Resource provisioning for cloud computing

Hu, Ye Fa; Wong, J.W.; Iszlai, Gabriel; Litoiu, Marin

doi:10.1145/1723028.1723041

Cited by 117 publications

(67 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then the SP will run the cloud software in order to provision request resources via multiple services to the customers. The Service Provider offers economically efficient services using hardware resources provisioned by infrastructure providers and it can be directly accessed by end-users or orchestrated by other service providers [8]. This provisioning process is abstracted into virtual machines by using Virtualization technology.…”

Section: Overview Of Cloud Computingmentioning

confidence: 99%

“…For example, event of resources become over utilized or vice versa cannot be tolerated. The infrastructure and service provider have to meet the Service Level Agreement (SLA), where they have an ability to allocate resources for mix environment or application to the fulfill mix of SLA of applications or users [8].…”

Section: B Resource Provisioning and Monitoring Processmentioning

confidence: 99%

“…This scenario affect the performance of the system, especially when there is a delay during a situation of determining which process to be run by the processor and which will wait. One of the earliest researches used scheduling algorithm, where the first come first serve [8] method is applied, by determining the smallest number of servers required to meet the SLAs for shared allocation and dedicated allocation resources. Consequently, many of the researches embark on scheduling algorithm such as in [24] proposed an energyconscious scheduling algorithm, while in paper [20], [25], [26] use gang scheduling resource allocation, In paper [25] implemented multi-tiered resource scheduling allocation scheme using virtual clusters to develop a more efficient algorithm.…”

Section: International Journal Of Machine Learning and Computing Volmentioning

confidence: 99%

“…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. A short process located behind a long process will result in lowering the CPU utilization.…”

Section: International Journal Of Machine Learning and Computing Volmentioning

confidence: 99%

“…Their goal is to capitalize on the provider from tenants by making efficient use of their infrastructures. Possibly, by outsourcing partial workloads to partnering providers [8]. Then the SP will run the cloud software in order to provision request resources via multiple services to the customers.…”

mentioning

confidence: 99%

See 4 more Smart Citations

A Survey on Resource Allocation and Monitoring in Cloud Computing

Mohamaddiah¹,

Abdullah²,

Subramaniam³

et al. 2014

IJMLC

View full text Add to dashboard Cite

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...

show abstract

Section: Overview Of Cloud Computingmentioning

confidence: 99%

Section: B Resource Provisioning and Monitoring Processmentioning

confidence: 99%

Section: International Journal Of Machine Learning and Computing Volmentioning

confidence: 99%

Section: International Journal Of Machine Learning and Computing Volmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

A Survey on Resource Allocation and Monitoring in Cloud Computing

Mohamaddiah¹,

Abdullah²,

Subramaniam³

et al. 2014

IJMLC

View full text Add to dashboard Cite

show abstract

Open‐Source Cloud Software Solutions

Murugesan

Bojanova²

2016

Encyclopedia of Cloud Computing

View full text Add to dashboard Cite

Applying queue theory for modeling of cloud computing: A systematic review

Ghomi

Rahmani

Qader

2019

Concurrency and Computation

View full text Add to dashboard Cite

The cloud computing paradigm is an important service in the Internet for sharing and providing resources in a cost-efficient way. Modeling of a cloud system is not an easy task because of the complexity and large scale of such systems. Cloud reliability could be improved by modeling the various aspects of cloud systems, including scheduling, service time, wait time, and hardware and software failures. The aim of this study is to survey research studies done on the modeling of cloud computing using the queuing system in order to identify where more emphasis should be placed in both current and future research directions. This paper follows the goal by investigating the articles published between 2008 and January 2017 in journals and conferences. A systematic mapping study combined with a systematic literature review was performed to find the related literature, and 71 articles were selected as primary studies that were classified in relation to the focus, research type, and contribution type. We classified the modeling techniques of cloud computing using the queuing theory in seven categories based on their focus area: (1) performance, (2) quality of service, (3) workflow scheduling, (4) energy savings, (5) resource management, (6) priority-based servicing, and (7) reliability. A majority of the primary articles focus on performance (37%), 15% of them focus on resource management, 14% of them focus on quality of service, 13% of them focus on workflow scheduling, 13% of them focus on energy savings, 4% of them focus on priority-based servicing for requests, and 4% of them focus on reliability. This work summarizes and classifies the research efforts conducted on applying queue theory for modeling of cloud computing (AQTMCC), providing a good starting point for further research in this area. KEYWORDScloud computing, cloud modeling, queuing systems, queuing theory, systematic review INTRODUCTIONCloud computing is the recent evolution in the information technology and is growing very fast due to the extensive use of mobile devices, such as PDAs, cell phones, and tablets. 1 To emphasize the goals of cloud computing, we refer to the definition of NIST (National Institute of Standards and Technology); a cloud model is composed of five characteristics, three service models, and four deployment models. 2 Service models of cloud computing are as follows: (1) Software as a Service (SaaS), such as CRM (Customer Relationship Management), virtual desktop, communications, and games; (2) Platform as a Service (PaaS), such as databases, web servers, and deployment tools; and (3) Infrastructure as a Service (IaaS), such as virtual machines (VMs), storages, servers, and load balancers. Deployment models include private clouds, public clouds, community clouds, and hybrid clouds. The characteristics of a cloud are on-demand self-servicing, elasticity, broad network access, resource pooling, and measured service. 1 A data center in cloud computing consists of several servers that are organized in racks and connected through communicati...

show abstract

Resource provisioning for cloud computing

Cited by 117 publications

References 17 publications

A Survey on Resource Allocation and Monitoring in Cloud Computing

A Survey on Resource Allocation and Monitoring in Cloud Computing

Open‐Source Cloud Software Solutions

Applying queue theory for modeling of cloud computing: A systematic review

Contact Info

Product

Resources

About