P2P-based resource discovery in dynamic grids allowing multi-attribute and range queries

A key point for the efficient use of large grid systems is the discovery of resources, and this task becomes more complicated as the size of the system grows up. In this case, large amounts of information on the available resources must be stored and kept up-to-date along the system so that it can be queried by users to find resources meeting specific requirements (e.g. a given operating system or available memory). Thus, three tasks must be performed, (1) information on resources must be gathered and processed, (2) such processed information has to be disseminated over the system, and (3) upon users' requests, the system must be able to discover resources meeting some requirements using the processed information. This paper presents a new technique for the discovery of resources in grids which can be used in the case of multi-attribute (e.g. {OS = Linux & memory = 4 GB}) and range queries (e.g. {50 GB < disk-space < 100 GB}). This technique relies on the use of content summarisation techniques to perform the first task mentioned before and strives at the main drawback found in proposals from literature using summarization. This drawback is related to scalability, and is tackled by means of using Peer-to-Peer (P2P) techniques, namely Routing Indices (RIs), to perform the second and third tasks. Another contribution of this work is a performance evaluation conducted by means of simulations of the EU DataGRID Testbed which shows the usefulness of this approach compared to other proposals from literature. More specifically, the technique presented in this paper improves on the scalability and produces good performance. Besides, the parameters involved in the summary creation have been tuned and the most suitable values for the presented test case have been found. (C) 2013 Elsevier B.V. All rights reserved.