00904nam0-22003011i-450-99000723093040332120120111133146.0000723093FED01000723093(Aleph)000723093FED0100072309320021021d1985----km-y0itay50------baitaITTendenze innovative nella formazione continuaItalia e paesi della Comunità europeaa cura di Luciano OsbatMilanoFrancoAngeli1985140 p.21 cmFondazione Giulio PastoreSez. Economia e sociologia del lavoro3331306Osbat,LucianoITUNINARICAUNIMARCBK990007230930403321B-XII-52427 dip.DDRCDDRCTendenze innovative nella formazione continua687487UNINA03142nam 2200589Ia 450 991045049550332120200520144314.0(CKB)1000000000243444(SSID)ssj0000280510(PQKBManifestationID)11240785(PQKBTitleCode)TC0000280510(PQKBWorkID)10269137(PQKB)11038962(MiAaPQ)EBC3306872(CaSebORM)0738499137(Au-PeEL)EBL3306872(CaPaEBR)ebr10113034(OCoLC)137342307(EXLCZ)99100000000024344420040610d2003 uy 0engurcn|||||||||txtccrIBM e server pSeries Cluster systems handbook[electronic resource] /[Dino Quintero ... et al.]1st ed.[S.l.] IBM, International Technical Support Organizationc2003xiv, 278 p. illIBM redbooks"October 2003."0-7384-9913-7 Includes bibliographical references and index.The IBM eServer Cluster 1600 server, which was introduced to meet the rigorous demands of mission-critical enterprise applications, continues to offer outstanding performance, scalability, reliability, availability, serviceability, and management capabilities. In this IBM Redbooks publication, we highlight the benefits of using a Cluster 1600, and describe which hardware components can be managed by either Parallel System Support Programs (PSSP) Version 3, Release 5, or Cluster Systems Management (CSM) Version 1, Release 3, Modification 2. This publication contains the following information on the Cluster 1600: - Cluster 1600 hardware components - Networking components and considerations - Cluster 1600 software components - Scalability of the Cluster 1600 - Solutions and offerings scenarios The Cluster 1600 helps to reduce the complexities and costs of system management, thus lowering the total cost of ownership and allowing simplification of application service level management. It also provides the infrastructure that supports availability, data sharing, and response time. This book will be useful for IT professionals seeking to implement Cluster 1600 mission-critical solutions to address business intelligence applications, server consolidation, and collaborative computing.IBM redbooks.Parallel computersIBM RISC System/6000 computersFile organization (Computer science)Electronic books.Parallel computers.IBM RISC System/6000 computers.File organization (Computer science)004/.35Quintero Dino865496International Business Machines Corporation.International Technical Support Organization.MiAaPQMiAaPQMiAaPQBOOK9910450495503321IBM e server pSeries Cluster systems handbook2175729UNINA05991nam 2200757 450 991080954650332120200520144314.01-119-13113-81-119-13115-41-119-13114-6(CKB)3710000000397663(EBL)1986955(OCoLC)906027939(SSID)ssj0001459791(PQKBManifestationID)11822133(PQKBTitleCode)TC0001459791(PQKBWorkID)11464489(PQKB)10440482(MiAaPQ)EBC1986955(Au-PeEL)EBL1986955(CaPaEBR)ebr11048219(CaONFJC)MIL770193(PPN)189307781(EXLCZ)99371000000039766320150508h20152015 uy 0engur|n|---|||||txtccrQuantitative assessments of distributed systems methodologies and techniques /edited by Dario Bruneo and Salvatore Distefano ; cover design by Russell RichardsonSalem, Massachusetts ;Hoboken, New Jersey :Scrivener Publishing :Wiley,2015.©20151 online resource (398 p.)Performability Engineering SeriesDescription based upon print version of record.1-118-59521-1 Includes bibliographical references at the end of each chapters and index.Cover; Title Page; Copyright Page; Contents; Preface; PART I VERIFICATION; 1 Modeling and Verification of Distributed Systems Using Markov Decision Processes; 1.1 Introduction; 1.2 Markov Decision Processes; 1.3 Markov Decision Well-Formed Net formalism; 1.4 Case study: Peer-to-Peer Botnets; 1.5 Conclusion; Appendices: Well-formed Net Formalism; A.0.1 Syntax of Basic Predicates; A.0.2 Markings and Enabling; References; 2 Quantitative Analysis of Distributed Systems in Stoklaim: A Tutorial; 2.1 Introduction; 2.2 StoKlaim: Stochastic Klaim; 2.2.1 Klaim in a Nutshell; 2.2.2 Syntactic Categories2.2.3 StoKlaim Syntax2.2.4 StoKlaim at Work; 2.3 StoKlaim Operational Semantics; 2.3.1 Rate Transition Systems; 2.3.2 StoKlaim: RTS-based Semantics; 2.4 MoSL: Mobile Stochastic Logic; 2.5 jSAM: Java Stochastic Model-Checker; 2.6 Leader Election in StoKlaim; 2.6.1 As far as it can; 2.6.2 Asynchronous Leader Election; 2.7 Concluding Remarks; References; 3 Stochastic Path Properties of Distributed Systems: the CSLTA Approach; 3.1 Introduction; 3.2 The Reference Formalisms for System Definition; 3.3 The Formalism for Path Property Definition: CSLTA; 3.4 CSLTA at work: a Fault-Tolerant Node3.5 Literature Comparison3.6 Summary and Final Remarks; References; PART II EVALUATION; 4 Failure Propagation in Load-Sharing Complex Systems; 4.1 Introduction; 4.2 Building Blocks; 4.2.1 Coarse-grained Modeling; 4.2.2 Abstract Mechanisms Impacting the Failure Occurrence; 4.2.3 Parametric Distributions Revisited; 4.2.4 Exponential Distribution; 4.2.5 Weibull Distribution; 4.2.6 Lognormal Distribution; 4.2.7 Other Distributions; 4.3 Sand Box for Distributed Failures; 4.3.1 Failure Modes; 4.3.2 LOS and Stress Rupture; 4.4 Summary; References5 Approximating Distributions and Transient Probabilities by Matrix Exponential Distributions and Functions5.1 Introduction; 5.2 Phase Type and Matrix Exponential Distributions; 5.3 Bernstein Polynomials and Expolynomials; 5.4 Application of BEs to Distribution Fitting; 5.5 Application of BEs to Transient Probabilities; 5.6 Conclusions; References; 6 Worst-Case Analysis of Tandem Queueing Systems Using Network Calculus; 6.1 Introduction; 6.2 Basic Network Calculus Modeling: Per-fl ow Scheduling; 6.2.1 Service Curve; 6.2.2 Arrival Curve; 6.2.3 Delay and Backlog Bounds; 6.2.4 Numerical Examples6.3 Advanced Network Calculus Modeling: Aggregate Multiplexing6.3.1 Aggregate-multiplexing Schemes; 6.4 Tandem Systems Traversed by Several Flows; 6.4.1 Model; 6.4.2 Loss of the Tightness; 6.4.3 Separated-flow Analysis; 6.5 Mathematical Programming Approach; 6.5.1 Blind Multiplexing; 6.5.2 FIFO Multiplexing; 6.6 Related Work; 6.7 Numerical Results; 6.8 Conclusions; References; 7 Cloud Evaluation: Benchmarking and Monitoring; 7.1 Introduction; 7.2 Benchmarking; 7.2.1 Benchamrking State of Art; 7.2.2 Benchmarking Big Data Services; 7.3 Benchmarking with mOSAIC; 7.4 Monitoring7.4.1 Monitoring Problem Scenarios Distributed systems employed in critical infrastructures must fulfill dependability, timeliness, and performance specifications. Since these systems most often operate in an unpredictable environment, their design and maintenance require quantitative evaluation of deterministic and probabilistic timed models. This need gave birth to an abundant literature devoted to formal modeling languages combined with analytical and simulative solution techniques The aim of the book is to provide an overview of techniques and methodologies dealing with such specific issues in the context of distributed Performability engineering series.Computer systemsEvaluationMathematicsSystem analysisMathematicsElectronic data processingDistributed processingMathematical modelsQuantitative researchComputer systemsEvaluationMathematics.System analysisMathematics.Electronic data processingDistributed processingMathematical models.Quantitative research.004.029TEC008000bisacshBruneo DarioDistefano SalvatoreRichardson RussellMiAaPQMiAaPQMiAaPQBOOK9910809546503321Quantitative assessments of distributed systems3922795UNINA