Peer to Peer Information Retrieval: An Overview

Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom

Answering Tag-Term Keyword Queries over XML Documents in DHT Networks

Abstract. The emergence of Peer-to-Peer (P2P) computing model and the popularity of Extensible Markup Language (XML) as the web data format have fueled the extensive research on retrieving XML data in P2P networks. In this paper, we developed an efficient and effective keyword search framework that can support tag-term keyword queries in Distributed Hash Table (DHT) networks. We employed a concise Bloom-Filter data structure to index XML meta-data in the DHT repository. We also developed an effective algorithm that supports tag-term keyword queries over our Bloom-Filter encoded XML meta-data in the DHT network. We conducted extensive experiments to demonstrate the efficiency of indexing scheme, the effectiveness of our keyword query algorithm and the system scalability of our framework

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Data sharing in DHT based P2P systems

International audienceThe evolution of peer-to-peer (P2P) systems triggered the building of large scale distributed applications. The main application domain is data sharing across a very large number of highly autonomous participants. Building such data sharing systems is particularly challenging because of the "extreme" characteristics of P2P infrastructures: massive distribution, high churn rate, no global control, potentially untrusted participants... This article focuses on declarative querying support, query optimization and data privacy on a major class of P2P systems, that based on Distributed Hash Table (P2P DHT). The usual approaches and the algorithms used by classic distributed systems and databases forproviding data privacy and querying services are not well suited to P2P DHT systems. A considerable amount of work was required to adapt them for the new challenges such systems present. This paper describes the most important solutions found. It also identies important future research trends in data management in P2P DHT systems

Query-driven indexing in large-scale distributed systems

Efficient and effective search in large-scale data repositories requires complex indexing solutions deployed on a large number of servers. Web search engines such as Google and Yahoo! already rely upon complex systems to be able to return relevant query results and keep processing times within the comfortable sub-second limit. Nevertheless, the exponential growth of the amount of content on the Web poses serious challenges with respect to scalability. Coping with these challenges requires novel indexing solutions that not only remain scalable but also preserve the search accuracy. In this thesis we introduce and explore the concept of query-driven indexing – an index construction strategy that uses caching techniques to adapt to the querying patterns expressed by users. We suggest to abandon the strict difference between indexing and caching, and to build a distributed indexing structure, or a distributed cache, such that it is optimized for the current query load. Our experimental and theoretical analysis shows that employing query-driven indexing is especially beneficial when the content is (geographically) distributed in a Peer-to-Peer network. In such a setting extensive bandwidth consumption has been identified as one of the major obstacles for efficient large-scale search. Our indexing mechanisms combat this problem by maintaining the query popularity statistics and by indexing (caching) intermediate query results that are requested frequently. We present several indexing strategies for processing multi-keyword and XPath queries over distributed collections of textual and XML documents respectively. Experimental evaluations show significant overall traffic reduction compared to the state-of-the-art approaches. We also study possible query-driven optimizations for Web search engine architectures. Contrary to the Peer-to-Peer setting, Web search engines use centralized caching of query results to reduce the processing load on the main index. We analyze real search engine query logs and show that the changes in query traffic that such a results cache induces fundamentally affect indexing performance. In particular, we study its impact on index pruning efficiency. We show that combination of both techniques enables efficient reduction of the query processing costs and thus is practical to use in Web search engines

Distributed resource discovery: architectures and applications in mobile networks

As the amount of digital information and services increases, it becomes increasingly important to be able to locate the desired content. The purpose of a resource discovery system is to allow available resources (information or services) to be located using a user-defined search criterion. This work studies distributed resource discovery systems that guarantee all existing resources to be found and allow a wide range of complex queries. Our goal is to allocate the load uniformly between the participating nodes, or alternatively to concentrate the load in the nodes with the highest available capacity. The first part of the work examines the performance of various existing unstructured architectures and proposes new architectures that provide features especially valuable in mobile networks. To reduce the network traffic, we use indexing, which is particularly useful in scenarios, where searches are frequent compared to resource modifications. The ratio between the search and update frequencies determines the optimal level of indexing. Based on this observation, we develop an architecture that adjusts itself to changing network conditions and search behavior while maintaining optimal indexing. We also propose an architecture based on large-scale indexing that we later apply to resource sharing within a user group. Furthermore, we propose an architecture that relieves the topology constraints of the Parallel Index Clustering architecture. The performance of the architectures is evaluated using simulation. In the second part of the work we apply the architectures to two types of mobile networks: cellular networks and ad hoc networks. In the cellular network, we first consider scenarios where multiple commercial operators provide a resource sharing service, and then a scenario where the users share resources without operator support. We evaluate the feasibility of the mobile peer-to-peer concept using user opinion surveys and technical performance studies. Based on user input we develop access control and group management algorithms for peer-to-peer networks. The technical evaluation is performed using prototype implementations. In particular, we examine whether the Session Initiation Protocol can be used for signaling in peer-to-peer networks. Finally, we study resource discovery in an ad hoc network. We observe that in an ad hoc network consisting of consumer devices, the capacity and mobility among nodes vary widely. We utilize this property in order to allocate the load to the high-capacity nodes, which serve lower-capacity nodes. We propose two methods for constructing a virtual backbone connecting the nodes

Approximate algorithms for efficient indexing, clustering, and classification in Peer-to-peer networks

[no abstract

An Overlay Architecture for Personalized Object Access and Sharing in a Peer-to-Peer Environment

Due to its exponential growth and decentralized nature, the Internet has evolved into a chaotic repository, making it difficult for users to discover and access resources of interest to them. As a result, users have to deal with the problem of information overload. The Semantic Web's emergence provides Internet users with the ability to associate explicit, self-described semantics with resources. This ability will facilitate in turn the development of ontology-based resource discovery tools to help users retrieve information in an efficient manner. However, it is widely believed that the Semantic Web of the future will be a complex web of smaller ontologies, mostly created by various groups of web users who share a similar interest, referred to as a Community of Interest. This thesis proposes a solution to the information overload problem using a user driven framework, referred to as a Personalized Web, that allows individual users to organize themselves into Communities of Interests based on ontologies agreed upon by all community members. Within this framework, users can define and augment their personalized views of the Internet by associating specific properties and attributes to resources and defining constraint-functions and rules that govern the interpretation of the semantics associated with the resources. Such views can then be used to capture the user's interests and integrate these views into a user-defined Personalized Web. As a proof of concept, a Personalized Web architecture that employs ontology-based semantics and a structured Peer-to-Peer overlay network to provide a foundation of semantically-based resource indexing and advertising is developed. In order to investigate mechanisms that support the resource advertising and retrieval of the Personalized Web architecture, three agent-driven advertising and retrieval schemes, the Aggressive scheme, the Crawler-based scheme, and the Minimum-Cover-Rule scheme, were implemented and evaluated in both stable and churn environments. In addition to the development of a Personalized Web architecture that deals with typical web resources, this thesis used a case study to explore the potential of the Personalized Web architecture to support future web service workflow applications. The results of this investigation demonstrated that the architecture can support the automation of service discovery, negotiation, and invocation, allowing service consumers to actualize a personalized web service workflow. Further investigation will be required to improve the performance of the automation and allow it to be performed in a secure and robust manner. In order to support the next generation Internet, further exploration will be needed for the development of a Personalized Web that includes ubiquitous and pervasive resources

Keyword-based search in peer-to-peer networks

Ph.DDOCTOR OF PHILOSOPH