Filters








31 Hits in 5.6 sec

Performance Analysis of Apache Storm Applications Using Stochastic Petri Nets

Jose-Ignacio Requeno, Jose Merseguer, Simona Bernardi
2017 2017 IEEE International Conference on Information Reuse and Integration (IRI)  
The design with UML, using a novel profile for Apache Storm, allowing performance metrics definition. The transformation of the design into a performance model, concretely stochastic Petri nets.  ...  Real-time data-processing applications, such as those developed using Apache Storm, need to address highly demanding performance requirements.  ...  We have used Generalized Stochastic Petri Nets as the formalism for performance analysis.  ... 
doi:10.1109/iri.2017.64 dblp:conf/iri/RequenoMB17 fatcat:44jk4zvvs5dgpfh3phcloddgpm

Quantitative Analysis of Apache Storm Applications: The NewsAsset Case Study

José I. Requeno, José Merseguer, Simona Bernardi, Diego Perez-Palacin, Giorgos Giotis, Vasilis Papanikolaou
2018 Information Systems Frontiers  
Later, we transformed said DSML into an appropriate language for performance evaluation, specifically, stochastic Petri nets.  ...  Our assessment approach, guided by the Unified Modeling Language (UML), takes advantage, for performance analysis, of the software designs already used for development.  ...  Generalised stochastic Petri nets (Chiola et al., 1993) , the formalism for performance analysis that we adopt here, have been already used for the performance assessment of Apache Hadoop MapReduce (  ... 
doi:10.1007/s10796-018-9851-x fatcat:626qdqr5r5eojm567dio3ybzki

Towards the Performance Analysis of Apache Tez Applications

José Ignacio Requeno, Iñigo Gascón, José Merseguer
2018 Companion of the 2018 ACM/SPEC International Conference on Performance Engineering - ICPE '18  
For the simulation, we propose to transform the stereotypes of the prole into stochastic Petri nets, which can be eventually used for computing performance metrics.  ...  Apache Tez is an application framework for large data processing using interactive queries.  ...  Generalized stochastic Petri nets (GSPNs [4] ), the formalism for performance analysis that we adopt here, have been successfully used for the performance assessment of Apache Hadoop MapReduce [3] ,  ... 
doi:10.1145/3185768.3186284 dblp:conf/wosp/RequenoGM18 fatcat:x7gw36c3gzev7frewamqriweji

Tulsa: A Tool for Transforming UML to Layered Queueing Networks for Performance Analysis of Data Intensive Applications [chapter]

Chen Li, Taghreed Altamimi, Mana Hassanzadeh Zargari, Giuliano Casale, Dorina Petriu
2017 Lecture Notes in Computer Science  
Motivated by the problem of detecting software performance anti-patterns in data-intensive applications (DIAs), we present a tool, Tulsa, for transforming software architecture models specified through  ...  Storm.  ...  Several approaches have been proposed for generating performance models, such as queueing networks [1] , stochastic Petri nets [3] and layered queueing networks (LQNs) [6] from architecture models  ... 
doi:10.1007/978-3-319-66335-7_18 fatcat:2ssm5xoyerdujjim3esvpqvxl4

Model-driven development of data intensive applications over cloud resources

Rafael Tolosana-Calasanz, José Ángel Bañares, José-Manuel Colom
2018 Future generations computer systems  
The central role is assigned to a set of Petri Net models for specifying functional and non-functional requirements.  ...  is assigned to a set of Petri Net models describing the functionality required and its behaviour from a non-functional perspective.  ...  GreatSPN2.0 (GSPN) is a software package for the modelling, validation, and performance evaluation of distributed systems using Generalised Stochastic Petri Nets and their coloured extension.  ... 
doi:10.1016/j.future.2017.12.046 fatcat:ucynjx7ayrgkth36x3z64cenyy

Modeling Web Client and System Behavior

Tomasz Rak
2020 Information  
Therefore we propose Queueing Petri Nets, the new modeling methodology for dealing with performance issues of production systems. We follow the simulation-based approach.  ...  The creation of performance models requires significant effort. In the article, we want to present various performance models of customer and Web systems.  ...  The author used Generalized Stochastic Petri Nets for performance checking.  ... 
doi:10.3390/info11060337 fatcat:uhtjtb55f5achjdqbggjdcnoa4

Programming big data analysis: principles and solutions

Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio
2022 Journal of Big Data  
of using them to implement Big Data analysis applications.  ...  we describe the most used systems for Big Data analysis (e.g., Hadoop, Spark, and Storm).  ...  Acknowledgements This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 955558.  ... 
doi:10.1186/s40537-021-00555-2 fatcat:enecmxiulnhrlhdly4ihsnoc64

PerTract: Model Extraction and Specification of Big Data Systems for Performance Prediction by the Example of Apache Spark and Hadoop

Johannes Kroß, Helmut Krcmar
2019 Big Data and Cognitive Computing  
We evaluate our approach by predicting the performance of linear regression and random forest applications of the HiBench benchmark suite.  ...  Evaluating and predicting the performance of big data applications are required to efficiently size capacities and manage operations.  ...  [29] also shows an approach to transform these models into stochastic Petri nets, which is intended to allow for evaluating performance requirements.  ... 
doi:10.3390/bdcc3030047 fatcat:dnbi74dnqbfd3ci6djrbhxmgje

Orchestrating BigData Analysis Workflows

Rajiv Ranjan, Saurabh Garg, Ali Reza Khoskbar, Ellis Solaiman, Philip James, Dimitrios Georgakopoulos
2017 IEEE Cloud Computing  
ACKNOWLEDGEMENT The authors would like thank Mazin Yousif (EIC, IEEE Cloud Computing) and Ivona Brandic (TU Wien, Austria) for their valuable feedback, which significantly contributed to improving quality of  ...  cannot deal with Edge resources.Another example of applying analytical techniques for composing BigData applications is the performanceanalysis of QoS models based on queuing networksand stochastic Petri  ...  Other works aimed at analysing the MapReduce paradigm usingstochastic Petri nets as well as process algebras and Markov chains are [3] [4] .  ... 
doi:10.1109/mcc.2017.55 fatcat:i7xqytpawnhbveohyc2kfwnx3q

A Survey on Automatic Parameter Tuning for Big Data Processing Systems

Herodotos Herodotou, Yuxing Chen, Jiaheng Lu
2020 ACM Computing Surveys  
The use of automated parameter tuning techniques is a promising, yet challenging approach for optimizing system performance.  ...  ., Hadoop, Spark, Storm) contain a vast number of configuration parameters controlling parallelism, I/O behavior, memory settings, and compression.  ...  Next, they apply transformation patterns to convert the UML to performance models using Generalized Stochastic Petri Nets.  ... 
doi:10.1145/3381027 fatcat:7aglimtuwze25boptuano4ufdy

The Real Time Big Data Processing Framework Advantages and Limitations

Vairaprakash Gurusamy, S. Kannan, K. Nandhini
2017 International Journal of Computer Sciences and Engineering  
Recently, cloud computing technology has attracted much attention with high-performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied.  ...  Especially, with the development of internet of things, how to processing large amount real-time data has become a great challenge in research and applications.  ...  Conflicts of Interest The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.26438/ijcse/v5i12.305312 fatcat:bpvvqm4wsbcvve3ttdivwwoyoa

An efficient method for uncertainty propagation in robust software performance estimation

Aldeida Aleti, Catia Trubiani, André van Hoorn, Pooyan Jamshidi
2018 Journal of Systems and Software  
To address the computational inefficiency of existing approaches, we employ Polynomial Chaos Expansion (PCE) as a rigorous method for uncertainty propagation and further extend its use to robust performance  ...  Through three very different case studies from different phases of software development and heterogeneous application domains, we show that PCE can accurately (>97\%) estimate the robustness of various  ...  At this stage, performance models (e.g., Petri Nets [2] , Queueing Networks [3] , Layered Queueing Networks (LQN) [4] ) are used to describe how system operations use resources, and how resource contention  ... 
doi:10.1016/j.jss.2018.01.010 fatcat:abx66xiuqbh3lmq2iw3snfkzze

Self-awareness of Cloud Applications [chapter]

Alex Iosup, Xiaoyun Zhu, Arif Merchant, Eva Kalyvianaki, Martina Maggio, Simon Spinner, Tarek Abdelzaher, Ole Mengshoel, Sara Bouchenak
2017 Self-Aware Computing Systems  
In this chapter, we propose a conceptual framework for analyzing state-of-the-art self-awareness approaches used in the context of cloud applications.  ...  To address the scale, growth, and reliability of cloud applications, self-aware management and scheduling are becoming commonplace. How are they used in practice?  ...  national program COM-MIT and COMMissioner sub-project, by the Dutch KIEM project KIESA, and by a generous ERO gift from Oracle, by the European FP7 research project AMADEOS Grant Agreement 610535 on Systems of  ... 
doi:10.1007/978-3-319-47474-8_20 fatcat:ckcxfmjmvvas5bhg7wp5qfmehy

Transfer Learning for Improving Model Predictions in Highly Configurable Software [article]

Pooyan Jamshidi, Miguel Velez, Christian Kästner, Norbert Siegmund, Prasad Kawthekar
2017 arXiv   pre-print
We propose a different solution: Instead of taking the measurements from the real system, we learn the model using samples from other sources, such as simulators that approximate performance of the real  ...  In a self-adaptation context, we are often interested in reasoning about the performance of the systems under different configurations.  ...  Kaestner's work is also supported by NSF awards 1318808 and 1552944 and the Science of Security Lablet (H9823014C0140). Siegmund's work is supported by the DFG under the contract SI 2171/2.  ... 
arXiv:1704.00234v2 fatcat:4rja3jewinfjrb2zvkxy6kegmq

Learning to sample: exploiting similarities across environments to learn performance models for configurable systems

Pooyan Jamshidi, Miguel Velez, Christian Kästner, Norbert Siegmund
2018 Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering - ESEC/FSE 2018  
With both synthetic benchmarks and several real systems, we demonstrate that L2S outperforms state of the art performance learning and transfer-learning approaches in terms of measurement effort and learning  ...  To identify how options and interactions affect the performance of a system, several sampling and learning strategies have been recently proposed.  ...  They are used for identifying performance bottlenecks so that developers can redesign the system. Queuing networks, Petri Nets, and Stochastic Process Algebras are commonly used [20] .  ... 
doi:10.1145/3236024.3236074 dblp:conf/sigsoft/JamshidiVKS18 fatcat:ctbkc6uqxvexlbzcivw5mtmjl4
« Previous Showing results 1 — 15 out of 31 results