Towards a Generic Cloud-Based Virtual Research Environment

Roth, Bastian; Hecht, Robin; Volz, Bernhard; Jablonski, Stefan

doi:10.1109/compsacw.2011.53

Cited by 11 publications

(11 citation statements)

References 4 publications

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“…Candela et al envisioned VREs to maximize the reuse of existing components, thus being assembled dynamically from a variety of scientific packages, and they pointed out the importance of automation, resilience and monitoring in these systems. Roth et al 7 and Assante et al 8 introduced two similar cloud-based implementations of such vision. Both implementations enable to dynamically compose VREs from a collection of scientific applications, which are installed directly on Virtual Machines (VMs).…”

Section: Introductionmentioning

confidence: 99%

“…We stress the term on-demand as, in contrast to current practices, our VREs are short-lived and dynamically instantiated as computing power is needed, by using cloud infrastructure. When compared to the inspiring work by Roth et al 7 and by Assante et al 8 , our methodology provides an improved way of packaging and delivering VRE components by adopting the microservices-oriented architecture. Furthermore, rather than describing a specific VRE implementation which builds on top of an ad hoc software stack, such as gCube by Assante et al 8 , we present a high-level methodology that employs industry-trusted technology.…”

Section: Introductionmentioning

confidence: 99%

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On-demand virtual research environments using microservices

Capuccini

Larsson

Carone

et al. 2019

PeerJ Computer Science

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The computational demands for scientific applications are continuously increasing. The emergence of cloud computing has enabled on-demand resource allocation. However, relying solely on infrastructure as a service does not achieve the degree of flexibility required by the scientific community. Here we present a microservice-oriented methodology, where scientific applications run in a distributed orchestration platform as software containers, referred to as on-demand, virtual research environments. The methodology is vendor agnostic and we provide an open source implementation that supports the major cloud providers, offering scalable management of scientific pipelines. We demonstrate applicability and scalability of our methodology in life science applications, but the methodology is general and can be applied to other scientific domains.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On-demand virtual research environments using microservices

Capuccini

Larsson

Carone

et al. 2019

PeerJ Computer Science

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“…These challenges are addressed by offering particular services in a Virtual Research Environment (VRE) as already explained in (Roth et al, 2011). In that, a service encapsulates each above mentioned IT resource (virtual machine, network storage, desktop applications, and web applications) which should be integrated and utilized within a VRE.…”

Section: Introductionmentioning

confidence: 99%

“…In (Roth et al, 2011) a high level solution proposal for a framework to build personal VREs with generic applicability is given, too. Below, we go into greater detail by focusing on Resource and Service layer, and thereby we present how generic applicability can be achieved.…”

Section: Introductionmentioning

confidence: 99%

It-as-a-Service for Building Virtual Research Environments

Roth

Jahn

Jablonski

2012

Proceedings of the 2nd International Conference on Cloud Computing and Services Science

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Virtual research environments are IT systems which support scientists in their daily workflow. Since there is a great number of different research domains, the quantity of utilized applications and hardware resources is immense. In the following, we present a solution how potentially each kind of IT resource like computing power, storage space, desktop applications and web applications can be integrated in form of services (ITas-a-Service). The composition of certain services defines a scientist's personal virtual research environment.

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“…Bastian Roth et al [10] have sort after the challenges in scientific collaboration and proposed an approach, which leverages on groupware tools and hypervisor-based virtualization techniques like KVM, VMware vSphere or Xen to run a generic collaboration platform.…”

Section: Introductionmentioning

confidence: 99%

CCCORE: Cloud Container for Collaborative Research

Suresh

Rao²

2018

IJECE

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Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high-performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on-demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources. Keyword: Cloud computing Collaborative research Container Dynamic allocation Finish time Residual resources Throughput Copyright © 2018 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Salini Suresh, Computer Science, Bharathiar University, Coimbatore, India. Email: pnsalinisuresh@gmail.com INTRODUCTIONIn mid-1990's various grid-based cyberinfrastructures or e-infrastructures were constituted that integrated high-speed research networks and middleware services and endorsed researchers for collaborative sharing of distributed resources. These firmly unified science gateways served as resource providers for specialized as well as generic research initiatives [1]. However, restricted interface to the data, domainspecific nature of science gateways did not match the requirement of the researchers outside those domains [2]. With the advent of cloud computing, easy reconfigurable and adaptive Virtual private research environments and science clouds became a preferred alternative to a traditional grid or cluster-based einfrastructures. Cloud-based collaborative research platforms provide the researchers with computing, storage resources required to run their applications, and they can collaborate to share data and application, while he concentrates on his area of research. Cloud platform offers compute environment with the huge set of computing resources much bigger than what an individual research organization can afford. Organizations can scale up, scale down the resources, and pay for it according to the usage. Multitenancy provided by cloud architecture enabled the creation of domain and requirement specific virtual private research environments that expedited researchers for collaboration and sharing of the resources [3]. Several science clouds such as Nectar Research cloud [4] provides the infrastructure to run compute-intensive scientific applications [5], [6]. Even though a substant...

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Towards a Generic Cloud-Based Virtual Research Environment

Cited by 11 publications

References 4 publications

On-demand virtual research environments using microservices

On-demand virtual research environments using microservices

It-as-a-Service for Building Virtual Research Environments

CCCORE: Cloud Container for Collaborative Research

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