A performance evaluation of Azure and Nimbus clouds for scientific applications

Tudoran, Radu; Costan, Alexandru; Antoniu, Gabriel; Bougé, Luc

doi:10.1145/2168697.2168701

Cited by 48 publications

(41 citation statements)

References 11 publications

(10 reference statements)

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“…It is commonly known that clouds offer a variable performance, analyzed in several previous works [19], [20], [21], focusing on the intra-datacenter performance. When it comes to the global cloud infrastructure, the variability is expected to increase.…”

Section: B Assessing the Cloud Infrastructure Variabilitymentioning

confidence: 99%

Bridging Data in the Clouds: An Environment-Aware System for Geographically Distributed Data Transfers

Tudoran¹,

Costan²,

Wang³

et al. 2014

2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

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Abstract-Today's continuously growing cloud infrastructures provide support for processing ever increasing amounts of scientific data. Cloud resources for computation and storage are spread among globally distributed datacenters. Thus, to leverage the full computation power of the clouds, global data processing across multiple sites has to be fully enabled. However, managing data across geographically distributed datacenters is not trivial as it involves high and variable latencies among sites which come at a high monetary cost. In this work, we propose a uniform data management system for scientific applications running across geographically distributed sites. Our solution is environmentaware, as it monitors and models the global cloud infrastructure, and offers predictable data handling performance for transfer cost and time. In terms of efficiency, it provides the applications with the possibility to set a tradeoff between money and time and optimizes the transfer strategy accordingly. The system was validated on Microsoft's Azure cloud across the 6 EU and US datacenters. The experiments were conducted on hundreds of nodes using both synthetic benchmarks and the real life A-Brain application. The results show that our system is able to model and predict well the cloud performance and to leverage this into efficient data dissemination. Our approach reduces the monetary costs and transfer time by up to 3 times.

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Section: B Assessing the Cloud Infrastructure Variabilitymentioning

confidence: 99%

Bridging Data in the Clouds: An Environment-Aware System for Geographically Distributed Data Transfers

Tudoran¹,

Costan²,

Wang³

et al. 2014

2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

Self Cite

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“…Originally used primarily by web application developers, scientific and technical high performance computing (HPC) applications have also found a use for them. [17][18] [19] However, cloud computing is challenging when there are real-time constraints [20]; this is an active area of research. However there are many robotics applications that are not time sensitive such as decluttering a room or precomputing grasp strategies.…”

Section: B Cloud Computingmentioning

confidence: 99%

IoT and Robotics: a synergy

Chowdhury¹

2017

Preprint

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Abstract-The Internet of Robotic Things (IoRT) [9] is a concept first introduced by Dan Kara at ABI Research, which talks about augmenting the existing IoT with active sensorization; thereby, opening the doors to novel business ideas, at the intersection of both IoT and Robotics. This position paper considers the synergy between IoT and robotics: it talks about the technologies in IoT that would benefit the robotics domain. The advent of Cloud Robotics and its role in aiding robot functions like sensing, manipulation, and mobility. The paper then discusses the ways in which robots can extend the capabilities of existing IoT infrastructure by acting as a special class of edge device. IoT-aided robotic applications are discussed in various domains like health-care, military, industrial plants and rescue operations. The paper concludes by considering the use case of an Intelligent Transportation System endowed by an IoRT-inspired architecture.

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“…Unfortunately, they do not consider the economic aspects related to each implementation. For instance, Tudoran et al 15 present a traditional performance evaluation study of two cloud architectures under a workload representative of scientific applications. More recently, Mukherjee et al 16 introduce an approach to evaluate the Amazon Cloud Platform for web applications.…”

Section: Background and Motivationmentioning

confidence: 99%

A Methodology for Economic Evaluation of Cloud-Based Web Applications

Domènech

Peña-Ortiz

Gil

et al. 2016

Int. J. Info. Tech. Dec. Mak.

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World Scientific Publishing Domenech, J.; Peña Ortiz, R.; Gil, JA.; Pont Sanjuan, A. (2016) Cloud technology is an attractive infrastructure solution to optimize the scalability and performance of web applications. The workload of these applications typically fluctuates between peak and valley loads and sometimes in an unpredictable way. Cloud systems can easily deal with this fluctuation because they provide customers with an almost unlimited on-demand infrastructure capacity using a pay-per-use model, which enables Internet-based companies to pay for the actual consumption instead of peak capacity. In this paradigm, this paper links the business model of an Internet-based company to the performance evaluation of the infrastructure. To this end, the paper develops a new methodology for assessing the costs and benefits of implementing web-based applications in the cloud. Traditional performance models and indexes related to usage of the main system resources (such as processor, memory, storage, and bandwidth) have been reformulated to include new metrics (such as customer losses and service costs) that are useful for business managers. Additionally, the proposed methodology has been illustrated with a case study of a typical e-commerce scenario. Experimental results show that the proposed metrics enable Internet-based companies to estimate the cost of adopting a particular cloud configuration more accurately in terms of the infrastructure cost and the cost of losing customers due to performance degradation. Consequently, the methodology can be a useful tool to assess the feasibility of business plans.

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A performance evaluation of Azure and Nimbus clouds for scientific applications

Cited by 48 publications

References 11 publications

Bridging Data in the Clouds: An Environment-Aware System for Geographically Distributed Data Transfers

Bridging Data in the Clouds: An Environment-Aware System for Geographically Distributed Data Transfers

IoT and Robotics: a synergy

A Methodology for Economic Evaluation of Cloud-Based Web Applications

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