In today’s chaotic network, data and services are mobile and replicated widely for availability, durability, and locality. Components within this infrastructure interact in rich and complex ways, greatly stressing traditional approaches to name service and routing. This paper explores an alternative to traditional approaches called Tapestry. Tapestry is an overlay location and routing infrastructure that provides location-independent routing of messages directly to the closest copy of an object or service using only point-to-point links and without centralized resources. The routing and directory information within this infrastructure is purely soft state and easily repaired. Tapestry is self-administering, faulttolerant, and resilient under load. This paper presents the architecture and algorithms of Tapestry and explores their advantages through a number of experiments. 1

Despite recent excitement generated by the P2P paradigm and despite surprisingly fast deployment of some P2P applications, there are few quantitative evaluations of P2P systems behavior. Due to its' open architecture and achieved scale, Gnutella is an interesting P2P architecture case study. Gnutella, like most other P2P applications, builds' at the application level a virtual network with its' own routing mechanisms. The topology of this virtual network and the routing mechanisms used have a significant influence on application properties such as performance, reliability, and scalability. We built a 'crawler' to extract the topology of Gnutella's application level network. In this' paper we analyze the topology graph and evaluate generated network traffic. We find that although Gnutella is' not a pure power-law network, its' current configuration has the benefits' and drawbacks' of a power-law structure. These findings lead us to propose changes to Gnutella protocol and implementations that bring significant performance and scalability improvements'.

In wide area computing systems, it is often desirable to create remote read-only copies (replicas) of files. Replication can be used to reduce access latency, improve data locality, and/or increase robustness, scalability and performance for distributed applications. We define a replica location service (RLS) as a system that maintains and provides access to information about the physical locations of copies. An RLS typically functions as one component of a data grid architecture. This paper makes the following contributions. First, we characterize RLS requirements. Next, we describe a parameterized architectural framework, which we name Giggle (for GIGa-scale Global Location Engine), within which a wide range of RLSs can be defined. We define several concrete instantiations of this framework with different performance characteristics. Finally, we present initial performance results for an RLS prototype, demonstrating that RLS systems can be constructed that meet performance goals.

Peer-to-peer systems are gaining popularity as a means to effectively share huge, massively distributed data collections. An important challenge in this context is discovering the appropriate data and services. In this paper, we consider peers that store XML documents. We show how an extension of traditional Bloom filters, called multi-level Bloom filters, can be used to route path queries in such a system. Two alternative ways are considered for building overlay networks of peers: one based on network proximity and one based on content similarity. Content similarity is derived from the similarity among filters. Our experimental results show that networks based on content similarity outperform those formed based on network proximity for finding all matching documents. 1.

We describe a decentralized, adaptive mechanism for replica location in wide-area distributed systems. Unlike traditional, hierarchical (e.g, DNS) and more recent (e.g., CAN, Chord, Gnutella) distributed search and indexing schemes, nodes in our location mechanism do not route queries, instead, they organize into an overlay network and distribute location information. We contend that this approach works well in environments where replica location queries are prevalent but the dynamic component of the system (e.g., node and network failures, replica add/delete operations) cannot be neglected. We argue that a replica location mechanism that combines probabilistic representations of replica location information with soft-state protocols and a flat overlay network of nodes brings important benefits: genuine decentralization, low query latency, and flexibility to introduce adaptive communication schedules. We support these claims in two ways. First, we provide a rough resource consumption evaluation: we show that, for environments similar to those encountered in large scientific data analysis projects, generated network traffic is limited and, more importantly, is comparable to the traffic generated by a request routing scheme. Second, we provide encouraging performance data from a prototype implementation. 1.

Abstract — A bloom filter is a simple, space-efficient, randomized data structure for concisely representing a static data set, in order to support approximate membership queries. It has great potential for distributed applications where systems need to share information about what resources they have. The space efficiency is achieved at the cost of a small probability of false positive in membership queries. However, for many applications the space savings and short locating time consistently outweigh this drawback. In this paper, we introduce dynamic bloom filters (DBF) to support concise representation and approximate membership queries of dynamic sets, and study the false positive probability and union algebra operations. We prove that DBF can control the false positive probability at a low level by adjusting the number of standard bloom filters used according to the actual size of current dynamic set. The space complexity is also acceptable if the actual size of dynamic set does not deviate too much from the predefined threshold. Furthermore, we present multidimension dynamic bloom filters (MDDBF) to support concise representation and approximate membership queries of dynamic sets in multiple attribute dimensions, and study the false positive probability and union algebra operations through mathematic analysis and experimentation. We also explore the optimization approach and three network applications of bloom filters, namely bloom joins, informed search, and global index implementation. Our simulation shows that informed search based on bloom filters can obtain higher recall and success rate of query than the blind search protocol.

In this paper, we present two novel hash-based indexing structures, based on Bloom filters, called Breadth and Depth Bloom filters, which in contrast to traditional hash-based indexes, are able to summarize hierarchical data and support regular path expression queries. We describe how these structures can be used for resource discovery in peer-to-peer networks. We have implemented both structures and our experiments show that they both outperform Simple Bloom filters in discovering the appropriate resources. 1.

Service discovery is an emerging field in the area of ubiquitous computing. There are various techniques and protocols (proposed or/and already implemented) particularly tailored to specific sets of objectives. This paper analyses the current state of the art and presents a taxonomy of service discovery protocols. Along with design issues, the diversity of solutions and open questions are systematically studied. 1

Abstract. Peer-to-peer systems are gaining popularity as a means to effectively share huge, massively distributed data collections. In this paper, we consider XML peers, that is, peers that store XML documents. We show how an extension of traditional Bloom filters, called multi-level Bloom filters, can be used to route path queries in such a system. In addition, we propose building content-based overlay networks by linking together peers with similar content. The similarity of the content (i.e., the local documents) of two peers is defined based on the similarity of their filters. Our experimental results show that overlay networks built based on filter similarity are very effective in retrieving a large number of relevant documents, since peers with similar content tend to be clustered together. 1

Within high-performance, large-scale wide area computing environments, data replication provides an important mechanism for managing data locality while increasing the reliability of access to critical data. For replicas to be of general use, it is important to have robust and scalable methods for identifying the storage systems on which specific replicas are located. We propose a general framework for creating replica location services, which we call the GIGa-scale Global Location Engine (Giggle). This framework defines a parameterized set of basic mechanisms than can be instantiated in various ways to create a wide range of different replica location services. By adjusting the system parameters, we can trade off reliability, storage and communication overhead, and update and access costs. We present requirements for replica location services, define the behavior of the framework’s fundamental components, and use examples to show how the framework can be used to construct replica location services with different properties.