Informatica Journal (Impact Factor: 1.63), May 2013
The dynamic nature of grid resources and the demands of users produce complexity in the grid sche... more The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with other meta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm that combines a GA and the gravitational emulation local search (GELS) algorithm denotes GGA. The noteworthy feature of the proposed optimal scheduler is that it decreases run-time and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods shows that it produces more optimal computation time.
Informatica Journal (Impact Factor: 1.63), Jun 2013
The dynamic nature of grid resources and the demands of users produce complexity in the grid sche... more The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with other meta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm that combines a GA and the gravitational emulation local search (GELS) algorithm denotes GGA. The noteworthy feature of the proposed optimal scheduler is that it decreases run-time and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods shows that it produces more optimal computation time.
Feature weighting is a technique used to approximate the optimal degree of influence of individua... more Feature weighting is a technique used to approximate the optimal degree of influence of individual features. This paper presents a feature weighting method for Document Image Retrieval System (DIRS) based on keyword spotting. In this method, we weight the features using Weighted Principal Component Analysis (PCA). The purpose of PCA is to reduce the dimensionality of the data space to the smaller intrinsic dimensionality of feature space (independent variables), which are needed to describe the data economically. This is the case when there is a strong correlation between variables. The aim of this paper is to show feature weighting effect on increasing the performance of DIRS. After applying the feature weighting method to DIRS the average precision is 92.1% and average recall become 97.7% respectively.
Reo is a Coordination Language which is Channel Based that is used in order to connect components... more Reo is a Coordination Language which is Channel Based that is used in order to connect components and is able to send certain Data through connectors. Most simple Connectors in Reo are Channels. Reo proffers a pattern for composition of Components that can be used as a language for coordinating parallel applications. Reo has been stated crisp for communication and connecting Components and cooperation of Data and non-crisp side of sending Data has not been proffered. Whereas certain applications have non-crisp side and it is not possible to apply them by Reo, therefore in this paper non-crisp side of sending Data by making fuzzy Reo Channel by using fuzzy rules is proposed.
The dynamic nature of grid resources and the demands of users produce complexity in the grid sche... more The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with other meta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm GCA that combines GA and the gravitational emulation local search (GELS) algorithm. The noteworthy feature of the proposed optimal scheduler is that it decreases runtime and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods shows that it produces more optimal computation time.
Informatica Journal (Impact Factor: 1.63), May 2013
The dynamic nature of grid resources and the demands of users produce complexity in the grid sche... more The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with other meta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm that combines a GA and the gravitational emulation local search (GELS) algorithm denotes GGA. The noteworthy feature of the proposed optimal scheduler is that it decreases run-time and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods shows that it produces more optimal computation time.
Informatica Journal (Impact Factor: 1.63), Jun 2013
The dynamic nature of grid resources and the demands of users produce complexity in the grid sche... more The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with other meta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm that combines a GA and the gravitational emulation local search (GELS) algorithm denotes GGA. The noteworthy feature of the proposed optimal scheduler is that it decreases run-time and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods shows that it produces more optimal computation time.
Feature weighting is a technique used to approximate the optimal degree of influence of individua... more Feature weighting is a technique used to approximate the optimal degree of influence of individual features. This paper presents a feature weighting method for Document Image Retrieval System (DIRS) based on keyword spotting. In this method, we weight the features using Weighted Principal Component Analysis (PCA). The purpose of PCA is to reduce the dimensionality of the data space to the smaller intrinsic dimensionality of feature space (independent variables), which are needed to describe the data economically. This is the case when there is a strong correlation between variables. The aim of this paper is to show feature weighting effect on increasing the performance of DIRS. After applying the feature weighting method to DIRS the average precision is 92.1% and average recall become 97.7% respectively.
Reo is a Coordination Language which is Channel Based that is used in order to connect components... more Reo is a Coordination Language which is Channel Based that is used in order to connect components and is able to send certain Data through connectors. Most simple Connectors in Reo are Channels. Reo proffers a pattern for composition of Components that can be used as a language for coordinating parallel applications. Reo has been stated crisp for communication and connecting Components and cooperation of Data and non-crisp side of sending Data has not been proffered. Whereas certain applications have non-crisp side and it is not possible to apply them by Reo, therefore in this paper non-crisp side of sending Data by making fuzzy Reo Channel by using fuzzy rules is proposed.
The dynamic nature of grid resources and the demands of users produce complexity in the grid sche... more The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with other meta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm GCA that combines GA and the gravitational emulation local search (GELS) algorithm. The noteworthy feature of the proposed optimal scheduler is that it decreases runtime and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods shows that it produces more optimal computation time.
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Papers by Reza Tavoli