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Perez-Palacin, DiegoORCID iD iconorcid.org/0000-0002-2736-845X
Publications (10 of 27) Show all publications
Bernardi, S., Domínguez, J. L., Gómez, A., Joubert, C., Merseguer, J., Perez-Palacin, D., . . . Romeu, A. (2018). A systematic approach for performance assessment using process mining: An industrial experience report. Journal of Empirical Software Engineering, 23(6), 3394-3441
Open this publication in new window or tab >>A systematic approach for performance assessment using process mining: An industrial experience report
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2018 (English)In: Journal of Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 23, no 6, p. 3394-3441Article in journal (Refereed) Published
Abstract [en]

Software performance engineering is a mature field that offers methods to assess system performance. Process mining is a promising research field applied to gain insight on system processes. The interplay of these two fields opens promising applications in the industry. In this work, we report our experience applying a methodology, based on process mining techniques, for the performance assessment of a commercial data-intensive software application. The methodology has successfully assessed the scalability of future versions of this system. Moreover, it has identified bottlenecks components and replication needs for fulfilling business rules. The system, an integrated port operations management system, has been developed by Prodevelop, a medium-sized software enterprise with high expertise in geospatial technologies. The performance assessment has been carried out by a team composed by practitioners and researchers. Finally, the paper offers a deep discussion on the lessons learned during the experience, that will be useful for practitioners to adopt the methodology and for researcher to find new routes.

Place, publisher, year, edition, pages
Springer, 2018
Keywords
Software performance, Process mining, Unified modeling language, Complex event processing, Stochastic petri net
National Category
Computer Sciences
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-74460 (URN)10.1007/s10664-018-9606-9 (DOI)
Projects
H2020 DICE, Grant Agreement No. 644869CyCriSec-TIN2014-58457-R
Funder
EU, Horizon 2020, 644869
Available from: 2018-05-22 Created: 2018-05-22 Last updated: 2018-12-11Bibliographically approved
Garcia-Valls, M., Perez-Palacin, D. & Mirandola, R. (2018). Pragmatic cyber physical systems design based on parametric models. Journal of Systems and Software, 144, 559-572
Open this publication in new window or tab >>Pragmatic cyber physical systems design based on parametric models
2018 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 144, p. 559-572Article in journal (Refereed) Published
Abstract [en]

The adaptive nature of cyber physical systems (CPS) comes from the fact that they are deeply immersed in the physical environments that are inherently dynamic. CPS also have stringent requirements on real-time operation and safety that are fulfilled by rigorous model design and verification. In the real-time literature, adaptation is mostly limited to off-line modeling of well known and predicted transitions; but this is not appropriate for cyber physical systems as each transition can have unique and unknown characteristics. In the adaptive systems literature, adaptation solutions are silent about timely execution and about the underlying hardware possibilities that can potentially speed up execution. This paper presents a solution for designing adaptive cyber physical systems by using parametric models that are verified during the system execution (i.e., online), so that adaptation decisions are made based on the timing requirements of each particular adaptation event. Our approach allows the system to undergo timely adaptations that exploit the potential parallelism of the software and its execution over multicore processors. We exemplify the approach on a specific use case with autonomous vehicles communication, showing its applicability for situations that require time-bounded online adaptations.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
CPS, Autonomous systems, Adaptive systems, Verification
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-78408 (URN)10.1016/j.jss.2018.06.044 (DOI)000445441100032 ()
Available from: 2018-10-22 Created: 2018-10-22 Last updated: 2018-10-22Bibliographically approved
Requeno, J. I., Merseguer, J., Bernardi, S., Perez-Palacin, D., Giotis, G. & Papanikolaou, V. (2018). Quantitative Analysis of Apache Storm Applications: The NewsAsset Case Study. Information Systems Frontiers
Open this publication in new window or tab >>Quantitative Analysis of Apache Storm Applications: The NewsAsset Case Study
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2018 (English)In: Information Systems Frontiers, ISSN 1387-3326, E-ISSN 1572-9419Article in journal (Refereed) Epub ahead of print
Abstract [en]

The development of Information Systems today faces the era of Big Data. Large volumes of information need to be processed in real-time, for example, for Facebook or Twitter analysis. This paper addresses the redesign of NewsAsset, a commercial product that helps journalists by providing services, which analyzes millions of media items from the social network in real-time. Technologies like Apache Storm can help enormously in this context. We have quantitatively analyzed the new design of NewsAsset to assess whether the introduction of Apache Storm can meet the demanding performance requirements of this media product. Our assessment approach, guided by the Unified Modeling Language (UML), takes advantage, for performance analysis, of the software designs already used for development. In addition, we converted UML into a domain-specific modeling language (DSML) for Apache Storm, thus creating a profile for Storm. Later, we transformed said DSML into an appropriate language for performance evaluation, specifically, stochastic Petri nets. The assessment ended with a successful software design that certainly met the scalability requirements of NewsAsset.

Place, publisher, year, edition, pages
Springer, 2018
Keywords
Apache Storm, UML, Petri nets, Software Performance, Software reuse
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-77364 (URN)10.1007/s10796-018-9851-x (DOI)
Projects
H2020 DICE - Grant Agreement 644869Spanis Ministry of Economy and Competitiveness TIN2014-58457-R
Funder
EU, European Research Council, 644869
Available from: 2018-08-28 Created: 2018-08-28 Last updated: 2018-08-31
Perez-Palacin, D., Mirandola, R. & Merseguer, J. (2017). Accurate modeling and efficient QoS analysis of scalable adaptive systems under bursty workload. Journal of Systems and Software, 130, 24-41
Open this publication in new window or tab >>Accurate modeling and efficient QoS analysis of scalable adaptive systems under bursty workload
2017 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 130, p. 24-41Article in journal (Refereed) Published
Abstract [en]

Fulfillment of QoS requirements for systems deployed in the Internet is becoming a must. A widespread characteristic of this kind of systems is that they are usually subject to highly variable and bursty workloads. The allocation of resources to fulfill QoS requirements during the peak workloads could entail a waste of computing resources. A solution is to provide the system with self-adaptive techniques that can allocate resources only when and where they are required. We pursue the QoS evaluation of workload-aware self-adaptive systems based on stochastic models. In particular, this work proposes an accurate modeling of the workload variability and burstiness phenomena based on previous approaches that use Markov Modulated Poisson Processes. We extend these approaches in order to accurately model the variations of the workload strongly influence the QoS of the self-adaptive system. Unfortunately, this stochastic modeling may lead to a non tractable QoS analysis. Consequently, this work also develops an efficient procedure for carrying out the QoS analysis.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Adaptability, Quality of service, Petri nets, Markov models, workload
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-68925 (URN)10.1016/j.jss.2017.05.022 (DOI)2-s2.0-85019454236 (Scopus ID)
Available from: 2017-11-23 Created: 2017-11-23 Last updated: 2018-01-13Bibliographically approved
Perez-Palacin, D., Ridene, Y. & Merseguer, J. (2017). Quality Assessment in DevOps: Automated Analysis of a Tax Fraud Detection System. In: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion: . Paper presented at 3rd International Workshop on Quality-Aware DevOps, L'Aquila, Italy, April 22 - 26, 2017 (pp. 133-138). New York, USA: ACM Press
Open this publication in new window or tab >>Quality Assessment in DevOps: Automated Analysis of a Tax Fraud Detection System
2017 (English)In: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion, New York, USA: ACM Press, 2017, p. 133-138Conference paper, Published paper (Refereed)
Abstract [en]

The paper presents an industrial application of a DevOps process for a Tax fraud detection system. In particular, we report the influence of the quality assessment during development iterations, with special focus on the fulfillment of performance requirements. We investigated how to guarantee quality requirements in a process iteration while new functionalities are added. The experience has been carried out by practitioners and academics in the context of a project for improving quality of data intensive applications.

Place, publisher, year, edition, pages
New York, USA: ACM Press, 2017
Keywords
DevOps, Model-based QoS, Tax Fraud detection, Data Intensive Applications, Unified Modeling Language
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-74484 (URN)10.1145/3053600.3053632 (DOI)978-1-4503-4899-7 (ISBN)
Conference
3rd International Workshop on Quality-Aware DevOps, L'Aquila, Italy, April 22 - 26, 2017
Projects
H2020 DICE
Funder
EU, Horizon 2020, 644869
Available from: 2018-05-22 Created: 2018-05-22 Last updated: 2018-05-23Bibliographically approved
Alexeeva, Z., Perez-Palacin, D. & Mirandola, R. (2016). Design Decision Documentation: A Literature Overview. In: Bedir Tekinerdogan, Uwe Zdun, Ali Babar (Ed.), Software Architecture: 10th European Conference, ECSA 2016, Copenhagen, Denmark, November 28 -- December 2, 2016, Proceedings. Paper presented at 10th European Conference on Software Architecture, ECSA 2016; Copenhagen; Denmark; 28 - 2 December 2016; (pp. 84-101). Springer
Open this publication in new window or tab >>Design Decision Documentation: A Literature Overview
2016 (English)In: Software Architecture: 10th European Conference, ECSA 2016, Copenhagen, Denmark, November 28 -- December 2, 2016, Proceedings / [ed] Bedir Tekinerdogan, Uwe Zdun, Ali Babar, Springer, 2016, p. 84-101Conference paper, Published paper (Refereed)
Abstract [en]

Despite the abundance of research on methodologies for the documentation of design decisions and the evidence linking documentation to the improvement in the systems evolution, their practical adoption seems to be sparse. To understand this issue, we have conducted an overview of state-of-the-art on documentation of design decisions. We pursue an identification of characteristics of the different techniques proposed in the literature, such as the final goal of the documentation, the quantity of information attached to each decision documentation, the rigour of the proposed technique or its level of automation. To unveil these, we propose six classification dimensions, relevant for the industrial application, and use them to structure and analyse the review results. This work contributes with a taxonomy of the area, a structured overview covering 96 publications and a summary of open questions, which can be addressed by future research to facilitate practical adoption.

Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9839
Keywords
design decision, documentation
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-75280 (URN)10.1007/978-3-319-48992-6_6 (DOI)978-3-319-48991-9 (ISBN)978-3-319-48992-6 (ISBN)
Conference
10th European Conference on Software Architecture, ECSA 2016; Copenhagen; Denmark; 28 - 2 December 2016;
Projects
FP7 seaclouds
Funder
EU, FP7, Seventh Framework Programme, ICT-610531
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2018-06-08Bibliographically approved
Pagliari, L., Mirandola, R., Perez-Palacin, D. & Trubiani, C. (2016). Energy-aware adaptive techniques for information diffusion in ungoverned peer-to-peer networks. In: Proceedings : 2016 12th International ACM SIGSOFT Conference on Quality of Software Architectures: QoSA 2016 : 5–8 April 2016, Venice, Italy. Paper presented at International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA 2016 (pp. 96-105). IEEE Press
Open this publication in new window or tab >>Energy-aware adaptive techniques for information diffusion in ungoverned peer-to-peer networks
2016 (English)In: Proceedings : 2016 12th International ACM SIGSOFT Conference on Quality of Software Architectures: QoSA 2016 : 5–8 April 2016, Venice, Italy, IEEE Press, 2016, p. 96-105Conference paper, Published paper (Refereed)
Abstract [en]

The problem of handling emergency situations (e.g., earthquakes, tornados, hurricanes, political rebellions, etc.) is very challenging since the fixed network infrastructures can become unusable, and it is fundamental to build a peer-to-peer network intended to spread information among people involved in the emergency. The goal of this paper is to propose an approach that enables an adaptive behavior of ungoverned communication networks with the purpose of maximizing the information diffusion and minimizing the energy consumption of the communication devices (e.g., smartphones). We introduce an energy-aware gossip algorithm to adapt the message passing methodology among the involved devices on the basis of their battery level, while guaranteeing the information diffusion within a certain geographical area and minimizing the overall energy consumption. The approach is implemented in a simulation context that allows to quantify the percentage of area coverage within a certain interval of time by adapting the process of message passing on the basis of devices' battery level. Experimental results demonstrate that our approach outperforms classic broadcast algorithms up to 85.58% in terms of energy consumption.

Place, publisher, year, edition, pages
IEEE Press, 2016
Keywords
energy, self-adaptive, peer-to-peer
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-68929 (URN)10.1109/QoSA.2016.19 (DOI)2-s2.0-84983424352 (Scopus ID)978-1-5090-2567-1 (ISBN)978-1-5090-2568-8 (ISBN)
Conference
International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA 2016
Available from: 2017-11-24 Created: 2017-11-24 Last updated: 2018-05-23Bibliographically approved
Ardagna, D., Bernardi, S., Gianniti, E., Aliabadi, S. K., Perez-Palacin, D. & Requeno, J. I. (2016). Modeling performance of Hadoop applications: A journey from queueing networks to stochastic well formed nets. In: Jesus Carretero, Javier Garcia-Blas, Ryan K.L. Ko, Peter Mueller, Koji Nakano (Ed.), Algorithms and Architectures for Parallel Processing: 16th International Conference, ICA3PP 2016, Granada, Spain, December 14-16, 2016, Proceedings. Paper presented at 16th International Conference, ICA3PP 2016, Granada, Spain, December 14-16, 2016 (pp. 599-613). Springer
Open this publication in new window or tab >>Modeling performance of Hadoop applications: A journey from queueing networks to stochastic well formed nets
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2016 (English)In: Algorithms and Architectures for Parallel Processing: 16th International Conference, ICA3PP 2016, Granada, Spain, December 14-16, 2016, Proceedings / [ed] Jesus Carretero, Javier Garcia-Blas, Ryan K.L. Ko, Peter Mueller, Koji Nakano, Springer, 2016, p. 599-613Conference paper, Published paper (Refereed)
Abstract [en]

Nowadays, many enterprises commit to the extraction of actionable knowledge from huge datasets as part of their core business activities. Applications belong to very different domains such as fraud detection or one-to-one marketing, and encompass business analytics and support to decision making in both private and public sectors. In these scenarios, a central place is held by the MapReduce framework and in particular its open source implementation, Apache Hadoop. In such environments, new challenges arise in the area of jobs performance prediction, with the needs to provide Service Level Agreement guarantees to the end-user and to avoid waste of computational resources. In this paper we provide performance analysis models to estimate MapReduce job execution times in Hadoop clusters governed by the YARN Capacity Scheduler. We propose models of increasing complexity and accuracy, ranging from queueing networks to stochastic well formed nets, able to estimate job performance under a number of scenarios of interest, including also unreliable resources. The accuracy of our models is evaluated by considering the TPC-DS industry benchmark running experiments on Amazon EC2 and the CINECA Italian supercomputing center. The results have shown that the average accuracy we can achieve is in the range 9–14%.

Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10048
Keywords
MapReduce, Performance Models
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-68933 (URN)10.1007/978-3-319-49583-5_47 (DOI)2-s2.0-85007258340 (Scopus ID)978-3-319-49582-8 (ISBN)978-3-319-49583-5 (ISBN)
Conference
16th International Conference, ICA3PP 2016, Granada, Spain, December 14-16, 2016
Available from: 2017-11-24 Created: 2017-11-24 Last updated: 2018-01-13Bibliographically approved
Perez-Palacin, D., Mirandola, R. & Scoppetta, M. (2016). Simulation of Techniques to Improve the Utilization of Cloud Elasticity in Workload-aware Adaptive Software. In: Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering Companion: . Paper presented at 2nd Workshop on Challenges in Performance Methods for Software Development (WOSP-C) 2016, Delft, March 12 - 16, 2016 (pp. 51-56). New York, USA: ACM Press
Open this publication in new window or tab >>Simulation of Techniques to Improve the Utilization of Cloud Elasticity in Workload-aware Adaptive Software
2016 (English)In: Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering Companion, New York, USA: ACM Press, 2016, p. 51-56Conference paper, Published paper (Refereed)
Abstract [en]

More and more software owners consider moving their IT infrastructure to the cloud. At present, cloud providers offer easy manners to deploy software artifacts. Therefore, the profile of cloud clients is no longer limited to computing experts. However, an appropriate configuration of the elasticity offered by cloud computing is still complicated. To help these clients, this work presents a simulator of the behavior of software services that run on the cloud and use the cloud elasticity for adapting their infrastructure in order to accommodate their workload in each moment. This work identifies techniques that are used to help mitigating at runtime the lack of predictability of workload changes. The presented simulator implements the identified techniques and allows users to execute scenarios where a combination of these techniques is enabled.

Place, publisher, year, edition, pages
New York, USA: ACM Press, 2016
Series
ICPE '16 Companion
Keywords
Performance, Simulation, Workload, Elasticity
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-75277 (URN)10.1145/2859889.2859897 (DOI)978-1-4503-4147-9 (ISBN)
Conference
2nd Workshop on Challenges in Performance Methods for Software Development (WOSP-C) 2016, Delft, March 12 - 16, 2016
Projects
FP7 Seaclouds
Funder
EU, FP7, Seventh Framework Programme, ICT-610531
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2018-06-08Bibliographically approved
Mirandola, R., Perez-Palacin, D., Scandurra, P., Brignoli, M. & Zonca, A. (2015). Business Process Adaptability Metrics for QoS-Based Service Compositions. In: Service Oriented and Cloud Computing: . Paper presented at 4th European Conference Service Oriented and Cloud Computing (ESOCC) 2015 (pp. 110-124). Springer
Open this publication in new window or tab >>Business Process Adaptability Metrics for QoS-Based Service Compositions
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2015 (English)In: Service Oriented and Cloud Computing, Springer, 2015, p. 110-124Conference paper, Published paper (Refereed)
Abstract [en]

Modern service-oriented software applications, like those envisioned in cloud computing scenarios, operate in highly dynamic and often unpredictable environments that can degrade their quality of service. Therefore, it is increasingly important to efficiently and effectively manage the adaptation of such service compositions while guaranteeing quality attributes, such as availability, performance or cost. Within this context, software metrics to quantify the adaptability of a business process in orchestrating distributed services are highly demanded in conjunction with techniques for evaluating other system quality attributes. This paper proposes a set of software metrics to quantify the adaptability of a service-oriented application when services are composed dynamically trough a business process. The paper also proposes an approach for analyzing tradeoffs between the application adaptability and a quality of service such as availability. The feasibility of the approach is illustrated through a case study carried out with a tool we have developed.

Place, publisher, year, edition, pages
Springer, 2015
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9306
Keywords
quality, adaptability, metrics
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-75102 (URN)10.1007/978-3-319-24072-5_8 (DOI)978-3-319-24071-8 (ISBN)978-3-319-24072-5 (ISBN)
Conference
4th European Conference Service Oriented and Cloud Computing (ESOCC) 2015
Projects
Italian PRIN GenData 2020, EU FP7 SeaClouds
Funder
EU, FP7, Seventh Framework Programme, ICT-610531
Available from: 2018-06-05 Created: 2018-06-05 Last updated: 2018-06-08Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2736-845X

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