Dynamic TTL-Based Search In Unstructured Peer-to-Peer Networks

International audienceResource discovery is a challenging issue in unstructured peer-to-peer networks. Blind search approaches, including flooding and random walks, are the two typical algorithms used in such systems. Blind flooding is not scalable because of its high communication cost. On the other hand, the performance of random walks approaches largely depends on the random choice of walks. Some informed mechanisms use additional information, usually obtained from previous queries, for routing. Such approaches can reduce the traffic overhead but they limit the query coverage. Furthermore, they usually rely on complex protocols to maintain information at each peer. In this paper, we propose two schemes which can be used to improve the search performance in unstructured peer-to-peer networks. The first one is a simple caching mechanism based on resource descriptions. Peers that offer resources send periodic advertisement messages. These messages are stored into a cache and are used for routing requests. The second scheme is a dynamic Time-To-Live (TTL) enabling messages to break their horizon. Instead of decreasing the query TTL by 1 at each hop, it is decreased by a value v such as

Modular P2P-Based Approach for RDF Data Storage and Retrieval

International audienceOne of the key elements of the Semantic Web is the Resource Description Framework (RDF). Efficient storage and retrieval of RDF data in large scale settings is still challenging and existing solutions are monolithic and thus not very flexible from a software engineering point of view. In this paper, we propose a modular system, based on the scalable Content-Addressable Network (CAN), which gives the possibility to store and retrieve RDF data in large scale settings. We identified and isolated key components forming such system in our design architecture. We have evaluated our system using the Grid'5000 testbed over 300 peers on 75 machines and the outcome of these micro-benchmarks show interesting results in terms of scalability and concurrent queries

RDF Data Indexing and Retrieval: A survey of Peer-to-Peer based solutions

The Semantic Web enables the possibility to model, create and query resources found on the Web. Enabling the full potential of its technologies at the Internet level requires infrastructures that can cope with scalability challenges and support various types of queries. The attractive features of the Peer-to-Peer (P2P) communication model such as decentralization, scalability, fault-tolerance seems to be a natural solution to deal with these challenges. Consequently, the combination of the Semantic Web and the P2P model can be a highly innovative attempt to harness the strengths of both technologies and come up with a scalable infrastructure for RDF data storage and retrieval. In this respect, this survey details the research works that adopt this combination and gives an insight on how to deal with the RDF data at the indexing and querying levels.Le Web Sémantique permet de modéliser, créer et faire des requêtes sur les ressources disponibles sur le Web. Afin de permettre à ses technologies d'exploiter leurs potentiels à l'échelle de l'Internet, il est nécessaire qu'elles reposent sur des infrastructures qui puissent passer à l'échelle ainsi que de répondre aux exigences d'expressivité des types de requêtes qu'elles offrent. Les bonnes propriétés qu'offrent les dernières générations de systèmes pair-à- pair en termes de décentralisation, de tolérance aux pannes ainsi que de passage à l'échelle en font d'eux des candidats prometteurs. La combinaison du modèle pair-à-pair et des technologies du Web Sémantique est une tentative innovante ayant pour but de fournir une infrastructure capable de passer à l'échelle et pouvant stocker et rechercher des données de type RDF. Dans ce contexte, ce rapport présente un état de l'art et discute en détail des travaux autour de systèmes pair-à-pair qui traitent des données de type RDF à large échelle. Nous détaillons leurs mécanismes d'indexation de données ainsi que le traitement des divers types de requêtes offerts

CoShare: A Cost-effective Data Sharing System for Data Center Networks

Numerous research groups and other organizations collect data from popular data sources such as online social networks. This leads to the problem of data islands, wherein all this data is isolated and lying idly, without any use to the community at large. Using existing centralized solutions such as Dropbox to replicate data to all interested parties is prohibitively costly, given the large size of datasets. A practical solution is to use a Peer-to-Peer (P2P) approach to replicate data in a self-organized manner. However, existing P2P approaches focus on minimizing downloading time without taking into account the bandwidth cost. In this paper, we present CoShare, a P2P inspired decentralized cost effective sharing system for data replication. CoShare allows users to specify their requirements on data sharing tasks and maps these requirements into resource requirements for data transfer. Through extensive simulations, we demonstrate that CoShare finds the desirable tradeoffs for a given cost and performance while varying user requirements and request arrival rates

Improving resource discovery in P2P systems

Le modèle de communication pair-à-pair a beaucoup attiré l attention dans les dernières années car il est considéré comme un paradigme puissant pour déployer et exécuter des applications distribuées à grande échelle. Dans ce contexte, le problème de découverte de ressources, c est-à-dire la recherche d une ressource donnée répondant aux besoins de l application constitue un aspect critique dans les systèmes pair-à-pair. Cette thèse se concentre sur la recherche de ressources dans les systèmes pair-à-pair non structurés ainsi que structurés. Dans la première partie de cette thèse, nous proposons un algorithme de découverte de ressources dans un environnement non structuré qui ajuste l horizon de la requête dynamiquement dans le but de retrouver les ressources demandées d une manière efficace. La deuxième partie porte sur la conception et l implémentation d une architecture pair-à-pair hiérarchique ayant pour but le stockage et la recherche de ressources sémantiques à grande échelle. Cette infrastructure combine le modèle pair-à-pair au niveau de l architecture elle même et le modèle RDF au niveau de la représentation des données.The Peer-to-Peer (P2P) communication model has drawn much attention in the last few years and has been emerged as a powerful paradigm to build large scale distributed applications. Resource discovery constitutes a critical aspect of P2P systems; it involves the matching of the user s application requirements to available resources. The thesis focuses on the resource discovery in P2P systems encompassing unstructured and structured P2P overlays. In the first part of this work, we have concentrated on resource discovery in unstructured P2P systems. We have proposed and evaluated a novel algorithm for resource location in unstructured P2P networks that dynamically adjust the query horizon in order to efficiently locate the required resources. The second part of the thesis deals with the design and the implementation of a hierarchical P2P semantic space infrastructure aiming at the distributed storage and retrieval of the semantic data at large scale. This infrastructure combines the strengths of both P2P paradigm at the architectural level and the Resource Description Framework (RDF) data model at the knowledge representation level. While the P2P communication model addresses the system complexity by allowing flexible and decentralized resource storage and processing, the semantic web technologies, on the other hand, address the problem of information complexity by providing advanced support for data presentation and querying.NICE-BU Sciences (060882101) / SudocSudocFranceF

Requirement Change Prediction Model for Small Software Systems

The software industry plays a vital role in driving technological advancements. Software projects are complex and consist of many components, so change is unavoidable in these projects. The change in software requirements must be predicted early to preserve resources, since it can lead to project failures. This work focuses on small-scale software systems in which requirements are changed gradually. The work provides a probabilistic prediction model, which predicts the probability of changes in software requirement specifications. The first part of the work considers analyzing the changes in software requirements due to certain variables with the help of stakeholders, developers, and experts by the questionnaire method. Then, the proposed model incorporates their knowledge in the Bayesian network as conditional probabilities of independent and dependent variables. The proposed approach utilizes the variable elimination method to obtain the posterior probability of the revisions in the software requirement document. The model was evaluated by sensitivity analysis and comparison methods. For a given dataset, the proposed model computed the low state revisions probability to 0.42, and the high state revisions probability to 0.45. Thus, the results proved that the proposed approach can predict the change in the requirements document accurately by outperforming existing models

An efficient framework for running applications on clusters, grids, and clouds

International audienceSince the appearance of distributed computing technology, there has been a significant effort in designing and building the infrastructure needed to tackle the challenges raised by complex scientific applications that require massive computational resources. This increases the awareness to harness the power and flexibility of Clouds that have recently emerged as an alternative to data centers or private clusters. We describe in this chapter an efficient high-level Grid and Cloud framework that allows a smooth transition from clusters and Grids to Clouds. The main lever is the ability to move application infrastructure-specific information away from the code and manage them in a deployment file. An application can thus easily run on a cluster, a grid, or a cloud, or any mix of them without modification