Rapid Prototyping of Multitier Cloud-Based Services and Systems

Bahga, Arshdeep; Madisetti, Vijay K.

doi:10.1109/mc.2013.154

Cited by 12 publications

(12 citation statements)

References 4 publications

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“…e.g. [2]). In [7] an initial approach has been presented that aims at supporting components with a partitionable state allowing better horizontal scalability.…”

Section: Methodsmentioning

confidence: 99%

“…Section III). 2 As an additional hard constraint a threshold level for the score of the best service is defined to be always above 0.15. In case the score drops below that threshold, a requirement violation is detected.…”

Section: Example and Evaluationmentioning

confidence: 99%

“…Having a closer look at a component (here Provider4 is selected) reveals that the component has a service container with a provided service (ICryptoService). Digging further into the service itself shows that it posses 2 The choice of the concrete evaluator function is not of importance for the scenario, we could also have used e.g. an exponential function such as = −0.1 * Figure 11.…”

Section: Example and Evaluationmentioning

confidence: 99%

“…Score statistics of providers a dynamic (green arrow) non-functional property on its encrypt method. On the right hand side of the GUI some details about the non-functional property are presented and the current value is shown (2). The dynamics of the system behavior is illustrated with Fig.…”

Section: Example and Evaluationmentioning

confidence: 99%

See 3 more Smart Citations

A Middleware for Managing Non-Functional Requirements in Cloud PaaS

Braubach¹,

Jander²,

Pokahr³

2014

2014 International Conference on Cloud and Autonomic Computing

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A key aspect of distributed applications in platformas-a-service clouds revolves around the definition of requirements for quality of service and the most efficient use of the available resources to achieve them. Matching both the requirements and resources represents a unique challenge: While requirements are generally defined in relatively abstract form and defined as system-wide parameters, the resources are concrete, low-level entities that, by themselves, are only of marginal influence on the requirements. In order to establish a relationship between these two requires both the agglomeration of properties into more abstract ones as well as refining requirements in more detailed, concrete ones, both of which can often only be done to a certain degree. This paper presents a vision how both aspects can be brought to the same level and introduces an approach enhancing component-based cloud applications with non-functional properties in the context of an integrated programming model. This allows developers of such applications to formally declare properties that may influence the application during runtime and document the expectations regarding non-functional aspects of the overall system. This can be used to ensure the health of the application and, in case requirements are violated, actions like the deployment of additional resources can be performed in order to alleviate any degradation of its non-functional state, either by evaluating, choosing and performing pre-defined actions automatically or by manual administrative intervention.

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“…e.g. [2]). In [7] an initial approach has been presented that aims at supporting components with a partitionable state allowing better horizontal scalability.…”

Section: Methodsmentioning

confidence: 99%

Section: Example and Evaluationmentioning

confidence: 99%

Section: Example and Evaluationmentioning

confidence: 99%

Section: Example and Evaluationmentioning

confidence: 99%

See 2 more Smart Citations

A Middleware for Managing Non-Functional Requirements in Cloud PaaS

Braubach¹,

Jander²,

Pokahr³

2014

2014 International Conference on Cloud and Autonomic Computing

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“…Because our work can extract templates from existing environments and reflects actual environment changes to stack information, users can replicate or federate virtual resource environments more easily. The paper [14] is a work to construct multitier cloud-based services. Our work provides a mechanism of template sharing in multi-tier contracts, so that end users can build virtual resource environments using templates of upper tier System Integrators.…”

Section: Related Workmentioning

confidence: 99%

Development of template management technology for easy deployment of virtual resources on OpenStack

et al. 2014

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In this paper, we describe the development of template management technology to build virtual resources environments on OpenStack. In recent days, Cloud computing has been progressed and also open source Cloud software has become widespread. Authors are developing cloud services using OpenStack. There are technologies which deploy a set of virtual resources based on system environmental templates to enable easy building, expansion or migration of cloud resources. OpenStack Heat and Amazon CloudFormation are template deployment technologies and build stacks which are sets of virtual resources based on templates. However, these existing technologies have 4 problems. Heat and CloudFormation transaction managements of stack create or update are insufficient. Heat and CloudFormation do not have sharing mechanism of templates. Heat cannot extract templates from existing virtual environments. Heat does not reflect actual environment changes to stack information. Therefore, we propose a new template management technology with 4 improvements. It has a mechanism of transaction management like roll back or roll forward in case of abnormal failure during stack operations. It shares templates among end users and System Integrators. It extracts templates from existing environments. It reflects actual environment changes to stack information. We implemented the proposed template management server and showed that end users can easily replicate or build virtual resources environments. Furthermore, we measured the performance of template extraction, stack create and update and showed our method could process templates in a sufficient short time.

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Elastic component‐based applications in PaaS clouds

Pokahr

Braubach

2015

Concurrency and Computation

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Elasticity is the capability of an application to adapt its resource usage to the current workload of the system. Existing platform-as-a-service (PaaS) solutions concentrate on web applications and do not support elasticity for other kinds of applications. To change this, in this paper, the vision and partial implementation for a component-based PaaS cloud is proposed consisting of a programming model and an autonomic manager for safeguarding non-functional application requirements. To illustrate this vision, the paper focuses on two key features of a PaaS infrastructure, the scale-out of services and the on-demand deployment of application resources. The former allows for increasing the performance by distributing service calls among several service providers working in parallel, and the latter refers to the automatic packaging and transfer of needed deployment units. It will be shown how these aspects have been solved within the Jadex PaaS cloud infrastructure. Both concepts have been validated using an application scenario, which highlights the advantages of automatic service scaling and deployment for developers and users.An example is a complex calculation algorithm. If it is deployed as is in the cloud, there is no elasticity regarding the size of the calculation problem, as according to Amdahl's law [5], the computation speed cannot be increased by scaling out. The developer would have to split the computation manually into parallelizable chunks, for example, by applying suitable algorithmic skeletons [6] such as map-reduce.The work presented in this paper aims at supporting the development of cloud-aware componentbased applications. Programming and adaptation management concepts and a PaaS infrastructure are introduced, which empower developers to achieve application elasticity. This paper expands on a vision of elastic component-based applications presented earlier [7]. The vision focuses on programming and adaptation management concepts that allow considering explicit non-functional requirements (NFRs) and non-functional properties (NFPs) seamlessly during design, implementation, and operation of applications. In addition, this paper especially presents required features for a PaaS infrastructure suitable to realize this vision. An initial prototype of such a PaaS infrastructure is presented with a focus on service scale-out and on-demand deployment, as well as an application scenario running on the prototype infrastructure.This paper is structured as follows. In Section 2, the vision of elastic component-based applications and the chosen approach are presented. As two fundamental building blocks of the approach, Section 3 introduces a generic component model for elastic application programming, and Section 4 presents adaptation management for elastic applications. In Section 5, details of the elastic PaaS infrastructure are presented by discussing how service scale-out and on-demand deployment can be realized. Afterwards, Section 6 discusses related work, and Section 7 finally concludes the paper. VISI...

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Rapid Prototyping of Multitier Cloud-Based Services and Systems

Cited by 12 publications

References 4 publications

A Middleware for Managing Non-Functional Requirements in Cloud PaaS

A Middleware for Managing Non-Functional Requirements in Cloud PaaS

Development of template management technology for easy deployment of virtual resources on OpenStack

Elastic component‐based applications in PaaS clouds

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