The high bandwidth and low latency of the modern internet has made possible the deployment of distributed computing platforms. The XenoServer platform provides a distributed computing platform open to all and presents three major new challenges for resource discovery: Firstly, network location is key for effectively provisioning services, to mitigate against high-latency, high-load or component failure. Secondly, many services require a presence on several servers, with inter-related requirements. Finally, as the platform is open with respect to users and servers, large numbers of queries and updates are expected. To address these requirements we introduce and evaluate Xeno-Search, a new distributed service for selecting the machines to host components of multi-node distributed systems and which is uniquely able to express and efficiently answer complex queries with inter-related location constraints. We demonstrate that Xeno-Search represents a trade-off between accuracy and query time which avoids exhaustive search and supports multiple resources. In addition the performance of the algorithm and the quality of its server selections is investigated and the performance of the distributed service shown to be invariant as the number of nodes or items indexed increases.

Efficient Resource discovery mechanism is one of the fundamental requirement for Grid computing systems, as it aids in resource management and scheduling of applications. Resource discovery activity involve searching for the appropriate resource types that match the user’s application requirements. Various kinds of solutions to grid resource discovery have been suggested, including the centralised and hierarchical information server approach. However, both of these approaches have serious limitations in regards to scalability, fault-tolerance and network congestion. To overcome these limitations, indexing resource information using a decentralised (such as Peer-to-Peer (P2P)) network model has been actively proposed in the past few years. This article investigates various decentralised resource discovery techniques primarily driven by P2P network model. To summarise, this article presents a: (i) summary of current state of art in grid resource discovery; (ii) resource taxonomy with focus on computational grid paradigm; (iii) P2P taxonomy with focus on extending the current structured systems (such as Distributed Hash Tables) for indexing d-dimensional grid resource queries; (iv) detailed survey of existing works that can support d-dimensional grid resource queries; and (v) classification of the surveyed approaches based on the proposed P2P taxonomy. We believe that this taxonomy and its mapping to relevant systems would be useful for academic and industry based researchers who are engaged in the design of scalable Grid and P2P systems. 1

Efficient Resource discovery mechanism is one of the fundamental requirement for Grid computing systems, as it aids in resource management and scheduling of applications. Resource discovery activity involve searching for the appropriate resource types that match the user’s application requirements. Various kinds of solutions to grid resource discovery have been suggested, including the centralised and hierarchical information server approach. However, both of these approaches have serious limitations in regards to scalability, fault-tolerance and network congestion. To overcome these limitations, indexing resource information using a decentralised (such as Peer-to-Peer (P2P)) network model has been actively proposed in the past few years. This article investigates various decentralised resource discovery techniques primarily driven by P2P network model. To summarise, this article presents a: (i) summary of current state of art in grid resource discovery; (ii) resource taxonomy with focus on computational grid paradigm; (iii) P2P taxonomy with focus on extending the current structured systems (such as Distributed Hash Tables) for indexing d-dimensional grid resource queries 1; (iv) detailed survey of existing works that can support d-dimensional grid resource queries; and (v) classification of the surveyed approaches based on the proposed P2P taxonomy. We believe that this taxonomy and its mapping to relevant systems would be useful for academic and industry based researchers who are engaged in the design of scalable Grid and P2P systems. 1

In this paper we investigate the interdomain connectivity of PlanetLab nodes. We note that about 85 percent of the hosts are located within what we call the Global Research and Educational Network (GREN) --- an interconnected network of high speed research networks such as Internet2 in the USA and Dante in Europe. Since traffic with source and destination on the GREN is very likely to be transited solely by the GREN, this means that over 70 percent of the end-to-end measurements between PlanetLab node pairs represent measurements of GREN characteristics. We suggest that it may be possible to systematically choose the placement of new nodes so that as the PlanetLab platform grows it becomes a closer and closer approximation to the Global Internet.