressed as an exponential function of the subscribers in a log scale when the number of subscribers does not surpass a certain value. After this value, it grows linearly as a function of the subscribers.

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SLA-based resource allocation in cluster computing systems

Cited by 19 publications

References 24 publications

SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments

SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments

Power-aware resource provisioning in cluster computing

Bandwidth provisioning in ADSL access networks

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