Abstract
A Grid information system resolves queries that may need to consider all information sources (Grid services), which are widely distributed geographically, in order to enable efficient Grid functions that may utilise multiple cooperating services. Fundamentally this can be achieved by either moving the query to the data (query shipping) or moving the data to the query (data shipping). Existing Grid information system implementations have adopted one of the two approaches. This paper explores the two approaches in further detail by evaluating them to the best possible extent with respect to Grid information system benchmarking metrics. A Grid information system that follows the data shipping approach based on the replication of information that aims to improve the currency for highly-mutable information is presented. An implementation of this, based on an Enterprise Messaging System, is evaluated using the benchmarking method and the consequence of the results for the design of Grid information systems is discussed.
Highlights
A fundamental aspect of Grid computing is the need to obtain information about the structure and state of Grid services which are widely distributed geographically
With a sufficiently large number of queries, the caching approach would in any case ship all information from the information sources
The focus should be on efficiently replicating the information from the information source to the information service
Summary
A fundamental aspect of Grid computing is the need to obtain information about the structure and state of Grid services which are widely distributed geographically. The (α, β)-currency metric is used along with real data from a production Grid infrastructure, the Worldwide LHC Computing Grid, to identify the approach that provides the best information consistency taking into account the scalability challenges of a largescale Grid. In this context, information consistency means that on query resolution, the result should accurately reflect the information source (in other words, it should be consistent) even if a time difference exists between when that information was extracted from the information source and when the query was returned to the client.
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