Published: Oct 1, 2019
Converted to Gold OA:
DOI: 10.4018/IJIRR.20191001.pre
Volume 9
Hadj Ahmed Bouarara, Reda Mohamed Hamou
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MLA
Bouarara, Hadj Ahmed, and Reda Mohamed Hamou. "Special Issue on Advanced Research in Internet of Things (IoT): Applications, Services, and Implementations." IJIRR vol.9, no.4 2019: pp.4-6. http://doi.org/10.4018/IJIRR.20191001.pre
APA
Bouarara, H. A. & Hamou, R. M. (2019). Special Issue on Advanced Research in Internet of Things (IoT): Applications, Services, and Implementations. International Journal of Information Retrieval Research (IJIRR), 9(4), 4-6. http://doi.org/10.4018/IJIRR.20191001.pre
Chicago
Bouarara, Hadj Ahmed, and Reda Mohamed Hamou. "Special Issue on Advanced Research in Internet of Things (IoT): Applications, Services, and Implementations," International Journal of Information Retrieval Research (IJIRR) 9, no.4: 4-6. http://doi.org/10.4018/IJIRR.20191001.pre
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Published: Oct 1, 2019
Converted to Gold OA:
DOI: 10.4018/IJIRR.2019100101
Volume 9
Mohammed Benhammouda, Mimoun Malki
Cloud computing is considered a new way to use on-demand computing resources. When executing a workflow process in such an environment, task scheduling, a well-known NP-hard problem is a very...
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Cloud computing is considered a new way to use on-demand computing resources. When executing a workflow process in such an environment, task scheduling, a well-known NP-hard problem is a very important step. Many heuristic algorithms have been proposed to solve this problem. In this article, the authors present a GPU-based approach for solving the workflow scheduling problem. The main idea of the approach is to implement a massively parallel version of the simulated annealing algorithm, in an asynchronous way where no information is exchanged among parallel runs. The proposed approach, called PSA algorithm, is against another well-established scheduling HEFT heuristic. Experiments with randomly generated graphs show a much better performance from the proposed approach.
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Benhammouda, Mohammed, and Mimoun Malki. "A GPU Based Approach for Solving the Workflow Scheduling Problem." IJIRR vol.9, no.4 2019: pp.1-12. http://doi.org/10.4018/IJIRR.2019100101
APA
Benhammouda, M. & Malki, M. (2019). A GPU Based Approach for Solving the Workflow Scheduling Problem. International Journal of Information Retrieval Research (IJIRR), 9(4), 1-12. http://doi.org/10.4018/IJIRR.2019100101
Chicago
Benhammouda, Mohammed, and Mimoun Malki. "A GPU Based Approach for Solving the Workflow Scheduling Problem," International Journal of Information Retrieval Research (IJIRR) 9, no.4: 1-12. http://doi.org/10.4018/IJIRR.2019100101
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Published: Oct 1, 2019
Converted to Gold OA:
DOI: 10.4018/IJIRR.2019100102
Volume 9
Fatima Ardjani, Djelloul Bouchiha
The ontology alignment process aims at generating a set of correspondences between entities of two ontologies. It is an important task, notably in the semantic web research, because it allows the...
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The ontology alignment process aims at generating a set of correspondences between entities of two ontologies. It is an important task, notably in the semantic web research, because it allows the joint consideration of resources defined in different ontologies. In this article, the authors developed an ontology alignment system called ABCMap+. It uses an optimization method based on artificial bee colonies (ABC) to solve the problem of optimizing the aggregation of three similarity measures of different matchers (syntactic, linguistic and structural) to obtain a single similarity measure. To evaluate the ABCMap+ ontology alignment system, authors considered the OAEI 2012 alignment system evaluation campaign. Experiments have been carried out to get the best ABCMap+'s alignment. Then, a comparative study showed that the ABCMap+ system is better than participants in the OAEI 2012 in terms of Recall and Precision.
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Ardjani, Fatima, and Djelloul Bouchiha. "A New Approach Based on the Bee Optimization Algorithm for Ontology Alignment: ABCMap+." IJIRR vol.9, no.4 2019: pp.13-22. http://doi.org/10.4018/IJIRR.2019100102
APA
Ardjani, F. & Bouchiha, D. (2019). A New Approach Based on the Bee Optimization Algorithm for Ontology Alignment: ABCMap+. International Journal of Information Retrieval Research (IJIRR), 9(4), 13-22. http://doi.org/10.4018/IJIRR.2019100102
Chicago
Ardjani, Fatima, and Djelloul Bouchiha. "A New Approach Based on the Bee Optimization Algorithm for Ontology Alignment: ABCMap+," International Journal of Information Retrieval Research (IJIRR) 9, no.4: 13-22. http://doi.org/10.4018/IJIRR.2019100102
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Published: Oct 1, 2019
Converted to Gold OA:
DOI: 10.4018/IJIRR.2019100103
Volume 9
Kouidri Siham, Yagoubi Belabbas
Cloud computing is a powerful and high-capacity system, because it can satisfy various demands and share resources for users. It also to benefits from a capacity for treatment and unlimited storage....
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Cloud computing is a powerful and high-capacity system, because it can satisfy various demands and share resources for users. It also to benefits from a capacity for treatment and unlimited storage. However, it is burdensome for the providers of internet services that the user demands are increasing as computer capacity is growing stronger and stronger. Therefore, the techniques of workflow scheduling and data replication are used to decrease the costs of the data intensive application. Unfortunately, these two approaches, which are very complementary, are used separately. In this article, a combination of workflow scheduling based on the clustering of data and dynamic data replication strategies has been introduced together. A Cloud simulator, Cloudsim, is used to evaluate the performance of the proposed algorithm. Simulation results show the effectiveness of the proposed algorithm in comparison with well-known algorithms such as random data placement and the Build Time algorithm.
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Siham, Kouidri, and Yagoubi Belabbas. "Combination of Scheduling and Dynamic Data Replication for Cloud Computing Workflows." IJIRR vol.9, no.4 2019: pp.23-35. http://doi.org/10.4018/IJIRR.2019100103
APA
Siham, K. & Belabbas, Y. (2019). Combination of Scheduling and Dynamic Data Replication for Cloud Computing Workflows. International Journal of Information Retrieval Research (IJIRR), 9(4), 23-35. http://doi.org/10.4018/IJIRR.2019100103
Chicago
Siham, Kouidri, and Yagoubi Belabbas. "Combination of Scheduling and Dynamic Data Replication for Cloud Computing Workflows," International Journal of Information Retrieval Research (IJIRR) 9, no.4: 23-35. http://doi.org/10.4018/IJIRR.2019100103
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Published: Oct 1, 2019
Converted to Gold OA:
DOI: 10.4018/IJIRR.2019100104
Volume 9
Vasantha Thangasamy
Information available on the internet is wide, diverse, and dynamic. Since an enormous amount of information is available online, finding similarity between webpages using efficient hyperlink...
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Information available on the internet is wide, diverse, and dynamic. Since an enormous amount of information is available online, finding similarity between webpages using efficient hyperlink analysis is a challenging task. In this article, the researcher proposes an improved PageSim algorithm which measurse the importance of a webpage based on the PageRank values of connected webpage. Therefore, the proposed algorithm uses heterogeneous propagation of the PageRank score, based on the prestige measure of each webpage. The existing and the improved PageSim algorithms are implemented with a sample web graph. Real time Citation Networks, namely the ZEWAIL Citation Network and the DBLP Citation Network are used to test and compare the existing and improved PageSim algorithms. By using this proposed algorithm, it has been found that a similarity score between two different webpages significantly increases based on common information features and significantly decreases based on distinct factors.
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