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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Traboulsi, S. Ortiz, A. Jorda, J. M'zoughi, A. |
| Copyright Year | 2008 |
| Description | Author affiliation: Inst. de Rech. en Inf. de Toulouse, Univ. Paul Sabatier Toulouse III, Toulouse (Traboulsi, S.; Ortiz, A.; Jorda, J.; M'zoughi, A.) |
| Abstract | This work is part of the ViSaGe project. This project concerns the storage virtualization applied in the grid environment. Its goal is to create and manage virtual storage resources by aggregating geographically distributed physical storage resources shared on a Grid. To these shared resources, a quality of service will be associated and related to the data storage performance. In a Grid environment, sharing resources may improve performances if these resources are well managed and if the management software obtains sufficient knowledge about the grid resources workload (computing nodes, storage nodes and links). The grid resources workload is mainly perceived by a monitoring system. Several existing monitoring systems are available for monitoring the grid resources and applications. Each one provides informations according to its aim. For example, Network Weather Service [6] is designed to monitor grid computing nodes and links. On the other hand, Netlogger [8] monitors grid resources and applications in order to detect application's bottleneck. These systems are useful for a post mortem analysis. However, in ViSaGe, we need a system that analyzes the necessary nodes state during execution time. This system is represented by the ViSaGe Administration and monitoring service "Admon". In this paper, we present our scalable distributed system: Admon. Admon traces applications, and calculates the system resources consumption (CPU, Disks, Links). Its originality consists in providing a new opportunity to improve virtual data storage performance by using workload's constraints (e.g., maximum CPU usage percentage). Many constraints will be discussed (such as time's constraint). These constraints allow performance improvement by assigning nodes to the ViSaGe's jobs in an effective manner. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 255437 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424417513 |
| DOI | 10.1109/ICTTA.2008.4530214 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-04-07 |
| Publisher Place | Syria |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Memory Quality of service Software performance Grid Knowledge management storage resources virtualization Application software monitoring Environmental management storage resources management Grid computing Resource management Time factors Monitoring |
| Content Type | Text |
| Resource Type | Article |
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