Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Computational grids have the potential for solving scientific and large -scale problems using heterogeneous and geographically distributed resources. In addition to the challenges of managing and scheduling resources reliable challenges arise because the grid infrastructure is unreliable. There are two major problems in Scheduling the Grid 1) Efficient Scheduling of jobs, 2) Providing fault tolerance in a reliable manner. Most of the existing strategies do not provide fault tolerance. There are some algorithms which provide fault tolerance but, they do a large amount of redundant computation to provide fault tolerance. This paper addresses this issue and minimizes redundant work by using a group level table of data. This technique is suitable for partitioning and group scheduling of jobs.
K. Srikala. 2013. \u201cFault Tolerant Scheduling of Partitioned and Grouped Jobs in Grid Computing (FTPG)\u201d. Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 13 (GJCST Volume 13 Issue B2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Computational grids have the potential for solving scientific and large -scale problems using heterogeneous and geographically distributed resources. In addition to the challenges of managing and scheduling resources reliable challenges arise because the grid infrastructure is unreliable. There are two major problems in Scheduling the Grid 1) Efficient Scheduling of jobs, 2) Providing fault tolerance in a reliable manner. Most of the existing strategies do not provide fault tolerance. There are some algorithms which provide fault tolerance but, they do a large amount of redundant computation to provide fault tolerance. This paper addresses this issue and minimizes redundant work by using a group level table of data. This technique is suitable for partitioning and group scheduling of jobs.
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