We present a Scalable Distributed Information Management System (SDIMS) that aggregates information about large-scale networked systems and that can serve as a basic building block for a broad range of large-scale distributed applications by providing detailed views of nearby information and summary views of global information. To serve as a basic building block, a SDIMS should have four properties: scalability to many nodes and attributes, flexibility to accommodate a broad range of applications, administrative isolation for security and availability, and robustness to node and network failures. We design, implement and evaluate a SDIMS that (1) leverages Distributed Hash Tables (DHT) to create scalable aggregation trees, (2) provides flexibility through a simple API that lets applications control propagation of reads and writes, (3) provides administrative isolation through simple extensions to current DHT algorithms, and (4) achieves robustness to node and network reconfigurations through lazy reaggregation, on-demand reaggregation, and tunable spatial replication. Through extensive simulations and micro-benchmark experiments, we observe that our system is an order of magnitude more scalable than existing approaches, achieves isolation properties at the cost of modestly increased read latency in comparison to flat DHTs, and gracefully handles failures.

Most current peer-to-peer lookup schemes keep a small amount of routing state per node, typically logarithmic in the number of overlay nodes. This design assumes that routing information at each member node must be kept small, so that the bookkeeping required to respond to system membership changes is also small, given that aggressive membership dynamics are expected. As a consequence, lookups have high latency as each lookup requires contacting several nodes in sequence. In this paper, we question these...

In this position paper, we present an efficient algorithm for performing a broadcast operation with minimal cost in structured DHT-based P2P networks. In a system of N nodes, a broadcast message originating at an arbitrary node reaches all other nodes after exactly N-1 messages. We emphasize the perception of a class of DHT systems as a form of distributed k-ary search and we take advantage of that perception in constructing a spanning tree that is utilized for ecient broadcasting. We consider broadcasting as a basic service that adds to existing DHTs the ability to search using arbitrary queries as well as dissiminate/collect global information.

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A `second generation' approach to the provision of Grid middleware is now emerging which is built on service-oriented architecture and web services standards and technologies. However, advanced Grid applications have significant demands that are not addressed by present-day web services platforms. As one prime example, current platforms do not support the rich diversity of communication `interaction types' that are demanded by advanced applications (e.g. publish-subscribe, media streaming, peer-to-peer interaction).

Providers of dynamic Web applications are currently unable to accommodate heavy usage without significant investment in infrastructure and in-house management capability. Our goal is to develop technology to enable a third party to offer scalability as a subscription service with "per-click" pricing to application providers. To this end we have developed a prototype proxy caching system able to scale delivery of dynamic Web content to a large number of users.

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In this paper, we present a scalable Peer-to-Peer RDF repository, named RDF-Peers, which stores each triple in a multi-attribute addressable network by applying globally known hash functions. Queries can be efficiently routed to the nodes that store matching triples. RDFPeers also supports users to selectively subscribe to RDF content. In RDFPeers, both the neighbors per node and the routing hops for triple insertion, most query resolution and triple subscription are logarithmic to the network size. Our experiments with real-world RDF data demonstrated that the triple-storing load among nodes in RDFPeers differs by less than an order of magnitude.

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We introduce Nemo, a novel peer-to-peer multicast protocol that achieves high delivery ratio without sacrificing end-toend latency or incurring additional costs. Based on two simple techniques: (1) co-leaders to minimize dependencies and, (2) triggered negative acknowledgments (NACKs) to detect lost packets, Nemo’s design emphasizes conceptual simplicity and minimum dependencies, thus achieving performance characteristics capable of withstanding the natural instability of its target environment. We present an extensive comparative evaluation of our protocol through simulation and wide-area experimentation. We contrast the scalability and performance of Nemo with that of three alternative protocols: Narada, Nice and Nice-PRM. Our results show that Nemo can achieve delivery ratios similar to those of comparable protocols under high failure rates, but at a fraction of their cost in terms of duplicate packets (reductions> 90%) and control-related traffic. Keywords: Resilient Multicast, Peer-to-Peer Multicast, Scalable Multicast 1.