Comparison of scheduling schemes for on-demand IaaS requests

Do, Tien Van; Rotter, Csaba

doi:10.1016/j.jss.2012.01.019

Cited by 25 publications

(11 citation statements)

References 12 publications

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“…Do et al works in paper [22] proved that several scheduling algorithm had assisted various resource allocation scheme to be implemented for the infrastructure provider. The impact of scheduling implemented in [8] creates a scenario when a very small process will have to wait for its turn to utilize the CPU.…”

Section: A Resource Allocationmentioning

confidence: 99%

“…In paper [22] states that several scheduling algorithms with different allocation strategy may produce a saving on the energy consumption in the operational kind but with condition whereby on-demand requests do not face the unpleasant blocking probability. As a result study for power consumption will contribute to energy efficiency and cost savings.…”

Section: Related Work In Resource Managementmentioning

confidence: 99%

“…The prediction is based on power calculation module which depicts the power consumption for every component in a data center such as servers (and its component), power module, storage and others in a private cloud. Thus, the prediction model can be improved and enhanced in public cloud which encompasses more heterogeneous components and will benefit the intercloud service provider and the consumer as well.In paper [22] states that several scheduling algorithms with different allocation strategy may produce a saving on the energy consumption in the operational kind but with condition whereby on-demand requests do not face the unpleasant blocking probability. As a result study for power consumption will contribute to energy efficiency and cost savings.…”

mentioning

confidence: 99%

“…However, this solution is based on the current allocation whereby the features of dynamic workload may be different and changes rapidly. Yet, the proposed method proved to be very fast in order to adapt the change, and rapid allocation of the needed resources.Do et al works in paper [22] proved that several scheduling algorithm had assisted various resource allocation scheme to be implemented for the infrastructure provider. The impact of scheduling implemented in [8] creates a scenario when a very small process will have to wait for its turn to utilize the CPU.…”

mentioning

confidence: 99%

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A Survey on Resource Allocation and Monitoring in Cloud Computing

Mohamaddiah¹,

Abdullah²,

Subramaniam³

et al. 2014

IJMLC

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Abstract-The cloud provider plays a major role especially providing resources such as computing power for the cloud subscriber to deploy their applications on multiple platforms anywhere; anytime. Hence the cloud users still having problem for resource management in receiving the guaranteed computing resources on time. This will impact the service time and the service level agreements for various users in multiple applications. Therefore there is a need for a new resolution to resolve this problem. This survey paper conducts a study in resource allocation and monitoring in the cloud computing environment. We describe cloud computing and its properties, research issues in resource management mainly in resource allocation and monitoring and finally solutions approach for resource allocation and monitoring. It is believed that this paper would benefit both cloud users and researchers for further knowledge on resource management in cloud computing.Index Terms-Resource allocation, resource monitoring, cloud computing, resource management. I. INTRODUCTIONCloud Computing, a service model was introduced to provide computing resources such as computing power, storage and bandwidth to deliver the IT services to the organization. This service model is rapidly being adopted by many organizations because it offers lots of business opportunity especially in terms of financial investment and human capital. With cloud services, the organization may opt out to set up a data center for its IT infrastructure or to procure hardware and software for its business applications as they can lease the resources from the cloud service provider. Initial providers in cloud computing such as Amazon EC2 [1], Google Apps Engine [2] , Microsoft Azure [3], SalesForce.com [4] offers great business value to the interested organizations who want to subscribe the services with a concept pay-per-use, on-demand and a defined Service level agreements (SLAs). For example, Google Apps Engine offers monthly uptime percentage: 99.00% -< 99.95% for client for its covered services. For the downtime period, they offer a period of five consecutive minutes of downtime. This value is an attractive package for the client, because they manage to control the usage of resources and demands more, faster and reliable infrastructure. Manuscript received October 11, 2013; revised December 7, 2013 On the other hand, the resources on the cloud are pooled in order to serve multiple subscribers. The provider use multi-tenancy model where the resources (physical and virtual) are reassigned dynamically based on the tenant requirement [5]. The assigning of the resources will be based on the lease and SLA agreement, whereby different clients will need more or less amount of virtual resources. Subsequently, the growth of demands for cloud services is bringing more challenge for the provider to provide the resources to the client subscriber. Therefore, in this paper we provide a review on cloud computing which focus on resource management: allocation and monitoring. Our methodolo...

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Section: A Resource Allocationmentioning

confidence: 99%

Section: Related Work In Resource Managementmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Survey on Resource Allocation and Monitoring in Cloud Computing

Mohamaddiah¹,

Abdullah²,

Subramaniam³

et al. 2014

IJMLC

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“…An analytical model for interaction aspects between on-demand request and allocation of virtual machine from the infrastructure owner to the user has been proposed by [18]. Comparison and numerical analysis of several scheduling algorithm has been performed considering the blocking probability of on demand request.…”

Section: B Study On Performance Toolsmentioning

confidence: 99%

Study of Response Time in Cloud Computing

Singh¹

2014

IJIEEB

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Abstract-Performance of a cloud is a critical issue and dependent on various factors that include load balancing used to distribute the load at data center. Proliferation of the cloud paradigm is profoundly dependent on the performance of the cloud. Therefore, to examine the cloud performance, it is significant to identify the factors that govern cloud performance. This work is focused to identify the factors that may have significant impact on the cloud performance. To identify the performance factors, we have reviewed the major publications of the last five years as well as the major real time cloud performance tools offered. Study revealed that response time is the major factor that has the significant impact on cloud computing performance. Finally, we have conducted an experiment to establish the dependency of response time on various load balancing techniques and number of data center. Experiment revealed that the round robin is directly proportional to the number of data center

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