Optimally Efficient Prefix Search and Multicast in Structured P2P Networks

Searching in P2P networks is fundamental to all overlay networks. P2P networks based on Distributed Hash Tables (DHT) are optimized for single key lookups, whereas unstructured networks offer more complex queries at the cost of increased traffic and uncertain success rates. Our Distributed Tree Construction (DTC) approach enables structured P2P networks to perform prefix search, range queries, and multicast in an optimal way. It achieves this by creating a spanning tree over the peers in the search area, using only information available locally on each peer. Because DTC creates a spanning tree, it can query all the peers in the search area with a minimal number of messages. Furthermore, we show that the tree depth has the same upper bound as a regular DHT lookup which in turn guarantees fast and responsive runtime behavior. By placing objects with a region quadtree, we can perform a prefix search or a range query in a freely selectable area of the DHT. Our DTC algorithm is DHT-agnostic and works with most existing DHTs. We evaluate the performance of DTC over several DHTs by comparing the performance to existing application-level multicast solutions, we show that DTC sends 30-250% fewer messages than common solutions

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

Content Distribution in P2P Systems

The report provides a literature review of the state-of-the-art for content distribution. The report's contributions are of threefold. First, it gives more insight into traditional Content Distribution Networks (CDN), their requirements and open issues. Second, it discusses Peer-to-Peer (P2P) systems as a cheap and scalable alternative for CDN and extracts their design challenges. Finally, it evaluates the existing P2P systems dedicated for content distribution according to the identied requirements and challenges

Video browsing interfaces and applications: a review

We present a comprehensive review of the state of the art in video browsing and retrieval systems, with special emphasis on interfaces and applications. There has been a significant increase in activity (e.g., storage, retrieval, and sharing) employing video data in the past decade, both for personal and professional use. The ever-growing amount of video content available for human consumption and the inherent characteristics of video data—which, if presented in its raw format, is rather unwieldy and costly—have become driving forces for the development of more effective solutions to present video contents and allow rich user interaction. As a result, there are many contemporary research efforts toward developing better video browsing solutions, which we summarize. We review more than 40 different video browsing and retrieval interfaces and classify them into three groups: applications that use video-player-like interaction, video retrieval applications, and browsing solutions based on video surrogates. For each category, we present a summary of existing work, highlight the technical aspects of each solution, and compare them against each other

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

Ontology-based Search Algorithms over Large-Scale Unstructured Peer-to-Peer Networks

Peer-to-Peer(P2P) systems have emerged as a promising paradigm to structure large scale distributed systems. They provide a robust, scalable and decentralized way to share and publish data.The unstructured P2P systems have gained much popularity in recent years for their wide applicability and simplicity. However efficient resource discovery remains a fundamental challenge for unstructured P2P networks due to the lack of a network structure. To effectively harness the power of unstructured P2P systems, the challenges in distributed knowledge management and information search need to be overcome. Current attempts to solve the problems pertaining to knowledge management and search have focused on simple term based routing indices and keyword search queries. Many P2P resource discovery applications will require more complex query functionality, as users will publish semantically rich data and need efficiently content location algorithms that find target content at moderate cost. Therefore, effective knowledge and data management techniques and search tools for information retrieval are imperative and lasting. In my dissertation, I present a suite of protocols that assist in efficient content location and knowledge management in unstructured Peer-to-Peer overlays. The basis of these schemes is their ability to learn from past peer interactions and increasing their performance with time.My work aims to provide effective and bandwidth-efficient searching and data sharing in unstructured P2P environments. A suite of algorithms which provide peers in unstructured P2P overlays with the state necessary in order to efficiently locate, disseminate and replicate objects is presented. Also, Existing approaches to federated search are adapted and new methods are developed for semantic knowledge representation, resource selection, and knowledge evolution for efficient search in dynamic and distributed P2P network environments. Furthermore,autonomous and decentralized algorithms that reorganizes an unstructured network topology into a one with desired search-enhancing properties are proposed in a network evolution model to facilitate effective and efficient semantic search in dynamic environments

A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids

[EN] Peer-to-Peer (P2P) overlay communications networks have emerged as a new paradigm for implementing distributed services in microgrids due to their potential benefits: they are robust, scalable, fault-tolerant, and they can route messages even with a large number of nodes which are frequently entering or leaving from the network. However, current P2P systems have been mainly developed for file sharing or cycle sharing applications where the processes of searching and managing resources are not optimized. Locality algorithms have gained a lot of attention due to their potential to provide an optimized path to groups with similar interests for routing messages in order to get better network performance. This paper develops a fully functional decentralized communication architecture with a new P2P locality algorithm and a specific protocol for monitoring and control of microgrids. Experimental results show that the proposed locality algorithm reduces the number of lookup messages and the lookup delay time. Moreover, the proposed communication architecture heavily depends of the lookup used algorithm as well as the placement of the communication layers within the architecture. Experimental results will show that the proposed techniques meet the network requirements of smart microgrids even with a large number of nodes on stream.This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (ERDF) under Grant ENE2015-64087-C2-2R. This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under BES-2013-064539.Marzal-Romeu, S.; González-Medina, R.; Salas-Puente, RA.; Figueres Amorós, E.; Garcerá, G. (2017). A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids. 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Use of latent semantic indexing for content based searching and routing of mobile agents on P2P network

The peer-to-peer (P2P) system has a number of nodes that are connected to each other in an unstructured or a structured overlay network. One of the most important problems in a P2P system is locating of resources that are shared by various nodes. Techniques such as Flooding and Distributed Hash-Table (DHT) have been proposed to locate resources shared by various nodes. Flooding suffers from saturation as number of nodes increase, while DHT cannot handle multiple keys to define and search a resource. Various further research works including multi agent systems (MAS) have been pursued that take unstructured or structured networks as a backbone and hence inherently suffer from problems. We present the solution that is more efficient and effective for discovering shared resources on a network that is influenced by content shared by nodes. Our solution presents use of multiple agents that manage the shared information on a node and a mobile agent called Reconnaissance Agent (RA) that is responsible for querying various nodes. To reduce the search load on nodes that have unrelated content, an efficient migration route is proposed for RA that is based on cosine similarity of content shared by nodes and user query. Results show reduction in search load and traffic due to communication, and increase in recall value for locating of resources defined by multiple keys using RA that are logically similar to user query. Furthermore, the results indicate that by use of our technique the relevance of search results is higher; that is obtained by minimal traffic generation/communication and hops made by RA