|
Descripción
|
|
|---|---|
| Grids emerged in the last decade as large distributed environments where the greatest challenges of the scientific community could be faced. These challenges, commonly known as grand challenge applications (GCAs), are characterized as problems that, given their size and/or complexity, can not be solved by means of conventional computing techniques. The grid scalability, flexibility and massive computation power make it an ideal environment to face these GCAs. In order to provide the expected service and achieve the required performance for these applications, grids must have powerful management mechanisms that efficiently deal with the natural variability and heterogeneity of the environment. Since the birth of this technology, this has been one of the key aspects of its development and, in many ways, one of the most problematic. Conventional grid management mechanisms try to improve performance based on the individual analysis of every component on the system. Then they intend to adjust the configuration or predict the behavior of each independent element. This approach may seem reasonable considering the large scale and complexity of the grid, but could possibly fail to achieve optimal performance, because in most cases it lacks the capability to understand the effects that different elements have on each other when they work together. From a more theoretical point of view, if we consider ¿the grid¿ as an individual entity (with its computational power, storage capacity and so on), it seems logical to analyze it as such, instead of composed of a huge set of individual resources. This could be similar as how computers are regarded as individual entities, even though they are made of several electronic components of different nature, or how clusters are most times considered as single machines, when in fact they are composed by many computers. In this paper we present a set of techniques oriented to build a global behavioral model of a large scale distributed environment, such as a grid. This kind of model would provide a deep understanding of the system and a better reference for management and optimization. A case study is also presented, in order to provide a validation of this approach. | |
|
Internacional
|
Si |
|
Nombre congreso
|
On the Move to Meaningful Internet Systems: OTM 2008 |
|
Tipo de participación
|
960 |
|
Lugar del congreso
|
Monterrey (México) |
|
Revisores
|
No |
|
ISBN o ISSN
|
978-3-540-88870-3 |
|
DOI
|
10.1007/978-3-540-88871-0_62 |
|
Fecha inicio congreso
|
13/11/2008 |
|
Fecha fin congreso
|
14/11/2008 |
|
Desde la página
|
886 |
|
Hasta la página
|
897 |
|
Título de las actas
|
On the Move to Meaningful Internet Systems: OTM 2008 |