6,749 research outputs found

    Measuring and Managing Answer Quality for Online Data-Intensive Services

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    Online data-intensive services parallelize query execution across distributed software components. Interactive response time is a priority, so online query executions return answers without waiting for slow running components to finish. However, data from these slow components could lead to better answers. We propose Ubora, an approach to measure the effect of slow running components on the quality of answers. Ubora randomly samples online queries and executes them twice. The first execution elides data from slow components and provides fast online answers; the second execution waits for all components to complete. Ubora uses memoization to speed up mature executions by replaying network messages exchanged between components. Our systems-level implementation works for a wide range of platforms, including Hadoop/Yarn, Apache Lucene, the EasyRec Recommendation Engine, and the OpenEphyra question answering system. Ubora computes answer quality much faster than competing approaches that do not use memoization. With Ubora, we show that answer quality can and should be used to guide online admission control. Our adaptive controller processed 37% more queries than a competing controller guided by the rate of timeouts.Comment: Technical Repor

    The AliEn system, status and perspectives

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    AliEn is a production environment that implements several components of the Grid paradigm needed to simulate, reconstruct and analyse HEP data in a distributed way. The system is built around Open Source components, uses the Web Services model and standard network protocols to implement the computing platform that is currently being used to produce and analyse Monte Carlo data at over 30 sites on four continents. The aim of this paper is to present the current AliEn architecture and outline its future developments in the light of emerging standards.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 10 pages, Word, 10 figures. PSN MOAT00

    Mobile Computing in Digital Ecosystems: Design Issues and Challenges

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    In this paper we argue that the set of wireless, mobile devices (e.g., portable telephones, tablet PCs, GPS navigators, media players) commonly used by human users enables the construction of what we term a digital ecosystem, i.e., an ecosystem constructed out of so-called digital organisms (see below), that can foster the development of novel distributed services. In this context, a human user equipped with his/her own mobile devices, can be though of as a digital organism (DO), a subsystem characterized by a set of peculiar features and resources it can offer to the rest of the ecosystem for use from its peer DOs. The internal organization of the DO must address issues of management of its own resources, including power consumption. Inside the DO and among DOs, peer-to-peer interaction mechanisms can be conveniently deployed to favor resource sharing and data dissemination. Throughout this paper, we show that most of the solutions and technologies needed to construct a digital ecosystem are already available. What is still missing is a framework (i.e., mechanisms, protocols, services) that can support effectively the integration and cooperation of these technologies. In addition, in the following we show that that framework can be implemented as a middleware subsystem that enables novel and ubiquitous forms of computation and communication. Finally, in order to illustrate the effectiveness of our approach, we introduce some experimental results we have obtained from preliminary implementations of (parts of) that subsystem.Comment: Proceedings of the 7th International wireless Communications and Mobile Computing conference (IWCMC-2011), Emergency Management: Communication and Computing Platforms Worksho

    Any Data, Any Time, Anywhere: Global Data Access for Science

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    Data access is key to science driven by distributed high-throughput computing (DHTC), an essential technology for many major research projects such as High Energy Physics (HEP) experiments. However, achieving efficient data access becomes quite difficult when many independent storage sites are involved because users are burdened with learning the intricacies of accessing each system and keeping careful track of data location. We present an alternate approach: the Any Data, Any Time, Anywhere infrastructure. Combining several existing software products, AAA presents a global, unified view of storage systems - a "data federation," a global filesystem for software delivery, and a workflow management system. We present how one HEP experiment, the Compact Muon Solenoid (CMS), is utilizing the AAA infrastructure and some simple performance metrics.Comment: 9 pages, 6 figures, submitted to 2nd IEEE/ACM International Symposium on Big Data Computing (BDC) 201
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