From infrastructure delivery to service management in clouds

Rodero-Merino, Luis; Vaquero, Luis M.; Gil, Victor; Galán, Fermín; Fontán, Javier; Montero, Rubén; Llorente, Ignacio

doi:10.1016/j.future.2010.02.013

Cited by 179 publications

(87 citation statements)

References 11 publications

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“…The lock-in issue turns critical when considering to terminate a contract with a particular provider. This factor will continue to be an inhibitor as long as there is a lack of standardization on service APIs, architectural components, and data structures (Armbrust et al, 2010;Rodero-Merino et al, 2010).…”

Section: Portabilitymentioning

confidence: 99%

A survey study on major technical barriers affecting the decision to adopt cloud services

Phaphoom

Wang

Samuel

et al. 2015

Journal of Systems and Software

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In the context of cloud computing, risks associated with underlying technologies, risks involving service models and outsourcing, and enterprise readiness have been recognized as potential barriers for the adoption. To accelerate cloud adoption, the concrete barriers negatively influencing the adoption decision need to be identified. Our study aims at understanding the impact of technical and security-related barriers on the organizational decision to adopt the cloud. We analyzed data collected through a web survey of 352 individuals working for enterprises consisting of decision makers as well as employees from other levels within an organization. The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability. The result from our logistic regression analysis confirms the criticality of the security concern, which results in an up to 26-fold increase in the non-adoption likelihood. Our study underlines the importance of the technical and security perspectives for research investigating the adoption

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Section: Portabilitymentioning

confidence: 99%

A survey study on major technical barriers affecting the decision to adopt cloud services

Phaphoom

Wang

Samuel

et al. 2015

Journal of Systems and Software

View full text Add to dashboard Cite

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“…In [29] and [30], a management system for services composed of multiple VMs is presented. These works focus on the definition and deployment of composed cloud services.…”

Section: Application Placementmentioning

confidence: 99%

Cost-Effective Feature Placement of Customizable Multi-Tenant Applications in the Cloud

et al. 2013

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Cloud computing technologies can be used to more flexibly provision application resources. By exploiting multi-tenancy, instances can be shared between users, lowering the cost of providing applications. A weakness of current cloud offerings however, is the difficulty of creating customizable applications that retain these advantages. In this article, we define a feature-based cloud resource management model, making use of Software Product Line Engineering (SPLE) techniques, where applications are composed of feature instances using a service-oriented architecture. We focus on how resources can be allocated in a cost-effective way within this model, a problem which we refer to as the feature placement problem. A formal description of this problem, that can be used to allocate resources in a cost-effective way, is provided. We take both the cost of failure to place features, and the cost of using servers into account, making it possible to take energy costs or the cost of public cloud infrastructure into consideration during the placement calculation. Four algorithms that can be used to solve the feature placement problem are defined. We evaluate the algorithm solutions, comparing them with the optimal solution determined using an integer linear problem solver, and evaluating the execution times of the algorithms, making use of both generated inputs and a use case based on three applications. We show that, using our approach a higher degree of multi-tenancy can be achieved, and that for the considered scenarios, taking the relationships between features into account and using application-oriented placement performs 25% to 40% better than a purely feature-oriented placement.

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“…Third, our model provides flexible system controls, and a service provider can activate, safe-deactivate, deactivate, suspend, and resume TRE at its own need. Instead, the recent work in [39] mainly focuses on how to enable automatic deployment and scaling for service managements. Fig.…”

Section: The Enhanced Scientific Public Cloud (Esp) Modelmentioning

confidence: 99%

“…Marshall et al [25] have implemented a resource manager, built on the Nimbus toolkit to dynamically and securely extend existing physical clusters into the cloud. Rodero-Merino et al [39] proposes a new abstraction layer that allows for their automatic deployment and escalation depending on the service status. Our previous Transformer [35] programming framework aims to facilitate the building of diverse data-parallel programming models: Dryadlike data flow, MapReduce, and All-Pairs.…”

Section: Infrastructure For Scientific Communitiesmentioning

confidence: 99%

In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

Wang

Zhan

Shi

et al. 2012

IEEE Trans. Parallel Distrib. Syst.

102

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Abstract-The basic idea behind cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to the success of cloud computing: in cloud, can small-to-medium scale scientific communities benefit from the economies of scale? Our research contributions are three-fold: first, we propose an innovative public cloud usage model for small-to-medium scale scientific communities to utilize elastic resources on a public cloud site while maintaining their flexible system controls, i.e., create, activate, suspend, resume, deactivate, and destroy their high-level management entities-service management layers without knowing the details of management. Second, we design and implement an innovative system-DawningCloud, at the core of which are lightweight service management layers running on top of a common management service framework. The common management service framework of DawningCloud not only facilitates building lightweight service management layers for heterogeneous workloads, but also makes their management tasks simple. Third, we evaluate the systems comprehensively using both emulation and real experiments. We found that for four traces of two typical scientific workloads: high throughput computing (HTC) and many task computing (MTC), DawningCloud saves the resource consumption maximally by 59.5% and 72.6% for HTC and MTC service providers, respectively, and saves the total resource consumption maximally by 54% for the resource provider with respect to the previous two public cloud solutions. To this end, we conclude that small-to-medium scale scientific communities indeed can benefit from the economies of scale of public clouds with the support of the enabling system.

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From infrastructure delivery to service management in clouds

Cited by 179 publications

References 11 publications

A survey study on major technical barriers affecting the decision to adopt cloud services

A survey study on major technical barriers affecting the decision to adopt cloud services

Cost-Effective Feature Placement of Customizable Multi-Tenant Applications in the Cloud

In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

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