Distributed computer architectures labeled “peer-to-peer ” are designed for the sharing of computer resources (content, storage, CPU cycles) by direct exchange, rather than requiring the intermediation or support of a centralized server or authority. Peer-to-peer architectures are characterized by their ability to adapt to failures and

Abstract. We present PlanetP, a peer-to-peer (P2P) content search and retrieval infrastructure targeting communities wishing to share large sets of text documents. P2P computing is an attractive model for information sharing between ad hoc groups of users because of its low cost of entry and explicit model for resource scaling. As communities grow, however, a key challenge becomes finding relevant information. To address this challenge, our design centers around indexing, content search, and retrieval rather than scalable name-based object location, which has been the focus of recent P2P systems. PlanetP takes the novel approach of replicating the global directory and a compact summary index at every peer using gossiping. PlanetP then leverages this information to approximate a state-of-the-art document ranking algorithm to help users locate relevant information within the large communal data set. Using a prototype implementation together with simulation, we show: (i) it is possible to design a gossiping algorithm that reliably maintains a copy of communal state at each peer yet requires only a modest amount of bandwidth, (ii) our content search and retrieval algorithm tracks the performance of the original ranking algorithm very closely, giving P2P communities a search and retrieval algorithm as good as that possible assuming a centralized server, and (iii) PlanetP’s gossiping and search and retrieval algorithms both scale well to communities of at least several thousand peers. 1

The ability to efficiently discover information using partial knowledge (for example keywords, attributes or ranges) is important in large, decentralized, resource sharing distributed environments such as computational Grids and Peer-to-Peer (P2P) storage and retrieval systems. This paper presents a P2P information discovery system that supports flexible queries using partial keywords and wildcards, and range queries. It guarantees that all existing data elements that match a query are found with bounded costs in terms of number of messages and number of peers involved. The key innovation is a dimension reducing indexing scheme that effectively maps the multidimensional information space to physical peers. The design, implementation and experimental evaluation of the system are presented.

Abstract not found

Computational grids provide mechanisms for sharing and accessing large and heterogeneous collections of remote resources such as computers, online instruments, storage space, data, and applications. Resources are requested ("discovered") by specifying a set of desired attributes. Resource attributes have various degrees of dynamism, from mostly static attributes, such as operating system version, to highly dynamic ones, such as available network bandwidth or CPU load. Another dimension of dynamism is introduced by variable and highly diverse sharing policies: resources are made available to the grid community based on locally defined and potentially changing policies.

Peer-to-peer (P2P) technology has undergone rapid growth, producing new protocols and applications, many of which enjoy considerable commercial success and academic interest. Yet, P2P applications are often based on complex protocols, whose behavior is not completely understood. We believe that in order to enable an even more widespread adoption of P2P systems in commercial and scientific applications, what is needed is a modular paradigm in which well-understood, predictable components with clean interfaces can be combined to implement arbitrarily complex functions. The goal of this paper is to promote this idea by describing our initial experiences in this direction. Our recent work has resulted in a collection of simple and robust components, which include aggregation and membership management. This paper shows how to combine them to obtain a novel load-balancing algorithm that is close to optimal with respect to load transfer. We also describe briefly our simulation environment, explicitly designed to efficiently support our modular approach to P2P protocol design.

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases.

Abstract—Peer-to-peer computing, the harnessing of idle compute cycles throughout the Internet, offers exciting new research challenges in the converging domains of networking and distributed computing. Our system, Cluster Computing on the Fly, seeks to harvest cycles from ordinary users in an open access, non-institutional environment. We conduct a comprehensive study of generic searching methods in a highly dynamic peer-to-peer environment for locating idle cycles for workpile applications, which are heavy consumers of cycles. We compare four scalable search methods: expanding ring, advertisement-based, random walk and rendezvous point. We model a variety of workloads, simple scheduling strategies and stabilities of hosts. Our preliminary results show that under light workloads, rendezvous point performs best, while under heavy workloads, its performance falls below the other techniques. We expected rendezvous point to consistently outperform the other search techniques because of its inherent advantage in gathering knowledge about the idle cycles. However, in a peer-to-peer environment, which satisfies requests on-demand, large jobs may dominate, resulting in delays for scheduling smaller jobs. I.

Abstract: Over the last few years, several nations around the world have set up Grids to share resources such as computers, data, and instruments to enable collaborative science, engineering, and business applications. These Grids follow a restricted organisational model wherein a Virtual Organisation (VO) is created for a specific collaboration and all interactions such as resource sharing are limited to within the VO. Therefore, dispersed Grid initiatives have led to the creation of disparate Grids with little or no interaction between them. In this paper, we propose a model that: (a) promotes interlinking of islands of Grids through peering arrangements to enable inter-Grid resource sharing; (b) provides a scalable structure for Grids that allow them to interconnect with one another and grow in a sustainable way; (c) creates a global Cyberinfrastructure to support e-Science and e-Business applications. This work identifies and proposes architecture, mechanisms and policies that allow the internetworking of Grids and allows Grids to grow in a similar manner as the Internet. We term the structure resulting from such internetworking between Grids as the InterGrid. The proposed InterGrid architecture is composed of InterGrid Gateways responsible for managing peering arrangements between Grids. We discuss the main components of the architecture and present a research agenda to enable the InterGrid vision.

An overview of the Triana Problem Solving Environment is provided – with a particular focus on the GAP application-level interface, for integration with Grid Computing and Peer-to-Peer infrastructure. GAP is a Javabased subset of the Grid Application Toolkit interface (being implemented in the GridLab project), and an outline of its current functionality, usage and mappings to three supported underlying middleware derivatives: JXTA, Web Services, and P2PS (a simplified Peer-to-Peer platform) are provided. The motivation behind the development of P2PS is given – emphasising its minimal, but effective Peer-to-Peer mechanisms that allow scalable, decentralized discovery and communication amongst cooperating P2PS peers within highly unstable environments. A summary of three application use cases illustrating the range of scenarios that such a system addresses is also provided.