Grid Computing

APRIL: An Application-Aware, Predictive and Intelligent Load Balancing Solution for Data-Intensive Science
In this paper, we propose an application-aware intelligent load balancing system for high-throughput, distributed computing, and …
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Comparative Performance Evaluation of High-performance Data Transfer Tools
Data transfer in wide-area networks has been long studied in different contexts, from data sharing among data centers to online access …
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Large Data Transfer Predictability and Forecasting using Application-Aware SDN
Network management for applications that rely on large-scale data transfers is challenging due to the volatility and the dynamic nature …
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Budget-Optimized Network-Aware Joint Resource Allocation in Grids/Clouds Over Optical Networks
Resource allocation is an important component of many Cloud computing and datacenter management problems. For infrastructure as a …
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A Tabu search based heuristic for optimized joint resource allocation and task scheduling in Grid/Clouds
Nowadays the development of Grid/Cloud networks has accelerated to meet the increasing requirements for large-scale computing, storage …
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Budget-Minimized Resource Allocation and Task Scheduling in Distributed Grid/Clouds
The need for large-scale computing, storage and network capabilities by the scientific or business community has resulted in the …
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A Tabu Search Approach for Joint Scheduling of Resources in a Lambda Grid Network
Advanced distributed applications in engineering, scientific and business domains that are highly data-intensive demand …
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Joint Computing and Network Resource Scheduling in a Lambda Grid Network
Data-intensive grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs …
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Dynamic and Deterministic Lightpath Scheduling in Next-Generation WDM Optical Networks
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