A Software as a Service with Multi-tenancy Support for an Electronic Contract Management Application

Kwok, Thomas; Nguyen, Thien Huu; Lam, Linh

doi:10.1109/scc.2008.138

Cited by 105 publications

(36 citation statements)

References 3 publications

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“…In SaaS -which is closest to the work descirbed here, the need to support a variety of clients/providers, referred as tenants was demonstrated in [14]. Here SaaS providers are aware of the diverse nature of their tenants and multi-tenancy support was controlled at different levels: by the application; by the middleware; by the virtual machine (VM), or by the operating system [15,16]. A framework to deal with these issues supporting hundreds or even thousands of tenants for SaaS applications was presented in [17].…”

Section: Related Workmentioning

confidence: 99%

Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Nino-Ruiz

Bayliss

Galang

et al. 2014

2014 IEEE 10th International Conference on E-Science

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For many research endeavours, e-Infrastructures need to provide predictable, on-demand access to large-scale computational resources with high data availability. These need to scale with the research communities requirements and use. One example of such an e-Infrastructure is the Australian Urban Research Infrastructure Network (AURIN -www.aurin.org.au) project, which supports Australia-wide research in and across the urban and built environment. This paper describes the architecture of the AURIN infrastructure and its support for access to distributed (federated) and highly heterogeneous data sets from a wide range of providers. We present how this architecture solution leverages the intersection of high throughput computing (HTC), infrastructure as a service (IaaS) Cloud services and big data technologies including use of NoSQL resources. The driving concept in this architecture and the focus of this paper is the ability for scaling up or down depending on resource demands at any given time. This is done automatically and on demand avoiding either under-or over-utilization of resources. This resourceoptimization-driven infrastructure has been designed to ensure that peak loads can be predicted and successfully coped with, as well as avoid wasting resources during non-peak times. This overall management strategy has resulted in an e-Infrastructure that provides a flexible, evolving research environment that scales with research needs, rather than providing a rigid (static) end product. The driving concept in this architecture and the focus of this paper is the ability for scaling up or down depending on resource demands at any given time. This is done automatically and on demand avoiding either under-or over-utilization of resources. This resource-optimization-driven infrastructure has been designed to ensure that peak loads can be predicted and successfully coped with, as well as avoid wasting resources during non-peak times. This overall management strategy has resulted in an e-Infrastructure that provides a flexible, evolving research environment that scales with research needs, rather than providing a rigid (static) end product.

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Section: Related Workmentioning

confidence: 99%

Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Nino-Ruiz

Bayliss

Galang

et al. 2014

2014 IEEE 10th International Conference on E-Science

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“…A SaaS application can be in one of two types of system architectures [2], [3]: multi-instance or multi-tenancy. The former employs virtual machines to install multiple instances of the software so that each instance of the software only serves one tenant.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Tenant Level Checkpointing Technique for SaaS Applications

Zhu

Yousef

Younas

2015

2015 IEEE 8th International Conference on Cloud Computing

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Abstract-Tenant level checkpointing is a novel faulttolerance technique proposed in our previous work for largescale software-as-a-service applications. This paper evaluates the technique by a theoretical analysis of the technique and an empirical study using workload benchmarks of real largescale cluster systems. We propose the notion of accumulated delay as a measurement of the performance of checkpointing techniques. It reflects the effect of checkpointing on system performance as experienced by the end users. Both theoretical analysis and empirical study show that tenant level checkpointing significantly outperforms traditional bulk checkpointing as measured by the amount of accumulated delays.

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“…the tenants, share the same (software) resources [1]. A multi-tenant system allows to make full use of the economy of scale, as several SaaS customers access the same application at the same time, while the instances are configured according to the diverse requirements of the various tenants [15]. Multi-tenant systems are characterized by high demands on configurability and evolvability, which go well beyond multi-instance and multi-user applications, or software product lines [3].…”

Section: Introductionmentioning

confidence: 99%

Understanding the interactions between users and versions in multi-tenant systems

Espinha

Zaidman

Groß

2013

Proceedings of the 2013 International Workshop on Principles of Software Evolution

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Multi-tenant systems represent a class of software-as-a-service (SaaS) applications in which several groups of users, i.e. the tenants, share the same resources. This resource sharing results in multiple business organizations using the same base application, yet, requiring specific adaptations or extensions for their specific business models. Each configuration must be tended to during evolution of a multi-tenant system, because the existing application is mended, or because new tenants request additional features. In order to facilitate the understanding of multi-tenant systems, we propose to use a runtime topology augmented with user and version information, to help understand usage patterns exhibited by tenants of the different components in the system.We introduce Serviz, our implementation of the augmented runtime topology, and evaluate it through a field user study to see to which extent Serviz aids in the analysis and understanding of a multi-tenant system.

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A Software as a Service with Multi-tenancy Support for an Electronic Contract Management Application

Cited by 105 publications

References 3 publications

Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Evaluation of a Tenant Level Checkpointing Technique for SaaS Applications

Understanding the interactions between users and versions in multi-tenant systems

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