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Naive Bayesian Based Target Selection for Distributed Real-Time System - A new target selection approach for achieving timeliness in distributed real-time system - Garg, Radhika
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Garg, Radhika:
Naive Bayesian Based Target Selection for Distributed Real-Time System - A new target selection approach for achieving timeliness in distributed real-time system - Taschenbuch

2010, ISBN: 9783639184716

[ED: Taschenbuch / Paperback], [PU: VDM Verlag Dr. Müller], This book introduces an innovative yet very simple approach to solve the most important issue in distributed real-time environment - target selection for task migration. It addresses inherent in-deterministic network delay and difficulty to predict the behavior of participating nodes in target selection. In this approach, nodes use Naive Bayesian classifier to dynamically learn the behavior of buddy nodes over a period of time. This information educates the node about the job arrival pattern on the remote node, load information and responses to the previous migration attempts. With this constantly updated information, nodes probabilistically estimate the best buddy node for migration. Naive Bayesian approach incurs minimal computational overhead, making the target selection highly efficient and is very effective in heterogeneous distributed environment as well. This book also discusses architecture of a new distributed real-time OS RK+OpenMosix designed to achieve decentralize online task scheduling and independence from underlying network architecture. This was also used as a baseline to compare the performance of Naive-Bayesian classifier based target selection approach., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 96, Selbstabholung und Barzahlung, PayPal, offene Rechnung, Banküberweisung, Interntationaler Versand

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Naive Bayesian Based Target Selection for Distributed Real-Time System - Radhika Garg
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ISBN: 9783639184716

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This book introduces an innovative yet very simple approach to solve the most important issue in distributed real-time environment - target selection for task migration. It addresses inherent in-deterministic network delay and difficulty to predict the behavior of participating nodes in target selection. In this approach, nodes use Naive Bayesian classifier to dynamically learn the behavior of buddy nodes over a period of time. This information educates the node about the job arrival pattern on the remote node, load information and responses to the previous migration attempts. With this constantly updated information, nodes probabilistically estimate the best buddy node for migration. Naive Bayesian approach incurs minimal computational overhead, making the target selection highly efficient and is very effective in heterogeneous distributed environment as well. This book also discusses architecture of a new distributed real-time OS RK+OpenMosix designed to achieve decentralize online task scheduling and independence from underlying network architecture. This was also used as a baseline to compare the performance of Naive-Bayesian classifier based target selection approach. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Informatik & EDV, [PU: VDM Verlag Dr. Müller, Saarbrücken]

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Naive Bayesian Based Target Selection for Distributed Real-Time System ab 48.99 EURO A new target selection approach for achieving timeliness in distributed real-time system Naive Bayesian Based Target Selection for Distributed Real-Time System ab 48.99 EURO A new target selection approach for achieving timeliness in distributed real-time system Bücher > English, International > Gebundene Ausgaben, [PU: VDM Verlag Dr. Müller, Saarbrücken]

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Naive Bayesian Based Target Selection for Distributed Real-Time System:A new target selection approach for achieving timeliness in distributed real-time system Radhika Garg Naive Bayesian Based Target Selection for Distributed Real-Time System:A new target selection approach for achieving timeliness in distributed real-time system Radhika Garg Bücher > English, International > Gebundene Ausgaben, VDM Verlag

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Naive Bayesian Based Target Selection for Distributed Real-Time System:A new target selection approach for achieving timeliness in distributed real-time system Radhika Garg Naive Bayesian Based Target Selection for Distributed Real-Time System:A new target selection approach for achieving timeliness in distributed real-time system Radhika Garg Bücher > Ratgeber > Computer & Internet, VDM Verlag

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Naive Bayesian Based Target Selection for Distributed Real-Time System

This book introduces an innovative yet very simple approach to solve the most important issue in distributed real-time environment - target selection for task migration. It addresses inherent in-deterministic network delay and difficulty to predict the behavior of participating nodes in target selection. In this approach, nodes use Naive Bayesian classifier to dynamically learn the behavior of buddy nodes over a period of time. This information educates the node about the job arrival pattern on the remote node, load information and responses to the previous migration attempts. With this constantly updated information, nodes probabilistically estimate the best buddy node for migration. Naive Bayesian approach incurs minimal computational overhead, making the target selection highly efficient and is very effective in heterogeneous distributed environment as well. This book also discusses architecture of a new distributed real-time OS RK+OpenMosix designed to achieve decentralize online task scheduling and independence from underlying network architecture. This was also used as a baseline to compare the performance of Naive-Bayesian classifier based target selection approach.

Detailangaben zum Buch - Naive Bayesian Based Target Selection for Distributed Real-Time System


EAN (ISBN-13): 9783639184716
ISBN (ISBN-10): 3639184718
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: Vdm Verlag Feb 2010

Buch in der Datenbank seit 10.02.2007 09:02:13
Buch zuletzt gefunden am 17.09.2017 21:26:59
ISBN/EAN: 9783639184716

ISBN - alternative Schreibweisen:
3-639-18471-8, 978-3-639-18471-6


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