000 03432nam a22005055i 4500
001 978-3-0346-0433-8
003 DE-He213
005 20140220084518.0
007 cr nn 008mamaa
008 101113s2010 sz | s |||| 0|eng d
020 _a9783034604338
_9978-3-0346-0433-8
024 7 _a10.1007/978-3-0346-0433-8
_2doi
050 4 _aQA76.9.M3
072 7 _aUYZM
_2bicssc
072 7 _aUKR
_2bicssc
072 7 _aBUS083000
_2bisacsh
072 7 _aCOM032000
_2bisacsh
082 0 4 _a005.74
_223
100 1 _aArdagna, Danilo.
_eeditor.
245 1 0 _aRun-time Models for Self-managing Systems and Applications
_h[electronic resource] /
_cedited by Danilo Ardagna, Li Zhang.
264 1 _aBasel :
_bSpringer Basel,
_c2010.
300 _aIX, 185p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAutonomic Systems
505 0 _aStochastic Analysis and Optimization of Multiserver Systems -- On the Selection of Models for Runtime Prediction of System Resources -- Estimating Model Parameters of Adaptive Software Systems in Real-Time -- A Control-Theoretic Approach for the Combined Management of Quality-of-Service and Energy in Service Centers -- The Emergence of Load Balancing in Distributed Systems: the SelfLet Approach -- Run Time Models in Adaptive Service Infrastructure -- On the Modeling and Management of Cloud Data Analytics.
520 _aThis edited volume focuses on the adoption of run-time models for the design and management of autonomic systems. Traditionally, performance models have a central role in the design of computer systems. Models are used at design-time to support the capacity planning of the physical infrastructure and to analyze the effects and trade-offs of different architectural choices. Models may also be used at run-time to assess the compliance of the running system with respect to design-time models, to measure the real system performance parameters to fill the gap between design and run-time. Models at run-time can also assess the compliance of service level agreements and trigger autonomic systems re-configuration. Run-time models are receiving great interest, since, e.g., power management of CPUs and resource management in virtualized systems can be actuated at very fine grain time scales. In such situations, traditional performance techniques evaluating the systems steady state may provide only a rough estimate of system behavior and are not effective to react to workload fluctuations. This book includes advanced techniques and solutions for the run-time estimation of autonomic systems performance, the analysis of transient conditions and their application in advanced prototype environments.
650 0 _aComputer science.
650 0 _aComputer simulation.
650 0 _aInformation Systems.
650 1 4 _aComputer Science.
650 2 4 _aManagement of Computing and Information Systems.
650 2 4 _aModels and Principles.
650 2 4 _aSimulation and Modeling.
700 1 _aZhang, Li.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783034604321
830 0 _aAutonomic Systems
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-0346-0433-8
912 _aZDB-2-SCS
999 _c111114
_d111114