A tenant-based resource allocation model for scaling Software-as-a-Service applications over cloud computing infrastructures

Espadas, Javier; Molina, Arturo; Jimenez, Guillermo; Molina, Martín; Ramírez, Raúl J.; Concha, David

doi:10.1016/j.future.2011.10.013

Cited by 148 publications

(68 citation statements)

References 35 publications

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“…The experimental results show that the proposed dynamic resource allocation scheme can improve resource utilization and reduce the user usage cost. Javier Espadas, Arturo Molina, Guillermo Jimenez, Martin Molina, Raul Ramirez, David Concha author proposed an architecture [4] a tenant-based model is presented to tackle over and underutilization when SaaS platforms are deployed over cloud computing infrastructures. This model contains three complementary approaches: tenant-based isolation which encapsulates the execution of each tenant, tenant-based load balancing which distributes requests according to the tenant information, and a tenant-based VM instance allocation which determines the number of VM instances needed for certain workload, based on VM capacity and tenant context weight In this architecture Each Tenant Context object holds information about tenant status such as active users, logged users, subscriber ID, total of requests, etc.. Yuda Wang, Renyu Yang, Tianyu Wo, Wenbo Jiang, Chunming Hu author proposed an architecture [5] that combine long running VM service with typical batch workload like MapReduce.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Resource Allocation for Virtual Machine in Cloud

2017

IJAERD

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Section: Related Workmentioning

confidence: 99%

Dynamic Resource Allocation for Virtual Machine in Cloud

2017

IJAERD

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“…In a cloud architecture the load of resources can be monitored (CPU, disk storage and network interface) and nodes switched on or off to minimize the overall power consumption [27]. This potential to scale up or down, based on performance monitoring, could help in achieving cost-effective scalability [31]. The dynamic part is relevant for green software practices and is determined by the resource utilization of the software.…”

Section: B Resource Utilizationmentioning

confidence: 99%

A Resource Utilization Score for Software Energy Consumption

Jagroep¹,

Werf²,

Broekman³

et al. 2016

Proceedings of ICT for Sustainability 2016

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Abstract-Software as the true consumer of power and its potential contribution to reach sustainability goals is increasingly being acknowledged. Studies so far have presented successful results and methods to address the energy consumption of the software, indicating that different stakeholders striving for green software have different information needs with respect to their goals. However, currently there is no uniform manner to communicate measurements to the different stakeholders such that key findings are clearly identifiable and easy to understand, which is likely to hamper green software practices. In this paper we propose a metric that expresses a score for the resource utilization, such as power consumption, of a software product. The metric is designed to be a single score and is flexible to encompass those aspects that a stakeholder considers relevant in the context of software energy consumption. The metric was applied on two applications and allowed for objective comparison of application configurations and versions. Also the behavior of these applications across different hardware configurations could be analyzed. In addition to the metric we investigate means to visualize measurements which enhances communication and helped with highlighting the key findings.

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“…Espadas et al in paper [18] discuss about over and under provisioning of cloud resources, although the peak loads can be successfully predicted, thus without having an effective elasticity model, costly resources are wasted during nonpeak times (under-utilization) or revenues from potential customers are lost after experiencing a poor service. The control of the leased resources (virtual machines, storage) falls under the client responsibilities.…”

Section: Related Work In Resource Managementmentioning

confidence: 99%

“…As a result, the proposed method had utilized the resources in the hybrid infrastructure (cloud and grid).The proposed model in paper [31] is being developed using time varying workload and DVFS theory in a multi-tier cloud platform which resulted in saving the energy and cost. In paper [18], the researcher proposed a model using multi-tenancy characteristic to solve the over and under provisioning of the cloud resources problem. They used a tenant-based isolation approach, which encapsulates the execution of each tenant.…”

Section: International Journal Of Machine Learning and Computing Volmentioning

confidence: 99%

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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A tenant-based resource allocation model for scaling Software-as-a-Service applications over cloud computing infrastructures

Cited by 148 publications

References 35 publications

Dynamic Resource Allocation for Virtual Machine in Cloud

Dynamic Resource Allocation for Virtual Machine in Cloud

A Resource Utilization Score for Software Energy Consumption

A Survey on Resource Allocation and Monitoring in Cloud Computing

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