On Fault Tolerance of Resources in Computational Grids

Das, Apurba

doi:10.5121/ijgca.2012.3301

Cited by 11 publications

(11 citation statements)

References 18 publications

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“…These processes execute in a special queue, allowing their execution to begin while placing other processes in suspension (sleep) mode. However, hardware and software failures may occur [28], preventing simulations from starting execution or new simulations may require additional computational resources. In Brazil, the National System of High Performance Computing (SINAPAD) coordinates the network of geographically distributed High Performance Computing Centers (CENAPAD).…”

Section: Discussionmentioning

confidence: 99%

“…The regional meteorological centers download this data and execute local scale simulations to generate weather forecasts for three days ahead, with six hour intervals (four time periods per forecast day). The regional scale simulation generates twenty eight (28) files, but local scale simulation uses only the first twelve (12) of the BRAMS forecast files.…”

Section: The Brazilian Regional Atmospheric Modelling Systemmentioning

confidence: 99%

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Reducing Time Delays in Computing Numerical Weather Models at Regional and Local Levels : A Grid-Based Approach

Almeida¹,

Bauer²

2012

IJGCA

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This paper introduces a grid-based approach to reduce the time to deliver local meteorological forecast information. The computation of local meteorological forecasts relies on the execution of both regional and local scale Numerical Weather Prediction models. Typically, such models require extensive computation on large compute clusters. Moreover, the models are commonly executed sequentially, since local models rely on the output of a regional model. The approach introduced in this paper, modifies the computational dependencies in order to compute the models more in parallel while ensuring that computational results are appropriately synchronized. We evaluate the method in a high performance computing grid using the Brazilian Regional Atmospheric Modelling System (BRAMS). The experimental results show a reduction of up to 71 % in the time to deliver local meteorological information with this approach. The approach is sufficiently general that it can be useful with other large distributed applications.

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Section: Discussionmentioning

confidence: 99%

Section: The Brazilian Regional Atmospheric Modelling Systemmentioning

confidence: 99%

Reducing Time Delays in Computing Numerical Weather Models at Regional and Local Levels : A Grid-Based Approach

Almeida¹,

Bauer²

2012

IJGCA

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“…Network failure is a very serious issue, as a communication in distributed environment is impossible without a network (Das and De Sarkar 2012). Network failure can be due to site failures, link failures, configuration changes, or device failures such as routers or switches (Haider et al 2011).…”

Section: Threats To Grid Dependability: Errors Failures and Faultsmentioning

confidence: 99%

Fault tolerance in computational grids: perspectives, challenges, and issues

Haider

Nazir

2016

SpringerPlus

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Computational grids are established with the intention of providing shared access to hardware and software based resources with special reference to increased computational capabilities. Fault tolerance is one of the most important issues faced by the computational grids. The main contribution of this survey is the creation of an extended classification of problems that incur in the computational grid environments. The proposed classification will help researchers, developers, and maintainers of grids to understand the types of issues to be anticipated. Moreover, different types of problems, such as omission, interaction, and timing related have been identified that need to be handled on various layers of the computational grid. In this survey, an analysis and examination is also performed pertaining to the fault tolerance and fault detection mechanisms. Our conclusion is that a dependable and reliable grid can only be established when more emphasis is on fault identification. Moreover, our survey reveals that adaptive and intelligent fault identification, and tolerance techniques can improve the dependability of grid working environments.

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“…Replication is creating multiple copies of an existing entity [15]. Replication increases availability of resources.…”

Section: Replicationmentioning

confidence: 99%

Replication: A Technique for Scalability in Cloud Computing

Shahapure¹,

Jayarekha²

2015

IJCA

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Cloud computing is a technology which produces and consumes huge amount of data every day. This makes the cloud to store tons of applications. The demand for these resources is on the rise. Multi cloud environment is used to satisfy these demands. If multiple providers cooperatively work together, the availability of resource can be improved. The replication of data across multiple places in cloud has become an effective solution to achieve good performance in terms of load balancing, response time and availability. Replication of data is a good way to achieve reliability and improve performance in a distributed system. The rising popularity of cloud computing is an alternative to classic information processing systems. This has increased the importance of its correct and continuous operation even in the presence of faulty components. Fault tolerance is a major concern to guarantee availability and reliability of critical services as well as application execution. In order to minimize failure impact on the system and application execution, failures should be anticipated and proactively handled.

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On Fault Tolerance of Resources in Computational Grids

Cited by 11 publications

References 18 publications

Reducing Time Delays in Computing Numerical Weather Models at Regional and Local Levels : A Grid-Based Approach

Reducing Time Delays in Computing Numerical Weather Models at Regional and Local Levels : A Grid-Based Approach

Fault tolerance in computational grids: perspectives, challenges, and issues

Replication: A Technique for Scalability in Cloud Computing

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