Cargando…

Temporal QOS management in scientific cloud workflow systems /

Cloud computing can provide virtually unlimited scalable high performance computing resources. Cloud workflows often underlie many large scale data/computation intensive e-science applications such as earthquake modelling, weather forecasting and astrophysics. During application modelling, these sop...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Liu, Xiao
Otros Autores: Chen, Jinjun, Yang, Yun (University lecturer)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Waltham, MA : Elsevier, 2012.
Colección:Elsevier insights.
Temas:
Acceso en línea:Texto completo

MARC

LEADER 00000cam a2200000 a 4500
001 SCIDIR_ocn778786621
003 OCoLC
005 20231117044709.0
006 m o d
007 cr cn|||||||||
008 120301s2012 mau ob 001 0 eng d
040 |a OPELS  |b eng  |e pn  |c OPELS  |d E7B  |d EBLCP  |d YDXCP  |d N$T  |d CDX  |d ITD  |d COO  |d OCLCQ  |d DEBSZ  |d OCLCQ  |d UMI  |d B24X7  |d OCLCO  |d OCLCQ  |d IDEBK  |d UKDOC  |d OCLCF  |d OCLCQ  |d A7U  |d OCLCQ  |d LIV  |d OCLCQ  |d MERUC  |d OCLCQ  |d U3W  |d D6H  |d CEF  |d OCLCQ  |d FEM  |d WYU  |d LEAUB  |d VT2  |d MUU  |d OCLCQ  |d BRF  |d VLY  |d TUHNV  |d OCLCQ  |d S2H  |d OCLCO  |d OCLCQ  |d OCLCO 
019 |a 781540793  |a 785782454  |a 817081191  |a 820028377  |a 823133495  |a 969056359  |a 1062901204  |a 1103278899  |a 1129348264  |a 1153017440  |a 1162236385  |a 1192348680  |a 1235828936  |a 1240514602  |a 1243581571  |a 1262688534  |a 1276915127 
020 |a 9780123970107  |q (electronic bk.) 
020 |a 0123970105  |q (electronic bk.) 
020 |a 9780123972958  |q (electronic bk.) 
020 |a 0123972957  |q (electronic bk.) 
020 |a 9781280581854  |q (MyiLibrary) 
020 |a 1280581859 
020 |a 9786613611635 
020 |a 6613611638 
024 8 |a 9786613611635 
035 |a (OCoLC)778786621  |z (OCoLC)781540793  |z (OCoLC)785782454  |z (OCoLC)817081191  |z (OCoLC)820028377  |z (OCoLC)823133495  |z (OCoLC)969056359  |z (OCoLC)1062901204  |z (OCoLC)1103278899  |z (OCoLC)1129348264  |z (OCoLC)1153017440  |z (OCoLC)1162236385  |z (OCoLC)1192348680  |z (OCoLC)1235828936  |z (OCoLC)1240514602  |z (OCoLC)1243581571  |z (OCoLC)1262688534  |z (OCoLC)1276915127 
050 4 |a QA76.585  |b .L58 2012 
072 7 |a COM  |x 060030  |2 bisacsh 
072 7 |a COM  |x 060080  |2 bisacsh 
082 0 4 |a 004.6782  |2 23 
100 1 |a Liu, Xiao. 
245 1 0 |a Temporal QOS management in scientific cloud workflow systems /  |c Xiao Liu, Jinjun Chen, Yun Yang. 
260 |a Waltham, MA :  |b Elsevier,  |c 2012. 
300 |a 1 online resource (xiv, 140 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file 
490 1 |a Elsevier insights 
520 |a Cloud computing can provide virtually unlimited scalable high performance computing resources. Cloud workflows often underlie many large scale data/computation intensive e-science applications such as earthquake modelling, weather forecasting and astrophysics. During application modelling, these sophisticated processes are redesigned as cloud workflows, and at runtime, the models are executed by employing the supercomputing and data sharing ability of the underlying cloud computing infrastructures. Temporal QOS Management in Scientific Cloud Workflow Systems focuses on real world scientific applications which often must be completed by satisfying a set of temporal constraints such as milestones and deadlines. Meanwhile, activity duration, as a measurement of system performance, often needs to be monitored and controlled. This book demonstrates how to guarantee on-time completion of most, if not all, workflow applications. Offering a comprehensive framework to support the lifecycle of time-constrained workflow applications, this book will enhance the overall performance and usability of scientific cloud workflow systems. Explains how to reduce the cost to detect and handle temporal violations while delivering high quality of service (QoS) Offers new concepts, innovative strategies and algorithms to support large-scale sophisticated applications in the cloud Improves the overall performance and usability of cloud workflow systems. 
505 0 |a Chapter 1 Introduction -- Chapter 2 Literature Review and Problem Analysis -- Chapter 3 A Scientific Cloud Workflow System -- Chapter 4 Novel Probabilistic Temporal Framework -- Chapter 5 Forecasting Scientific Cloud Workflow Activity Duration Intervals -- Chapter 6 Temporal Constraint Setting -- Chapter 7 Temporal Checkpoint Selection and Temporal Verification -- Chapter 8 Temporal Violation Handling Point Selection -- Chapter 9 Temporal Violation Handling -- Chapter 10 Conclusions and Contribution Bibliography. 
504 |a Includes bibliographical references and index. 
546 |a English. 
650 0 |a Cloud computing. 
650 0 |a Workflow  |x Management. 
650 6 |a Infonuagique.  |0 (CaQQLa)000263273 
650 7 |a COMPUTERS  |x Networking  |x Intranets & Extranets.  |2 bisacsh 
650 7 |a COMPUTERS  |x Web  |x General.  |2 bisacsh 
650 7 |a Cloud computing  |2 fast  |0 (OCoLC)fst01745899 
650 7 |a Workflow  |x Management  |2 fast  |0 (OCoLC)fst01180406 
700 1 |a Chen, Jinjun. 
700 1 |a Yang, Yun  |c (University lecturer) 
776 0 8 |i Print version:  |z 9780123970107  |w (OCoLC)761843513 
830 0 |a Elsevier insights. 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780123970107  |z Texto completo