Cloud computing in e-Science: research challenges and opportunities

Yang, Xiaoyu; Wallom, David; Waddington, Simon; Wang, Jianwu; Shaon, Arif; Matthews, Brian; Wilson, M.; Guo, Yike; Guo, Li; Blower, Jon; Vasilakos, Athanasios V.; Liu, Kecheng; Kershaw, Philip

doi:10.1007/s11227-014-1251-5

Cited by 36 publications

(28 citation statements)

References 96 publications

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“…Next, all important reliability and HA measuring tools and metrics to evaluate the importance degree of each cloud components in the proposed architecture will be specified. Some main failure modes of CCSs have been proposed in [36,63,64] but as one of the future works of this research, different viewpoints exist for proposing a comprehensive classification of cloud failures. Table 4 presents a summary of these studies.…”

Section: Which?mentioning

confidence: 99%

Reliability and high availability in cloud computing environments: a reference roadmap

Mesbahi

Rahmani

Hosseinzadeh

2018

Hum. Cent. Comput. Inf. Sci.

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Reliability and high availability have always been a major concern in distributed systems. Providing highly available and reliable services in cloud computing is essential for maintaining customer confidence and satisfaction and preventing revenue losses. Although various solutions have been proposed for cloud availability and reliability, but there are no comprehensive studies that completely cover all different aspects in the problem. This paper presented a ‘Reference Roadmap’ of reliability and high availability in cloud computing environments. A big picture was proposed which was divided into four steps specifying through four pivotal questions starting with ‘Where?’, ‘Which?’, ‘When?’ and ‘How?’ keywords. The desirable result of having a highly available and reliable cloud system could be gained by answering these questions. Each step of this reference roadmap proposed a specific concern of a special portion of the issue. Two main research gaps were proposed by this reference roadmap.

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Section: Which?mentioning

confidence: 99%

Reliability and high availability in cloud computing environments: a reference roadmap

Mesbahi

Rahmani

Hosseinzadeh

2018

Hum. Cent. Comput. Inf. Sci.

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“…Out of these problems, cloud computing can help the EIs to reduce their financial and technical issues by providing servers, databases, software, Online library, etc. These facilities do not only help in reducing the expenses of EIs on purchasing new equipment like servers, databases, software, etc., but also in reducing the need for extra space, and manpower for operating and maintaining these systems [13]. For example, when it comes to deploy a network in an EI, then the equipment is purchased.…”

Section: Trust Management In Educational Institutesmentioning

confidence: 99%

“…In their paper, Yang, et al [13] gave the detailed survey of recent research advances in different fields and cloud computing in e-science. They included, e.g., business model, computing model, and programming model in e-science.…”

Section: Literature Surveymentioning

confidence: 99%

“…However, in most cases CSPs hire third party services to implement the security features as per the requirements of an organization, finally additional cost added to the consumers. Mehbub et al [13] discussed the selection of trustworthy CSP only based on its SLA and conclude that selection criteria on SLA are not convincing. Their proposed architecture is a multi-faceted Trust management system for a cloud marketplace, providing means to efficiently differentiate between good and poor quality providers.…”

Section: Proposed Model Versus Existing Modelmentioning

confidence: 99%

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Trust model at service layer of cloud computing for educational institutes

et al. 2015

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Cloud computing is one of those technologies which have revolutionized the modern world. Through this, people can start their businesses without huge investments required for infrastructure like servers, technical staff for maintenance, and purchasing of expensive software, etc. With many advantages, there are few risks involved with cloud computing. There are issues like unavailability of service, i.e., they are down when required. Another issue is of outdated service/stuff provision to the clients by the cloud service providers. Similarly, lacking of effective and quality support services to their customers is another important concern. Moreover, non-capability of cloud B Moneeb Gohar 123 S. Jabbar et al.service provider in honoring the service level agreement is an additional prong in this list. All such issues make cloud service users frustrated. Hence, there is a need of a system which may help the cloud service user to select good cloud service provider. Hence, for the above mentioned issues, in this article, we have proposed a model which will help the cloud service users in finding out the efficient and trustworthy cloud service provider. In put data to the model can be collected from regulatory authorities, performance of cloud service provider in the last one year, and feedback taken from the customers. Moreover, the proposed model is flexible enough to be customized according to the precedence level of aforementioned parameters for the cloud service users, i.e., educational institutes. We have also given a comparative analysis of proposed model with general existing model to portray the importance and requirement of the designed model for the said application domain.

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“…Strategic Outsourcing), or even multi-party contracts.Although several advances happened in the last years in the cloud space, there is still a lot to be done in HPC cloud. Studies have shown some challenges on HPC cloud [1,52,53,55,56,90,102,111,115,119], however, they do not present a comprehensive view of findings and challenges in the area. Therefore, this paper aims at helping users, research institutions, universities, and companies understand solutions in HPC cloud.…”

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confidence: 99%

HPC Cloud for Scientific and Business Applications

et al. 2018

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High Performance Computing (HPC) clouds are becoming an alternative to on-premise clusters for executing scientific applications and business analytics services. Most research efforts in HPC cloud aim to understand the cost-benefit of moving resource-intensive applications from on-premise environments to public cloud platforms. Industry trends show hybrid environments are the natural path to get the best of the on-premise and cloud resources-steady (and sensitive) workloads can run on on-premise resources and peak demand can leverage remote resources in a pay-as-you-go manner. Nevertheless, there are plenty of questions to be answered in HPC cloud, which range from how to extract the best performance of an unknown underlying platform to what services are essential to make its usage easier. Moreover, the discussion on the right pricing and contractual models to fit small and large users is relevant for the sustainability of HPC clouds. This paper brings a survey and taxonomy of efforts in HPC cloud and a vision on what we believe is ahead of us, including a set of research challenges that, once tackled, can help advance businesses and scientific discoveries. This becomes particularly relevant due to the fast increasing wave of new HPC applications coming from big data and artificial intelligence. users have no visibility or concerns on costs of running jobs. However, large clusters do incur expenses and, when not properly managed, can generate resource wastage and poor quality of service.Motivated by the different utilization levels of clusters around the globe and by the need to run even larger parallel programs, in the early 2000s, Grid Computing became relevant for the HPC community. Grids offer users access to powerful resources managed by autonomous administrative domains [50,51]. The notion of monetary costs for running applications was soft, favoring a more collaborative model of resource sharing. Therefore, quality of service was not strict in Grids, having users relying on best-effort policies to run applications.In the late 2000s, cloud computing [8,26,91] was quickly increasing its maturity level and popularity, and studies started to emerge on the viability of executing HPC applications on remote cloud resources. These applications, which consume more resources than traditional cloud applications and usually are executed in batches rather than 24x7 services, range from parallel applications written in Message Passing Interface (MPI) [58,59] to the newest big data [11,14,39,101] and artificial intelligence applications-the latter mostly relying on deep learning [34,80]. Cloud then came up as an evolution of a series of technologies, mainly on virtualization and computer networks, which facilitated both workload management and interaction with remote resources respectively. Apart from software and hardware, cloud offers a business model where users pay for resources on demand. Compared to traditional HPC environments, in clouds users can quickly adjust their resource pools, via a mechanism known as elast...

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Cloud computing in e-Science: research challenges and opportunities

Cited by 36 publications

References 96 publications

Reliability and high availability in cloud computing environments: a reference roadmap

Reliability and high availability in cloud computing environments: a reference roadmap

Trust model at service layer of cloud computing for educational institutes

HPC Cloud for Scientific and Business Applications

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