LEADER 05991nam 2200757 450 001 9910131281903321 005 20200520144314.0 010 $a1-119-13113-8 010 $a1-119-13115-4 010 $a1-119-13114-6 035 $a(CKB)3710000000397663 035 $a(EBL)1986955 035 $a(OCoLC)906027939 035 $a(SSID)ssj0001459791 035 $a(PQKBManifestationID)11822133 035 $a(PQKBTitleCode)TC0001459791 035 $a(PQKBWorkID)11464489 035 $a(PQKB)10440482 035 $a(MiAaPQ)EBC1986955 035 $a(Au-PeEL)EBL1986955 035 $a(CaPaEBR)ebr11048219 035 $a(CaONFJC)MIL770193 035 $a(PPN)189307781 035 $a(EXLCZ)993710000000397663 100 $a20150508h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aQuantitative assessments of distributed systems $emethodologies and techniques /$fedited by Dario Bruneo and Salvatore Distefano ; cover design by Russell Richardson 210 1$aSalem, Massachusetts ;$aHoboken, New Jersey :$cScrivener Publishing :$cWiley,$d2015. 210 4$dİ2015 215 $a1 online resource (398 p.) 225 1 $aPerformability Engineering Series 300 $aDescription based upon print version of record. 311 $a1-118-59521-1 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aCover; 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 Categories 327 $a2.2.3 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 Node 327 $a3.5 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; References 327 $a5 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 Examples 327 $a6.3 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 Monitoring 327 $a7.4.1 Monitoring Problem Scenarios 330 $a Distributed systems employed in critical infrastructures must fulfill dependability, timeliness, and performance specifications. Since these systems most often operate in an unpredictable environment, their design and maintenance require quantitative evaluation of deterministic and probabilistic timed models. This need gave birth to an abundant literature devoted to formal modeling languages combined with analytical and simulative solution techniques The aim of the book is to provide an overview of techniques and methodologies dealing with such specific issues in the context of distributed 410 0$aPerformability engineering series. 606 $aComputer systems$xEvaluation$xMathematics 606 $aSystem analysis$xMathematics 606 $aElectronic data processing$xDistributed processing$xMathematical models 606 $aQuantitative research 615 0$aComputer systems$xEvaluation$xMathematics. 615 0$aSystem analysis$xMathematics. 615 0$aElectronic data processing$xDistributed processing$xMathematical models. 615 0$aQuantitative research. 676 $a004.029 686 $aTEC008000$2bisacsh 702 $aBruneo$b Dario 702 $aDistefano$b Salvatore 702 $aRichardson$b Russell 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910131281903321 996 $aQuantitative assessments of distributed systems$92128088 997 $aUNINA