Enabling Social Applications via Decentralized Social Data Management

An unprecedented information wealth produced by online social networks, further augmented by location/collocation data, is currently fragmented across different proprietary services. Combined, it can accurately represent the social world and enable novel socially-aware applications. We present Prometheus, a socially-aware peer-to-peer service that collects social information from multiple sources into a multigraph managed in a decentralized fashion on user-contributed nodes, and exposes it through an interface implementing non-trivial social inferences while complying with user-defined access policies. Simulations and experiments on PlanetLab with emulated application workloads show the system exhibits good end-to-end response time, low communication overhead and resilience to malicious attacks.Comment: 27 pages, single ACM column, 9 figures, accepted in Special Issue of Foundations of Social Computing, ACM Transactions on Internet Technolog

Socially-Aware Distributed Hash Tables for Decentralized Online Social Networks

Many decentralized online social networks (DOSNs) have been proposed due to an increase in awareness related to privacy and scalability issues in centralized social networks. Such decentralized networks transfer processing and storage functionalities from the service providers towards the end users. DOSNs require individualistic implementation for services, (i.e., search, information dissemination, storage, and publish/subscribe). However, many of these services mostly perform social queries, where OSN users are interested in accessing information of their friends. In our work, we design a socially-aware distributed hash table (DHTs) for efficient implementation of DOSNs. In particular, we propose a gossip-based algorithm to place users in a DHT, while maximizing the social awareness among them. Through a set of experiments, we show that our approach reduces the lookup latency by almost 30% and improves the reliability of the communication by nearly 10% via trusted contacts.Comment: 10 pages, p2p 2015 conferenc

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

Scalable, Data- intensive Network Computation

To enable groups of collaborating researchers at different locations to effectively share large datasets and investigate their spontaneous hypotheses on the fly, we are interested in de- veloping a distributed system that can be easily leveraged by a variety of data intensive applications. The system is composed of (i) a number of best effort logistical depots to en- able large-scale data sharing and in-network data processing, (ii) a set of end-to-end tools to effectively aggregate, manage and schedule a large number of network computations with attendant data movements, and (iii) a Distributed Hash Table (DHT) on top of the generic depot services for scalable data management. The logistical depot is extended by following the end-to-end principles and is modeled with a closed queuing network model. Its performance characteristics are studied by solving the steady state distributions of the model using local balance equations. The modeling results confirm that the wide area network is the performance bottleneck and running concurrent jobs can increase resource utilization and system throughput. As a novel contribution, techniques to effectively support resource demanding data- intensive applications using the ¯ne-grained depot services are developed. These techniques include instruction level scheduling of operations, dynamic co-scheduling of computation and replication, and adaptive workload control. Experiments in volume visualization have proved the effectiveness of these techniques. Due to the unique characteristic of data- intensive applications and our co-scheduling algorithm, a DHT is implemented on top of the basic storage and computation services. It demonstrates the potential of the Logistical Networking infrastructure to serve as a service creation platform

Service discovery in a peer-to-peer environment for computational grids

Les grilles de calcul sont des systèmes distribués dont l'objectif est l'agrégation et le partage de ressources hétérogènes géographiquement réparties pour le calcul haute performance. Les services d'une grille sont l'ensemble des applicatifs que des serveurs mettent à disposition des clients. Une problématique largement soulevée par les utilisateurs de grilles est la découverte de services. Les mécanismes actuels de découverte de services manquent de fonctionnalités et deviennent inefficaces dans des environnements dynamiques à large échelle. Il est donc indispensable de proposer de nouveaux outils pour de tels environnements. Les technologies pair-à-pair émergentes fournissent des algorithmes permettant une décentralisation totale de la construction et de la maintenance de systèmes distribués performants et tolérants aux pannes. Le problème que l'on cherche à résoudre est de permettre une découverte flexible (recherche multicritères, complétion automatique) des services dans des grilles prenant place dans un environnement dynamique à large échelle (pair-à-pair) en tenant compte de la topologie du réseau physique sous-jacent

Wireless mobile ad-hoc sensor networks for very large scale cattle monitoring

This paper investigates the use of wireless mobile ad hoc sensor networks in the nationwide cattle monitoring systems. This problem is essential for monitoring general animal health and detecting outbreaks of animal diseases that can be a serious threat for the national cattle industry and human health. We begin by describing a number of related approaches for supporting animal monitoring applications and identify a comprehensive set of requirements that guides our approach. We then propose a novel infrastructure-less, self -organized peer to peer architecture that fulfills these requirements. The core of our work is the novel data storage and routing protocol for large scale, highly mobile ad hoc sensor networks that is based on the Distributed Hash Table (DHT) substrate that we optimize for disconnections. We show over a range of extensive simulations that by exploiting nodes’ mobility, packet overhearing and proactive caching we significantly improve availability of sensor data in these extreme conditions