XMatch: A language for satisfaction-based selection of Grid services

Grid systems enable the sharing of a large number of geographically-dispersed resources among different communities of users. They require a mapping functionality for the association of users requests expressed in terms of requirements and preferences to actual resources. This functionality should deal with a potentially high number of similar resources and with the diversity of the perceived satisfactions of users. We propose XMatch, a query language enabling the expression of the user request in terms of the expected satisfaction over XML-based representation of available resources. This language offers a compact way for users to express their preferences for Grid resources and enable the maximization of the global preference

XMatch: A Language for Satisfaction-Based Selection of Grid Services

Grid systems enable the sharing of a large number of geographically-dispersed resources among different communities of users. They require a mapping functionality for the association of users requests expressed in terms of requirements and preferences to actual resources. This functionality should deal with a potentially high number of similar resources and with the diversity of the perceived satisfactions of users. We propose XMatch, a query language enabling the expression of the user request in terms of the expected satisfaction over XML-based representation of available resources. This language offers a compact way for users to express their preferences for Grid resources and enable the maximization of the global preference

Monitoring the connectivity of a Grid

Grid computing is a new paradigm that enables the distributed coordination of resources and services which are geographically dispersed, span multiple trust domains and are heterogeneous. Network infrastructure monitoring, while vital for activities such as service selection, exhibits inherent scalability problems: in principle, in a Grid composed of n resources, we need to keep record of n2 end-to-end paths. We introduce an approach to network monitoring that takes into account scalability: a Grid is partitioned into domains, and network monitoring is limited to the measurement of domain-to-domain connectivity. However, partitions must be consistent with network performance, since we expect that an observed network performance between domains is representative of the performance between the Grid Services included into domains

ABSTRACT Monitoring the Connectivity of a Grid

Grid computing is a new paradigm that enables the distributed coordination of resources and services which are geographically dispersed, span multiple trust domains and are heterogeneous. Network infrastructure monitoring, while vital for activities such as service selection, exhibits inherent scalability problems: in principle, in a Grid composed of n resources, we need to keep record of n 2 end-to-end paths. We introduce an approach to network monitoring that takes into account scalability: a Grid is partitioned into domains, and network monitoring is limited to the measurement of domain-to-domain connectivity. However, partitions must be consistent with network performance, since we expect that an observed network performance between domains is representative of the performance between the Grid Services included into domains