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Journal ArticleDOI

Job scheduling and data replication on data grids

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TLDR
A job scheduling policy called HCS (Hierarchical Cluster Scheduling), and a dynamic data replication strategy, called HRS (Hiersarchical Replication Strategy), to improve the data access efficiencies in a cluster grid are developed and implemented.
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This article is published in Future Generation Computer Systems.The article was published on 2007-08-01. It has received 132 citations till now. The article focuses on the topics: Data grid & Data access.

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Citations
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Journal ArticleDOI

An ant algorithm for balanced job scheduling in grids

TL;DR: A Balanced Ant Colony Optimization (BACO) algorithm for job scheduling in the Grid environment is proposed to balance the entire system load while trying to minimize the makespan of a given set of jobs.
Journal ArticleDOI

A dynamic data replication strategy using access-weights in data grids

TL;DR: A dynamic data replication mechanism called Latest Access Largest Weight (LALW), which selects a popular file for replication and calculates a suitable number of copies and grid sites for replication, and successfully increases the effective network usage.
Journal ArticleDOI

Improving job scheduling algorithms in a grid environment

TL;DR: A hierarchical framework and a job scheduling algorithm called Hierarchical Load Balanced Algorithm (HLBA) for Grid environment is proposed and Experimental results show that the performance of HLBA is better than those of other algorithms.
Journal ArticleDOI

Data Replication in Data Intensive Scientific Applications with Performance Guarantee

TL;DR: This paper designs a polynomial time centralized replication algorithm that reduces the total data file access delay by at least half of that reduced by the optimal replication solution, and designs a distributed caching algorithm, which can be easily adopted in a distributed environment such as Data Grids.
Journal ArticleDOI

A Bee Colony based optimization approach for simultaneous job scheduling and data replication in grid environments

TL;DR: This paper presents a novel Bee Colony based optimization algorithm, named Job Data Scheduling using Bee Colony (JDS-BC), which consists of two collaborating mechanisms to efficiently schedule jobs onto computational nodes and replicate datafiles on storage nodes in a system so that the two independent, and in many cases conflicting, objectives are concurrently minimized.
References
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Journal ArticleDOI

The network weather service: a distributed resource performance forecasting service for metacomputing

TL;DR: The current implementation of the NWS for Unix and TCP/IP sockets is described and examples of its performance monitoring and forecasting capabilities are provided.
Book

Fat-trees: universal networks for hardware-efficient supercomputing

TL;DR: In this article, the authors presented a new class of universal routing networks, called fat-trees, which might be used to interconnect the processors of a general-purpose parallel supercomputer, and proved that a fat-tree of a given size is nearly the best routing network of that size.
Journal ArticleDOI

The data grid

TL;DR: In this paper, the authors introduce design principles for a data management architecture called the data grid, and describe two basic services that are fundamental to the design of a data grid: storage systems and metadata management.
Journal ArticleDOI

Fat-trees: Universal networks for hardware-efficient supercomputing

TL;DR: In this article, the authors presented a new class of universal routing networks, called fat-trees, which might be used to interconnect the processors of a general-purpose parallel supercomputer, and proved that a fat-tree of a given size is nearly the best routing network of that size.
Proceedings ArticleDOI

Matchmaking: distributed resource management for high throughput computing

TL;DR: The classified advertisement (classad) matchmaking framework is developed and implemented, a flexible and general approach to resource management in distributed environment with decentralized ownership of resources.
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