A Toolkit for Storage Qos Provisioning for Data-Intensive Applications

Słota, Renata; Król, Dariusz; Skałkowski, Kornel; Orzechowski, Michał; Nikołow, Darin; Kryza, Bartosz; Wrzeszcz, Michał; Kitowski, Jacek

doi:10.7494/csci.2012.13.1.63

Cited by 5 publications

(3 citation statements)

References 11 publications

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“…In such a case, there are usually different Lustre instances on the different sites, which means that the data stored on this file system can only be shared within the local cluster. Although the efficiency of the Lustre system is high, there is still a possibility of improving it using dedicated tools such as QstorMan [50][51][52].…”

Section: Typical Grid and Cloud Data-access Toolsmentioning

confidence: 99%

Towards Transparent Data Access With Context Awareness

Wrzeszcz

Kitowski

Słota

2018

csci

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Open-data research is an important factor accelerating the production and analysis of scientific results as well as worldwide collaboration; still, very little data is being shared at scale. The aim of this article is to analyze existing data-access solutions along with their usage limitations. After analyzing the existing solutions and data-access stakeholder needs, the authors propose their own vision of a data-access model.

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Section: Typical Grid and Cloud Data-access Toolsmentioning

confidence: 99%

Towards Transparent Data Access With Context Awareness

Wrzeszcz

Kitowski

Słota

2018

csci

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“…A second example of software which can provide backup and archive services is the National Data Storage system (NDS) [18,19,20,21,22,23,24], developed at the CYFRONET Academic Computer Center. The NDS is a distributed data storage system intended to provide backup, archiving, and data access services.…”

Section: State-of-the-art (Related Work)mentioning

confidence: 99%

Resource Storage Management Model for ensuring quality of service in the cloud archive systems

Kapanowski¹,

Słota²,

Kitowski³

2014

csci

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Nowadays, service providers offer a lot of IT services in the public or private cloud. Clients can buy various kinds of services, such as SaaS, PaaS, etc. Recently, Backup as a Service (BaaS), a variety of SaaS, was introduced there. At the moment, there are several different BaaS's available to archive data in the cloud, but they provide only a basic level of service quality. In this paper, we propose a model which ensures QoS for BaaS and some methods for management of storage resources aimed at achieving the required SLA. This model introduces a set of parameters responsible for an SLA level which can be offered at the basic or higher level of quality. The storage systems (typically HSM), which are distributed between several Data Centers, are built based on disk arrays, VTL's, and tape libraries. The RSMM model does not assume bandwidth reservation or control, but rather is focused on management of storage resources.

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“…As the data input for our system we used a simulator for monitoring whose output is similar to the SMED [15] application which is part of QStorMan which will be used in the future as a source of monitoring data. During the current research we try to test and check the correctness of our knowledge engines.…”

Section: Test Environmentmentioning

confidence: 99%

Data Storage Management Using Ai Methods

Wlodzimierz

Szura

2013

csci

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Data management and monitoring is an important issue in scientific computation. Scientists want to access their data as quickly as possible. Some experiments need to store a lot of data which have to be secure. By saying this we mean that this data can not disappear or be damaged also the data storage should be as cheap as possible. In this paper we present an approach to the automation of monitoring and management of data storage. We introduce a knowledge based system which is able to manage data, i.e., make decisions on migrating data, replicating or removing it. We discuss some of the existing solutions which are popular on the market. In this paper we aim to present our system which uses such AI techniques like fuzzy logic or a rule-based expert system to deal with data storage management. We exploit in this system a cost model to analyze the proposed solutions. The operations performed by our system are aimed to optimize the usage of the monitored infrastructure.

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A Toolkit for Storage Qos Provisioning for Data-Intensive Applications

Cited by 5 publications

References 11 publications

Towards Transparent Data Access With Context Awareness

Towards Transparent Data Access With Context Awareness

Resource Storage Management Model for ensuring quality of service in the cloud archive systems

Data Storage Management Using Ai Methods

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