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- PublicationMétadonnées seulementBRISA: Combining Efficiency and Reliability in Epidemic Data DisseminationThere is an increasing demand for efficient and robust systems able to cope with today's global needs for intensive data dissemination, e.g., media content or news feeds. Unfortunately, traditional approaches tend to focus on one end of the efficiency/robustness design spectrum, by either leveraging rigid structures such as trees to achieve efficient distribution, or using loosely-coupled epidemic protocols to obtain robustness. In this paper we present BRISA, a hybrid approach combining the robustness of epidemic-based dissemination with the efficiency of tree-based structured approaches. This is achieved by having dissemination structures such as trees implicitly emerge from an underlying epidemic substrate by a judicious selection of links. These links are chosen with local knowledge only and in such a way that the completeness of data dissemination is not compromised, i.e., the resulting structure covers all nodes. Failures are treated as an integral part of the system as the dissemination structures can be promptly compensated and repaired thanks to the underlying epidemic substrate. Besides presenting the protocol design, we conduct an extensive evaluation in a real environment, analyzing the effectiveness of the structure creation mechanism and its robustness under faults and churn. Results confirm BRISA as an efficient and robust approach to data dissemination in the large scale.
- PublicationMétadonnées seulementExploiting Node Connection Regularity for DHT Replication(: IEEE, 2011-10)
;Pace, Alessio ;Quema, Vivien
- PublicationAccès libreHave a Seat on the ErasureBench: Easy Evaluation of Erasure Coding Libraries for Distributed Storage SystemsWe present ErasureBench, an open-source framework to test and benchmark erasure coding implementations for distributed storage systems under realistic conditions. ErasureBench automatically instantiates and scales a cluster of storage nodes, and can seamlessly leverage existing failure traces. As a first example, we use ErasureBench to compare three coding implementations: a (10,4) Reed-Solomon (RS) code, a (10,6,5) locally repairable code (LRC), and a partition of the data source in ten pieces without error-correction. Our experiments show that LRC and RS codes require the same repair throughput when used with small storage nodes, since cluster and network management traffic dominate at this regime. With large storage nodes, read and write traffic increases and our experiments confirm the theoretical and practical tradeoffs between the storage overhead and repair bandwidth of RS and LRC codes.
- PublicationMétadonnées seulementGenPack: A Generational Scheduler for Cloud Data Centers(: IEEE, 2017-4-4)
- PublicationAccès libreSGX-FS: Hardening a File System in User-Space with Intel SGX
- PublicationMétadonnées seulement
- PublicationMétadonnées seulementTOPiCo: Detecting Most Frequent Items from Multiple High-Rate Event StreamsSystems such as social networks, search engines or trading platforms operate geographically distant sites that continu- ously generate streams of events at high-rate. Such events can be access logs to web servers, feeds of messages from participants of a social network, or financial data, among others. The ability to timely detect trends and popularity variations is of paramount importance in such systems. In particular, determining what are the most popular events across all sites allows to capture the most relevant informa- tion in near real-time and quickly adapt the system to the load. This paper presents TOPiCo, a protocol that com- putes the most popular events across geo-distributed sites in a low cost, bandwidth-efficient and timely manner. TOPiCo starts by building the set of most popular events locally at each site. Then, it disseminates only events that have a chance to be among the most popular ones across all sites, significantly reducing the required bandwidth. We give a correctness proof of our algorithm and evaluate TOPiCo using a real-world trace of more than 240 million events spread across 32 sites. Our empirical results shows that (i) TOPiCo is timely and cost-efficient for detecting popular events in a large-scale setting, (ii) it adapts dynamically to the distribution of the events, and (iii) our protocol is particularly efficient for skewed distributions.
- PublicationMétadonnées seulementEvaluating the Cost and Robustness of Self-organizing Distributed Hash TablesSelf-organizing construction principles are a natural fit for large-scale distributed system in unpredictable deployment environments. These principles allow a system to systematically converge to a global state by means of simple, uncoordinated actions by individual peers. Indexing services based on the distributed hash table (DHT) abstraction have been established as a solid foundation for large-scale distributed applications. For most DHTs, the creation and maintenance of the overlay structure relies on the exploration and update of an already stabilized structure. We evaluate in this paper the practical interest of self-organizing principles, and in particular gossip-based overlay construction protocols, to bootstrap and maintain various DHT implementations. Based on the seminal work on T-Chord, a self-organizing version of Chord using the T-Man overlay construction service, we contribute three additional self-organizing DHTs: T-Pastry, T-Kademlia and T-Kelips. We conduct an experimental evaluation of the cost and performance of each of these designs using a prototype implementation. Our conclusion is that, while providing equivalent performance in a stabilized system, self-organizing DHTs are able to sustain and recover from higher level of churn than their explicitly-created counterparts, and should therefore be considered as a method of choice for deploying robust indexing layers in adverse environments.
- PublicationMétadonnées seulementUniCrawl: A Practical Geographically Distributed Web CrawlerAs the wealth of information available on the web keeps growing, being able to harvest massive amounts of data has become a major challenge. Web crawlers are the core components to retrieve such vast collections of publicly available data. The key limiting factor of any crawler architecture is however its large infrastructure cost. To reduce this cost, and in particular the high upfront investments, we present in this paper a geo- distributed crawler solution, UniCrawl. UniCrawl orchestrates several geographically distributed sites. Each site operates an independent crawler and relies on well-established techniques for fetching and parsing the content of the web. UniCrawl splits the crawled domain space across the sites and federates their storage and computing resources, while minimizing thee inter-site communication cost. To assess our design choices, we evaluate UniCrawl in a controlled environment using the ClueWeb12 dataset, and in the wild when deployed over several remote locations. We conducted several experiments over 3 sites spread across Germany. When compared to a centralized architecture with a crawler simply stretched over several locations, UniCrawl shows a performance improvement of 93.6% in terms of network bandwidth consumption, and a speedup factor of 1.75.