An Importance-Aware Architecture for Large-Scale Grid Information Services

This paper is concerned with the scalability of large-scale grid monitoring and information services, which are mainly used for the discovery of resources of interest. Large-scale grid monitoring systems have to balance between three competing performance metrics: query response time, imposed network overhead, and information freshness. Improving one of the three metrics will affect another; any solution will be based on a trade-off. The paper is motivated by the observation that existing grid monitoring systems can only be manually configured for a trade-off among the three metrics, which applies equally to all monitored resources; this implies that all resources in a grid are considered to be of equal importance. Assuming that in a large-scale grid setting this is unlikely to hold, the paper proposes an importance-based monitoring architecture for large-scale grid information services, based on an adaptation of the web crawling paradigm. The main idea is that , since not all resources are of equal importance, one can vary the trade-off based on the relative importance of the monitored resources. The proposed architecture is described and evaluated based on large-scale deployments of a prototype implementation on PlanetLab.