Computer Science ›› 2025, Vol. 52 ›› Issue (9): 346-359.doi: 10.11896/jsjkx.240600022
• Computer Software • Previous Articles Next Articles
WANG Huiqiang, LIN Yang, LYU Hongwu
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[1]DEAVOURS D D,SANDERS W H.An efficient disk-based tool for solving large Markov models[J].Performance Evaluation,1998,33(1):67-84. [2]HILLSTON J.A Compositional Approach to Performance Mo-delling[M].Cambridge University Press,1996. [3]MANSOURI Y,PROKHORENKO V,BABAR M A.An automated implementation of hybrid cloud for performance evaluation of distributed databases[J].Journal of Network and Computer Applications,2020,167(2020):102740. [4]OLAWUMI T O,CHAN D W M.Cloud-based sustainability assessment(CSA) system for automating the sustainability decision-making process of built assets[J].Expert Systems with Application,2022,188:116020. [5]TABASSUM M,PURYEAR N,KUZLU M,et al.Performance Evaluation of a Cloud-based IoT Platform for Smart Cities:Open Cybercity[C]//Proceeding of the Mediterranean Conference on Embedded Computing.2023:1-4. [6]PATEL K,MISTRY C,GUPTA R,et al.A systematic review on performance evaluation metric selection method for IoT-based applications[J].Microprocessors and Microsystems,2023,10:80-94. [7]KADARINA T M,PRIAMBODO R.Performance Evaluation of IoT-based SpO2 Monitoring Systems for COVID-19 Patients[J].Journal of Electronics Electromedical Engineering and Me-dical Informatics,2021,3(2):64-71. [8]ZHU Y,HUANG Z Q,ZHOU H.Formal method for verifying BPEL model used by functional programming language[J].Journal of Frontiers of Computer Science & Technology,2018,12(2):185. [9]ISHIBUCHI H,NAN Y,PANG L M.Performance Evaluation of Multi-objective Evolutionary Algorithms Using Artificial and Real-world Problems[C]//Proceedings of International Confe-rence on Evolutionary Multi-Criterion Optimization.Cham:Springer,2023:333-347. [10]SHAFAEI M H,ALISHAHI M M,EMDAD H.A new hybrid crweno-mwenoz-adaptive moving mesh method for cavitating two-phase compressible fluid flow simulation[J].International Journal of Modern Physics C,2023,34(3):2350033. [11]DING J,SUN H,CHEN X,et al.Response time analysis of amanufacturing supply chain with performance evaluation process algebra[J].Computers & Industrial Engineering,2022,167:108043-108053. [12]HILLSTON J,MARIN A,PIAZZA C,et al.Persistent Stochastic Non-Interference[J].Fundamenta Informaticae,2021,181(1):1-35. [13]BOCCHI L,FIADEIRO J,GILMORE S,et al.A Formal Approach to Modelling Time Properties of Service-Oriented Systems[M]//Handbook of Research on Non-Functional Properties for Service-Oriented Systems:Future Directions.2009:1-17. [14]MARSAN M A,CONTE G,BALBO G.A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems[J].ACM Transactions on Computer Systems,1984,2(2):93-122. [15]LIN L,JIANG J C.Modeling and Analysis of Traffic Information System Based on Generalized Stochastic Petri Net[J].Chinese Journal of Computers,2005,28(1):81-87. [16]GAUR M,KANT R.A Survey on Process Algebraic Stochastic Modelling of Large Distributed Systems for Its Performance Analysis[C]//Proceedings of the International Conference on Eco-friendly Computing Communication Systems.IEEE,2015:206-211. [17]LIN C,WEI Y Y.Stochastic Process Algebras and Stochastic Petri Nets[J].Journal of Software,2002,13(2):201-213. [18]EBERSOLD S,HUANG L,KOGTENKOV A,et al.Lessonsfrom Formally Verified Deployed Software Systems[J].arXiv:2301.02206,2023. [19]XIE R.Survey of Complex System Modeling Methods[J].Mo-dern Defence Technology,2020,48(3):31. [20]ADHIKARI R,POKHAREL S.Performance Evaluation of Convolutional Neural Network Using Synthetic Medical Data Augmentation Generated by GAN[J].International Journal of Image and Graphics,2023,23(1):2350002. [21]LU Q,LI X J,GUAN Y,et al.Modeling and Analysis of RoS2 Data Distribution Service for Data FIow[J].Journal of Software,2021,32(6):1818-1829. [22]ZHANG J W,NIU B N.Overview of Modeling Methods for Database System Performance Models[J].Journal of Computer Research Applications,2019,36(3):641-656. [23]SADATI E A,CHESHMEHSOHRABI M M.Performanceevaluation of web search engines in image retrieval:An experimental study[J].Information Development,2022,38(4):522-534. [24]NEJATI F,ABDUL A A G,NG K Y,et al.Handling state space explosion in component-based software verification:A review[J].Procedia Computer Science,2021,9:77526-77544. [25]GONG X,FENG T,DU J Z.Formal modeling and security ana-lysis method of security protocol based on CPN[J].Journal on Communications,2021,42(9):240-253. [26]SANKUR O.Contributions on Formal Methods for Timed and Probabilistic Systems[J].Information Development,2023,20(2):354-370. [27]GRIMM T,DJONES L,MICHAEL H.A survey on formal verification techniques for safety-critical systems-on-chip[J].Electronics,2018,7(6):81. [28]ALSHAER S,MURALI P,ROMAN O.Model Comparative Analysis of Neighborhood Aggregation Levels in Graph Neural Networks for Metaschedulers[C]//2024 IEEE International Conference on Industrial Technology(ICIT).2024:1-7. [29]DO C M,PHYO Y,RIESCO A,et al.Optimization techniques for model checking leads-to properties in a stratified way[J].ACM Transactions on Software Engineering and Methodology,2023,32(6):1-38. [30]ZHOU S,WANG J,XUE P,et al.An Approach to the State Explosion Problem:SOPC Case Study[J].Electronics,2023,12(24):4987. [31]JAMROGA W,YAN K,DAMIAN K.Scalable Verification of Social Explainable AI by Variable Abstraction[C]//ICAART.2024:149-158. [32]SCHRICK N L,HAWRYLAK P J.State Space Explosion Mitigation for Large-Scale Attack and Compliance Graphs Using Synchronous Exploit Firing[J].IEEE Open Journal of the Computer Society,2023,4:147-157. [33]MASOOD A,PLANA R.A Predictive Dynamic Approach to Evaluating the Reliability of Passive Systems[J].Procedia Computer Science,2023,11:93784-93792. [34]BEEK M H T,LORETI M.Guest editorial for the special issue on formal methods for the quantitative evaluation of collective adaptive systems[J].ACM Transactions on Modeling and Computer Simulation,2018,28(2):1-4. [35]PREISER R,BIGGS R,DE VOS A,et al.Social-ecological systems as complex adaptive systems[J].Ecology and Society,2018,23(4):1-15. [36]HILLSTON J.Fluid flow approximation of PEPA models[C]//Proceeding of the Second International Conference on the IEEE Computer Society.2005:33-42. [37]HAYDEN R A,BRADLEY J T.Evaluating fluid semantics for passive stochastic process algebra cooperation[J].Performance Evaluation,2010,67(4):260-284. [38]BORTOLUSSI L,HILLSTON J,LORETI M.Fluid approximation of broadcasting systems[J].Theoretical Computer Science,2020,816:221-248. [39]KHADER M,INC M,AKGUL A.Numerical Appraisal for the Unsteady Casson Fluid Flow via the Method of Finite-Elements[J].Engineering,Physics,2023,30(2):454-463. [40]LYU H W,HILLSTON J,PIHO P,et al.An Attribute-Based Availability Model for Large Scale IaaS Clouds with CARMA[J].IEEE Transactions on Parallel and Distributed Systems,2020,31(3):733-748. [41]MICHAELIDES M,HILLSTON J,SANGUINETTI G.Geo-metric fluid approximation for general continuous-time Markov chains[C]//Proceedings of the Royal Society A:Mathematical,Physical and Engineering Science.2019:1-24. [42]DING J,LIN Z G,YU T.On reaction-diffusion equations derived from a PEPA model[J].Applied Mathematics Letters,2011,24(12):2072-2076. [43]NAZEER M,HUSSAIN F,TUERKYILMAZOGLU M,et al.Development of Highly Viscous Multiphase Fluid Flows:Towards an Approximate Analysis[J].Journal of Computational Biophysics and Chemistry,2023,22(3):371-381. [44]BORTOLUSSI L,HILLSTON J,GALPIN V,et al.Hybrid semantics for PEPA[C]//Proceeding of the Seventh International Conference on the Quantitative Evaluation of Systems.2010:181-190. [45]WALRAND J C.An Introduction to Queuing Networks[EB/OL].https://api.semanticscholar.org/CorpusID:59726732. [46]ERLANG A K.The theory of probabilities and telephone conversations[J].Nyt Tidsskrift for Matematik B,1909,20:33-39. [47]KUMAWAT G L,ROY D.A new solution approach for multi-stage semi-open queuing networks:An application in shuttle-based compact storage systems[J].Computers & Operations Research,2021,125(1):1-15. [48]XIE Q,JIN L.Stabilizing queuing networks with model data-independent control[J].IEEE Transactions on Control of Network Systems,2022,9(3):1317-1326. [49]ARCELLI D.Exploiting queuing networks to model and assess the performance of self-adaptive software systems:a survey[J].Procedia Computer Science,2020,170:498-505. [50]BYCHKOV I,KAZAKOV A,LEMPERT A,et al.Modeling of railway stations based on queuing networks[J].Applied Sciences,2021,11(5):2425-2440. [51]ZONDERLAND M E,BOUCHERIE R J.Queuing networks in health care systems[C]//Proceeding of Handbook of Healthcare System Scheduling.Boston:Springer,2011:201-243. [52]LEE S,SIM B,YE J C.Support Vectors and Gradient Dynamics of Single-Neuron ReLU Networks[J].arXiv:2202.05510,2022. [53]MOKA S B,NAZARATHY Y,SCHEINHARDT W.Diffusion parameters of flows in stable multi-class queueing networks[J].Queueing Systems:Theory and Applications,2023,103(4):313-346. [54]PETRI C A.Communication with Automata[D].Bonn:University of Bonn,1962. [55]TIGANE S,KAHLOUL L,HAMANI N,et al.On quantitative properties preservation in reconfigurable generalized stochastic Petri nets[J].IEEE Transactions on Systems,Man,and Cybernetics:Systems,2023,53(6):3311-3323. [56]MOHAMMED A S,KOVALENKO A,KUCHUK N.Temporary Petri-nets-based method for synthesizing network models[J].Journal of Electronic Imaging,2022,31(6):61805.1-61805.15. [57]HUANG B,ZHOU M,LU X S,et al.Scheduling of resource al-location systems with timed Petri nets:A Survey[J].ACM Computing Surveys,2023,55(11):1-27. [58]LIU X M,ZHAO M,WEI Z H,et al.The energy management and economic optimization scheduling of microgrid based on Colored Petri net and Quantum-PSO algorithm[J].Sustainable Energy Technologies and Assessments,2022,53(10):1-11. [59]LIN J C,HO I.Generating real-time software test cases by time petri nets[J].International Journal of Computers and Applications,2000,22(3):151-158. [60]NORMATOV I,YARASHOV I,BOBOQULOV B.Develop-ment of models for describing the processing of environmental information in security problems of controlling a protection system based on Petri nets[J].Central Asian Journal of Mathema-tical Theory and Computer Sciences,2022,3(12):229-239. [61]BAETEN J C M.Process Algebra[J].Cambridge Tracts in Theo-retical Computer Science,2009,18(84):109-137. [62]HERZOG U.Formal Description,Time and Performance Analysis a Framework[C]//Proceedings of Entwurf and Betrieb Verteilter System.Berlin:Springer,1990:172-190. [63]HOARE C A R.Communicating sequential processes[J].Communications of the ACM,1978,21(8):666-677. [64]BERGSTRA J A,KLOP J W.Algebra of communicating processes with abstraction[J].Theoretical Computer Science,1985,37:77-121. [65]Milner R.Communication and concurrency[EB/OL].http://purl.org/coar/resource_type/c_6501. [66]TURNER K J,SINDEREN V M.OSI Specification Style forLOTOS[J].LOTOSphere:Software Development with LOTOS,1992,5(1):1-22. [67]D’ARGENIO P R,BRINKSMA E.A Calculus for Timed Automata[C]//Proceeding of International Symposium on Formal Techniques in Real-Time and Fault-Tolerant Systems.Berlin:Springer,1996:110-129. [68]SKOU K G L A.Bisimulation through probabilistic testing[J].Information and Computation,1991,94(1):1-28. [69]WANG F,CAO Z,TAN L,et al.Formal Modeling and Performance Evaluation for Hybrid Systems:A Probabilistic Hybrid Process Algebra-Based Approach[J].International Journal of Software Engineering and Knowledge Engineering,2022,32(2):283-315. [70]KACHI F,BOUANAKA C.A hybrid model for efficient deci-sion-making in self-adaptive systems[J].Information and Software Technology,2023,153:1-19. [71]SEGALA R,LYNCH N.Probabilistic simulations for probabilistic processes[J].Nordic Journal of Computing,1995,2(2):250-273. [72]TOFTS C M N.Compositional Performance Analysis[M].Berlin:Springer,1997:290-305. [73]HANSSON H,JONSSON B.A calculus for communicating systems with time and probabilities[C]//Proceeding of the IEEE Real-Time Systems.1990:278-287. [74]NOUNOU N M.A Methodology for Specification-Based Per-formance Analysis of Protocols[EB/OL].https://api.semanticscholar.org/CorpusID:60657327. [75]GUZMÁN D,PRIETO M,SÁNCHEZ S,et al.Improving the LEON Spacecraft Computer Processor for Real-Time Perfor-mance Analysis[J].Journal of Spacecraft & Rockets,2011,48(4):671-678. [76]BERNARDO M,DONATIELLO L,GORRIERI R.A formal approach to the integration of performance aspects in the modeling and analysis of concurrent systems[J].Information and Computation,1998,144(2):83-154. [77]BOHNENKAMP H,D’ARGENIO P,HERMANNS H,et al.MODEST:A compositional modeling formalism for hard and softly timed systems[J].IEEE Transactions on Software Engineering,2006,32(10):812-830. [78]FENG C,HILLSTON J.PALOMA:A process algebra for located markovian agents[C]//Proceeding of International Confe-rence on Quantitative Evaluation of Systems.Cham:Springer,2014:265-280. [79]LORETI M,HILLSTON J.Modelling and analysis of collective adaptive systems with CARMA and its tools[C]//Proceeding of the Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems.Bertinoro:Springer,2016:83-119. [80]AUDRITO G.FCPP:an efficient and extensible field calculus framework[C]//Proceeding of 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems.2020:153-159. [81]CASADEI R,VIROLI M,AGUZZI G,et al.Scafi:A scala DSL and toolkit for aggregate programming[J].SoftwareX,2022,20:101248. [82]D’ARGENIO P,KATOEN J P,BRINKSMA H.An Algebraic Approach to the Specification of Stochastic Sy-stems[C]//Proceeding of Chapman Hall Programming Concepts and Methods.New York:Springer,1998:126-147. [83]OROZCO K J G,RIVERA A G,ALMARAZ A M D L,et al.Service level analysis for an automotive prototype manufacturing company through the application of discrete event modelling and simulation[J].International Journal of Simulation & Process Modelling,2022,18(1):11-22. [84]FOISSY L,PENG X S.Typed angularly decorated planar rooted trees and generalized Rota-Baxter algebras[J].Journal of Algebraic Combinatorics,2021,57(1):271-303. [85]RYDER T,PRANGLE D,GOLIGHTLY A,et al.The Neural Moving Average Model for Scalable Variational Inference of State Space Models[J].Uncertainty in Artificial Intelligence,2021,161:12-22. [86]OHIGASHI Y,ISHIKAWA S,OMORI T.Model-based statespace segmentation for finding suitable procedure in game task[J].Ieice Technical Report Neurocomputing,2022:15(1):1-6. [87]NEWMAN K,KING R,VÍCTOR E,et al.State-space models for ecological time-series data:Practical model-fitting[J].Me-thods in Ecology and Evolution,2023,14:26-42. [88]MORIMOTO M,FUKAMI K,MAULIK R,et al.Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression[J].Physica D,2022,440:133454. [89]TSCHAIKOWSKI M,TRIBASTONE M.Exact fluid lumpability in Markovian process algebra[J].Theoretical Computer Science,2014,538(9):140-166. [90]MOHAMMAD-DJAFARI A,MOHAMMADPOOR A,BALIN.Hierarchical Markovian models for hyperspectral image segmentation[C]//Proceeding of the International Workshop on Intelligent Computing in Pattern Analysis and Synthesis.Berlin:Springer,2007:416-424. [91]GILMORE S,HILLSTON J,RIBAUDO M.An efficient algorithm for aggregating pepa models[J].IEEE Transactions on Software Engineering,2001,27(5):449-464. [92]MATEU V,PETCU D,KIANI J.Solving Anonymous Voting Security Protocol with Hybrid Method[J].International Journal of Information Security,2024,15:211-221. [93]CARABALLO L E,DIAZ-BANEZ J M,FABILA-MONROY R,et al.Stochastic strategies for patrolling a terrain with a synchronized multi-robot system[J].European Journal of Operational Research,2022,30(1):1-18. [94]MOREAUX P.Performance models with product form steady-state distributions[C]//Proceeding of the First International Conference on Verification and Evaluation of Computer and Communication Systems.2007:11-12. [95]HILLSTON J,MARIN A,ROSSI S.Contextual Lumpability[C]//Proceeding of the 7th International Conference on Performance Evaluation Methodologies and Tools.2014:194-203. [96]HERMANNS H,KATOEN J P.Automated compositionalMarkov chain generation for a plain-old telephone system[J].Science of Computer Programming,2000,36(1):97-127. [97]POURRANJBAR A,HILLSTON J.An Aggregation Technique For Large-Scale PEPA Models With Non-Uniform Populations.Institute for Computer Sciences[C]//Proceeding of 7th International Conference on Performance Evaluation Methodologies and Tools.2013:20-29. [98]MARTINOLI A,IJSPEERT A,GAMBARDELLA L M.Aprobabilistic model for understanding and comparing collective aggregation mechanisms[C]//Proceeding of the Advances in Artificial Life.Torino:Springer,2022:575-584. [99]NEUMANN V J,MORGENSTERN O.Theory of games andeconomic behavior[J].The Review of Economics and Statistics,1944,29(1):47-52. [100]CHAUM D.Untraceable electronic mail,return addresses anddigital pseudonyms[J].Communications of the ACM,1981,24(2):84-88. [101]BRADLEY J T,GILMORE S T.Stochastic Simulation Methods Applied to a Secure Electronic Voting Model[J].Electronic Notes in Theoretical Computer Science,2006,151(3):5-25. [102]GILLESPIE D T.Exact stochastic simulation of coupled chemical reactions[J].The Journal of Physical Chemistry,1977,81(25):2340-2361. [103]BRADLEY J T,GILMORE S T,THOMAS N.Performanceanalysis of stochastic process algebra models using stochastic simulation[C]//Proceeding of the 20th International Parallel and Distributed Processing Symposium.IEEE,2006:25-29. [104]TURNER T E,SCHNELL S,BURRAGE K.Review:Stochastic approaches for modelling in vivo reactions[J].Computational Biology and Chemistry,2004,28(3):165-178. [105]PTZSCHE C.Ordinary Differential Equations and DynamicalSystems[J].Internationale Mathematische Nachrichten,2013,67(223):51-52. [106]TRIBASTONE M,GILMORE S,HILLSTON J.Scalable diffe-rential analysis of process algebra models[J].IEEE Transactions on Software Engineering,2012,38(1):205-219. [107]BRADLEY J T,GILMORE S T,HILLSTON J.Analysing distributed internet worm attacks using continuous state-space approximation of process algebra models[J].Journal of Computer and System Sciences,2008,74(6):1013-1032. [108]MASSINK M,HARRISON M,LATELLA D.Scalable analysis of collective behaviour in smart service systems[C]//Proceeding of the 2010 ACM Symposium on Applied Computing.ACM,2010:1173-1180. [109]DUGUID A.Coping with the Parallelism of BitTorrent:Conversion of PEPA to ODEs in Dealing with State Space Explosion[C]//Proceeding of the International Conference on Formal Modeling and Analysis of Timed Systems.Berlin:Springer,2006:150-176. [110]BRAVETTI M,GILMORE S,GUIDI C,et al.Replicating web services for scalability[C]//Proceeding of the Trustworthy Global Computing.Springer,2007:204-221. [111]ANG P S,TEO D C H,DORAJOO S R,et al.Augmenting Pro-duct Defect Surveillance Through Web Crawling and Machine Learning in Singapore[J].Drug Safety,2021,44(9):939-948. [112]GAUR M,KANT R.A Survey on Process Algebraic Stochastic Modelling of Large Distributed Systems for Its Performance Analysis[C]//Proceeding of the International Conference on Eco-friendly Computing Communication Systems.IEEE,2015:206-211. [113]DING J,GU H,LIN Z.Fundamental results on the reaction-diffusion equations associated with a PEPA model[J].Applied Mathematical Modelling,2013,37(3):636-648. [114]POSTELWAIT J.Rugged Field Computing[J].T&D World,2023,5(75):1-52. |
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