Hossein Deldari
Ferdowsi University of Mashhad
62 Papers
254 Citations
Hossein Deldari is an academic researcher from Ferdowsi University of Mashhad. The author has contributed to research in topics: Grid & Scheduling (computing). The author has an hindex of 10, co-authored 62 publications. Previous affiliations of Hossein Deldari include Islamic Azad University.
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Papers
Scheduling of scientific workflows using a chaos-genetic algorithm
Golnar Gharooni-fard,Fahime Moein-darbari,Hossein Deldari,Anahita Morvaridi +3 more
- 01 May 2010
TL;DR: A novel genetic algorithm called chaos-genetic algorithm is used to solve the scheduling problem considering both user’s budget and deadline and showed greater performances of CGS compared to traditional genetic algorithm (TGS) on both balanced and unbalanced workflows.
Job failure prediction in grid environment based on workload characteristics
Hamid Fadishei,Hamid Saadatfar,Hossein Deldari +2 more
- 08 Dec 2009
TL;DR: By analyzing grid workload traces and extracting patterns describing common failure characteristics, the success or failure status of jobs during 6 months of AuverGrid activity was predicted with around 96% accuracy.
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Balancing Load in a Computational Grid Applying Adaptive, Intelligent Colonies of Ants
TL;DR: A new concept called Ant level load balancing is presented here for improving the performance of the mechanism and theoretical analyses, supported with experiment results, prove that this new mechanism surpasses its predecessor.
Localization in wireless sensor networks using tabu search and simulated annealing
S. Kazem Shekofteh,Mohammad Hossien Yaghmaee,Maryam Baradaran Khalkhali,Hossein Deldari +3 more
- 19 Apr 2010
TL;DR: This paper proposes a method in which the localization is done through two steps, in which tabu search is used to obtain an accurate estimation of the nodes' location and simulated annealing algorithm is use to refine the location estimates of those nodes that are likely to have flip ambiguity problem.
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CycloidGrid: A proximity-aware P2P-based resource discovery architecture in volunteer computing systems
TL;DR: A proximity-aware resource discovery architecture for peer-to-peer based volunteer computing systems that improves the response time of user's requests by a factor of 4.04 under a moderate load.
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