104,739 research outputs found
Towards operator-less data centers through data-driven, predictive, proactive autonomics
No full textContinued reliance on human operators for managing data centers is a major impediment for them from ever reaching extreme dimensions. Large computer systems in general, and data centers in particular, will ultimately be managed using predictive computational and executable models obtained through data-science tools, and at that point, the intervention of humans will be limited to setting high-level goals and policies rather than performing low-level operations. Data-driven autonomics, where management and control are based on holistic predictive models that are built and updated using live data, opens one possible path towards limiting the role of operators in data centers. In this paper, we present a data-science study of a public Google dataset collected in a 12K-node cluster with the goal of building and evaluating predictive models for node failures. Our results support the practicality of a data-driven approach by showing the effectiveness of predictive models based on data found in typical data center logs. We use BigQuery, the big data SQL platform from the Google Cloud suite, to process massive amounts of data and generate a rich feature set characterizing node state over time. We describe how an ensemble classifier can be built out of many Random Forest classifiers each trained on these features, to predict if nodes will fail in a future 24-h window. Our evaluation reveals that if we limit false positive rates to 5 %, we can achieve true positive rates between 27 and 88 % with precision varying between 50 and 72 %. This level of performance allows us to recover large fraction of jobs’ executions (by redirecting them to other nodes when a failure of the present node is predicted) that would otherwise have been wasted due to failures. We discuss the feasibility of including our predictive model as the central component of a data-driven autonomic manager and operating it on-line with live data streams (rather than off-line on data logs). All of the scripts used for BigQuery and classification analyses are publicly available on GitHub
Jgroup/ARM: a distributed object group platform with autonomous replication management
No full textThis paper presents the design and implementation of Jgroup/ARM, a distributed object group platform
with autonomous replication management along with a novel measurement-based assessment technique
that is used to validate the fault-handling capability of Jgroup/ARM. Jgroup extends Java RMI through the
group communication paradigm and has been designed specifically for application support in partitionable
systems. ARM aims at improving the dependability characteristics of systems through a fault-treatment
mechanism. Hence, ARM focuses on deployment and operational aspects, where the gain in terms of
improved dependability is likely to be the greatest. The main objective of ARM is to localize failures
and to reconfigure the system according to application-specific dependability requirements. Combining
Jgroup and ARM can significantly reduce the effort necessary for developing, deploying and managing
dependable, partition-aware applications. Jgroup/ARM is evaluated experimentally to validate its fault-handling capability; the recovery performance of a system deployed in a wide area network is evaluated. In
this experiment multiple nearly coincident reachability changes are injected to emulate network partition
IntegratingAgentCommunicationLanguagesin
No full text2002-6 TowardsaSemanticWebforFormalMathematics(Ph.D.Thesis),Schena,I.,March2002. 2002-7 RevisitingInteractiveMarkovChains,Bravetti,M.,June2002. 2002-8 UserUntraceabilityintheNext-GenerationInternet:aProposal,Tortonesi,M.,Davoli,R.,August2002. 2002-9 Towards Adaptive, Resilientand Self-OrganizingPeer-to-Peer Systems, Montresor, A., Meling, H., Babaoglu,O.,September2002. 2002-10 TowardsSelf-Organizing,Self-RepairingandResilientDistributedSystems,Montresor,A.,Babaoglu,O., Meling,H.,September2002(RevisedNovember2002). 2002-11 Messor:Load-BalancingthroughaSwarmofAutonomousAgents,Montresor,A.,Meling,H.,Babaoglu, O.,September2002. 2002-12 Johanna: OpenCollaborativeTechnologiesforTeleorganizations,Gaspari,M.,Picci,L.,Petrucci,A., Faglioni,G.,December2002
Robust Aggregation Protocols for Large-Scale Overlay Networks
No full textAggregation refers to a set of functions that provide global information about a distributed system. These functions operate on numeric values distributed over the system and can be used to count network size, determine extremal values and compute averages, products or sums. Aggregation allows important basic functionality to be achieved in fully distributed and peerto -peer networks. For example, in a monitoring application, some aggregate reaching a specific value may trigger the execution of certain operations; distributed storage systems may need to know the total free space available; load-balancing protocols may benefit from knowing the target average load so as to minimize the transfered load. Building on the simple but efficient idea of anti-entropy aggregation (a scheme based on the anti-entropy epidemic communication model), in this paper we introduce practically applicable robust and adaptive protocols for proactive aggregation, including the calculation of average, product and extremal values. We show how the averaging protocol can be applied to compute further aggregates like sum, variance and the network size. We present theoretical and empirical evidence supporting the robustness of the averaging protocol under different scenarios including node and communication failures
TechnicalReportUBLCS-2003-9
No full text2002-6 TowardsaSemanticWebforFormalMathematics(Ph.D.Thesis),Schena,I.,March2002. 2002-7 RevisitingInteractiveMarkovChains,Bravetti,M.,June2002. 2002-8 UserUntraceabilityintheNext-GenerationInternet:aProposal,Tortonesi,M.,Davoli,R.,August2002. 2002-9 Towards Adaptive, Resilientand Self-OrganizingPeer-to-Peer Systems, Montresor, A., Meling, H., Babaoglu,O.,September2002. 2002-10 TowardsSelf-Organizing,Self-RepairingandResilientDistributedSystems,Montresor,A.,Babaoglu,O., Meling,H.,September2002(RevisedNovember2002). 2002-11 Messor:Load-BalancingthroughaSwarmofAutonomousAgents,Montresor,A.,Meling,H.,Babaoglu, O.,September2002. 2002-12 Johanna: OpenCollaborativeTechnologiesforTeleorganizations,Gaspari,M.,Picci,L.,Petrucci,A., Faglioni,G.,December2002
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
The construction of Karen Karnak: The multi-author-function
No full textThis thesis is situated within the comparatively recent developments of Web 2.0 and the emergence of interactive WikiMedia, and explores the mode of authorship within a Read/Write culture compared to that of a Read/Only tradition. The hypothesis of this study is that the role of the audience has become merged with the author, and as such, represents new functions and attributes, distinct from a more conventional concept of authorship, in which the roles of audience and author are more separate. Read/Write and participatory culture, as defined by this study, is focused on collaboration, and includes the influences of D.I.Y. culture, Open-Source practices and the production of text by multiple authors. Multi-authorship presents a re-thinking of several concepts which support the notion of the individual author, since the focus of multi-authorship is not on attribution and ownership of a finished text, but on the continued malleability of a text. Modes of multi-authorship, demonstrated in the use of the pseudonyms Alan Smithee and Karen Eliot, represent declarative authors whose names signify multiple origins, whilst concurrently indicating a distinct body of work. The function of these names form an important context to this study, since primary research involves the construction of an experimental mode of multi-authorship utilising WikiMedia technology and the interaction of thirty nine participants, who are invited to create a body of work under the collective pseudonym Karen Karnak. The data generated by this experiment is analysed using aspects of Michel Foucault's author-function to identify and determine power structures inherent in the WikiMedia context. The interplay of power structures, including concepts such as identity, ownership and the body of work, affect the resulting mode of authorship and contribute to the construction of Karen Karnak, suggesting further areas of research into the emerging multi-author
Contribution of Information and Communication Technology (ICT) in Country’S H-Index
No full textThe aim of this study is to examine the effect of Information and Communication Technology (ICT) development on country’s scientific ranking as measured by H-index. Moreover, this study applies ICT development sub-indices including ICT Use, ICT Access and ICT skill to find the distinct effect of these sub-indices on country’s H-index. To this purpose, required data for the panel of 14 Middle East countries over the period 1995 to 2009 is collected. Findings of the current study show that ICT development increases the H-index of the sample countries. The results also indicate that ICT Use and ICT Skill sub-indices positively contribute to higher H-index but the effect of ICT access on country’s H-index is not clear
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