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Cai, Simin
Publications (10 of 13) Show all publications
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2019). Data Aggregation Processes: A Survey, A Taxonomy, and Design Guidelines. Computing, 101(10), 1397-1429
Open this publication in new window or tab >>Data Aggregation Processes: A Survey, A Taxonomy, and Design Guidelines
2019 (English)In: Computing, ISSN 0010-485X, E-ISSN 1436-5057, Vol. 101, no 10, p. 1397-1429Article in journal (Refereed) Published
Abstract [en]

Data aggregation processes are essential constituents for data management in modern computer systems, such as decision support systems and Internet of Things (IoT) systems, many with timing constraints. Understanding the common and variable features of data aggregation processes, especially their implications to the timerelated properties, is key to improving the quality of the designed system and reduce design effort. In this paper, we present a survey of data aggregation processes in a variety of application domains from literature.We investigate their common and variable features, which serves as the basis of our previously proposed taxonomy called DAGGTAX. By studying the implications of the DAGGTAX features, we formulate a set of constraints to be satisfied during design, which helps to check the correctness of the specifications and reduce the design space. We also provide a set of design heuristics that could help designers to decide the appropriate mechanisms for achieving the selected features. We apply DAGGTAX on industrial case studies, showing that DAGGTAX not only strengthens the understanding, but also serves as the foundation of a design tool which facilitates the model-driven design of data aggregation processes.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-41747 (URN)10.1007/s00607-018-0679-5 (DOI)000487922400002 ()
Projects
Adequacy-based Testing of Extra-Functional Properties of Embedded Systems (VR)
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2019-10-17Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2019). Specification and Automated Verification of Atomic Concurrent Real-Time Transactions.
Open this publication in new window or tab >>Specification and Automated Verification of Atomic Concurrent Real-Time Transactions
2019 (English)Manuscript (preprint) (Other academic)
National Category
Software Engineering
Identifiers
urn:nbn:se:mdh:diva-45212 (URN)
Available from: 2019-09-13 Created: 2019-09-13 Last updated: 2019-09-20Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2019). Statistical Model Checking for Real-Time Database Management Systems: A Case Study. In: The 24th IEEE Conference on Emerging Technologies and Factory Automation ETFA2019: . Paper presented at The 24th IEEE Conference on Emerging Technologies and Factory Automation ETFA2019, 10 Sep 2019, Zaragoza, Spain.
Open this publication in new window or tab >>Statistical Model Checking for Real-Time Database Management Systems: A Case Study
2019 (English)In: The 24th IEEE Conference on Emerging Technologies and Factory Automation ETFA2019, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Many industrial control systems manage critical data using Database Management Systems (DBMS). The correctness of transactions, especially their atomicity, isolation and temporal correctness, is essential for the dependability of the entire system. Existing methods and techniques, however, either lack the ability to analyze the interplay of these properties, or do not scale well for systems with large amounts of transactions and data, and complex transaction management mechanisms. In this paper, we propose to analyze large scale real-time database systems using statistical model checking. We propose a pattern-based framework, by extending our previous work, to model the real-time DBMS as a network of stochastic timed automata, which can be analyzed by UPPAAL Statistical Model Checker. We present an industrial case study, in which we design a collision avoidance system for multiple autonomous construction vehicles, via concurrency control of a real-time DBMS. The desired properties of the designed system are analyzed using our proposed framework.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-45045 (URN)
Conference
The 24th IEEE Conference on Emerging Technologies and Factory Automation ETFA2019, 10 Sep 2019, Zaragoza, Spain
Projects
Adequacy-based Testing of Extra-Functional Properties of Embedded Systems (VR)
Available from: 2019-08-22 Created: 2019-08-22 Last updated: 2019-09-13Bibliographically approved
Cai, S. (2019). Systematic Design and Analysis of Customized Data Management for Real-Time Database Systems. (Doctoral dissertation). Västerås: Mälardalen University
Open this publication in new window or tab >>Systematic Design and Analysis of Customized Data Management for Real-Time Database Systems
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Modern real-time data-intensive systems generate large amounts of data that are processed using complex data-related computations such as data aggregation. In order to maintain logical data consistency and temporal correctness of the computations, one solution is to model the latter as transactions and manage them using a Real-Time Database Management System (RTDBMS). Ideally, depending on the particular system, the transactions are customized with the desired logical and temporal correctness properties, which should be enforced by the customized RTDBMS via appropriate transaction management mechanisms. However, developing such a data management solution with high assurance is not easy, partly due to inadequate support for systematic specification and analysis during the design. Firstly, designers do not have means to identify the characteristics of the computations, especially data aggregation, and to reason about their implications. Design flaws might not be discovered early enough, and thus they may propagate to the implementation. Secondly, meeting more properties simultaneously might not be possible, so trading-off the less critical ones for the critical one, for instance, temporal correctness, is sometimes required. Nevertheless, trade-off analysis of conflicting properties, such as transaction atomicity, isolation and temporal correctness, is mainly performed ad-hoc, which increases the risk of unpredictable behavior.

In this thesis, we address the above problems by showing how to systematically design and provide assurance of transaction-based data management with data aggregation support, customized for real-time systems. We propose a design process as our methodology for the systematic design and analysis of the trade-offs between desired properties, which is facilitated by a series of modeling and analysis techniques. Our design process consists of three major steps as follows: (i) Specifying the data-related computations, as well as the logical data consistency and temporal correctness properties, from system requirements, (ii) Selecting the appropriate transaction models to model the computations, and deciding the corresponding transaction management mechanisms that can guarantee the properties, via formal analysis, and, (iii) Generating the customized RTDBMS with the proved transaction management mechanisms, via configuration or implementation. In order to support the first step of our process, we propose a taxonomy of data aggregation processes for identifying their common and variable characteristics, based on which their inter-dependencies can be captured, and the consequent design implications can be reasoned about. Tool support is provided to check the consistency of the data aggregation design specifications. To specify transaction atomicity, isolation and temporal correctness, as well as the transaction management mechanisms, we also propose a Unified Modeling Language (UML) profile with explicit support for these elements. The second step of our process relies on the systematic analysis of trade-offs between transaction atomicity, isolation and temporal correctness. To achieve this, we propose two formal frameworks for modeling transactions with abort recovery, concurrency control, and scheduling. The first framework UPPCART utilizes timed automata as the underlying formalism, based on which the desired properties can be verified by model checking. The second framework UPPCART-SMC models the system as stochastic timed automata, which allows for probabilistic analysis of the properties for large complex RTDBMS using statistical model checking. The encoding of high-level UTRAN specifications into corresponding formal models is supported by tool automation, which we also propose in this thesis. The applicability and usefulness of our proposed techniques are validated via several industrial use cases focusing on real-time data management.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2019
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 295
National Category
Software Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-45211 (URN)978-91-7485-441-1 (ISBN)
Public defence
2019-11-04, Gamma, Mälardalens högskola, Västerås, 13:30 (English)
Opponent
Supervisors
Available from: 2019-09-19 Created: 2019-09-13 Last updated: 2019-09-26Bibliographically approved
Cai, S., Gallina, B., Nyström, D., Seceleanu, C. & Larsson, A. (2019). Tool-supported design of data aggregation processes in cloud monitoring systems. Journal of Ambient Intelligence and Humanized Computing, 10(7), 2519-2535
Open this publication in new window or tab >>Tool-supported design of data aggregation processes in cloud monitoring systems
Show others...
2019 (English)In: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145, Vol. 10, no 7, p. 2519-2535Article in journal (Refereed) Published
Abstract [en]

Efficient monitoring of a cloud system involves multiple aggregation processes and large amounts of data with various and interdependent requirements. A thorough understanding and analysis of the characteristics of data aggregation processes can help to improve the software quality and reduce development cost. In this paper, we propose a systematic approach for designing data aggregation processes in cloud monitoring systems. Our approach applies a feature-oriented taxonomy called DAGGTAX (Data AGGregation TAXonomy) to systematically specify the features of the designed system, and SAT-based analysis to check the consistency of the specifications. Following our approach, designers first specify the data aggregation processes by selecting and composing the features from DAGGTAX. These specified features, as well as design constraints, are then formalized as propositional formulas, whose consistency is checked by the Z3 SAT solver. To support our approach, we propose a design tool called SAFARE (SAt-based Feature-oriented dAta aggREgation design), which implements DAGGTAX-based specification of data aggregation processes and design constraints, and integrates the state-of-the-art solver Z3 for automated analysis. We also propose a set of general design constraints, which are integrated by default in SAFARE. The effectiveness of our approach is demonstrated via a case study provided by industry, which aims to design a cloud monitoring system for video streaming. The case study shows that DAGGTAX and SAFARE can help designers to identify reusable features, eliminate infeasible design decisions, and derive crucial system parameters.

Place, publisher, year, edition, pages
Springer Verlag, 2019
Keywords
Cloud monitoring system design, Consistency checking, Data aggregation, Feature model, Computer software selection and evaluation, Design, Quality control, Specifications, Taxonomies, Based specification, Cloud monitoring, Efficient monitoring, Feature modeling, Large amounts of data, Propositional formulas, Monitoring
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-43881 (URN)10.1007/s12652-018-0730-6 (DOI)000469922500004 ()2-s2.0-85049591829 (Scopus ID)
Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2019-09-13Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2018). Effective Test Suite Design for Detecting Concurrency Control Faults in Distributed Transaction Systems. In: 8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation ISoLA 2018: . Paper presented at 8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation ISoLA 2018, 30 Oct 2018, Limassol, Cyprus (pp. 355-374).
Open this publication in new window or tab >>Effective Test Suite Design for Detecting Concurrency Control Faults in Distributed Transaction Systems
2018 (English)In: 8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation ISoLA 2018, 2018, p. 355-374Conference paper, Published paper (Refereed)
Abstract [en]

Concurrency control faults may lead to unwanted interleavings, and breach data consistency in distributed transaction systems. However, due to the unpredictable delays between sites, detecting concurrency control faults in distributed transaction systems is difficult. In this paper, we propose a methodology, relying on model-based testing and mutation testing, for designing test cases in order to detect such faults. The generated test inputs are designated delays between distributed operations, while the outputs are the occurrence of unwanted interleavings that are consequences of the concurrency control faults. We mutate the distributed transaction specification with common concurrency control faults, and model them as UPPAAL timed automata, in which designated delays are encoded as stopwatches. Test cases are generated via reachability analysis using UPPAAL Model Checker, and are selected to form an effective test suite. Our methodology can reduce redundant test cases, and find the appropriate delays to detect concurrency control faults effectively.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-41709 (URN)10.1007/978-3-030-03424-5_24 (DOI)978-3-030-03424-5 (ISBN)
Conference
8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation ISoLA 2018, 30 Oct 2018, Limassol, Cyprus
Projects
Adequacy-based Testing of Extra-Functional Properties of Embedded Systems (VR)
Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2018-12-20Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2018). Specification and Formal Verification of Atomic Concurrent Real-Time Transactions. In: 23rd IEEE Pacific Rim International Symposium on Dependable Computing PRDC 2018: . Paper presented at The 23rd IEEE Pacific Rim International Symposium on Dependable Computing PRDC 2018, 04 Dec 2018, Taipei, Taiwan.
Open this publication in new window or tab >>Specification and Formal Verification of Atomic Concurrent Real-Time Transactions
2018 (English)In: 23rd IEEE Pacific Rim International Symposium on Dependable Computing PRDC 2018, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Although atomicity, isolation and temporal correctness are crucial to the dependability of many real-time database-centric systems, the selected assurance mechanism for one property may breach another. Trading off these properties requires to specify and analyze their dependencies, together with the selected supporting mechanisms (abort recovery, concurrency control, and scheduling), which is still insufficiently supported. In this paper, we propose a UML profile, called UTRAN, for specifying atomic concurrent real-time transactions, with explicit support for all three properties and their supporting mechanisms. We also propose a pattern-based modeling framework, called UPPCART, to formalize the transactions and the mechanisms specified in UTRAN, as UPPAAL timed automata. Various mechanisms can be modeled flexibly using our reusable patterns, after which the desired properties can be verified by the UPPAAL model checker. Our techniques facilitate systematic analysis of atomicity, isolation and temporal correctness trade-offs with guarantee, thus contributing to a dependable real-time database system.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-41710 (URN)000462280800012 ()978-1-5386-5700-3 (ISBN)
Conference
The 23rd IEEE Pacific Rim International Symposium on Dependable Computing PRDC 2018, 04 Dec 2018, Taipei, Taiwan
Projects
Adequacy-based Testing of Extra-Functional Properties of Embedded Systems (VR)
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2019-04-11Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2017). Customized Real-Time Data Management for Automotive Systems: A Case Study. In: IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY: . Paper presented at 43rd Annual Conference of the IEEE Industrial Electronics Society IECON 2017, 30 Oct 2017, Beijing, China (pp. 8397-8404).
Open this publication in new window or tab >>Customized Real-Time Data Management for Automotive Systems: A Case Study
2017 (English)In: IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2017, p. 8397-8404Conference paper, Published paper (Refereed)
Abstract [en]

Real-time DataBase Management Systems (RTDBMS) have been considered as a promising means to manage data for data-centric automotive systems. During the design of an RTDBMS, one must carefully trade off data consistency and timeliness, in order to achieve an acceptable level of both properties. Previously, we have proposed a design process called DAGGERS to facilitate a systematic customization of transaction models and decision on the run-time mechanisms. In this paper, we evaluate the applicability of DAGGERS via an industrially relevant case study that aims to design the transaction management for an on-board diagnostic system, which should guarantee both timeliness and data consistency under concurrent access. To achieve this, we apply the pattern-based approach of DAGGERS to formalize the transactions, and derive the appropriate isolation level and concurrency control algorithm guided by model checking. We show by simulation that the implementation of our designed system satisfies the desired timeliness and derived isolation, and demonstrate that DAGGERS helps to customize desired real-time transaction management prior to implementation.

Series
IEEE Industrial Electronics Society, ISSN 1553-572X
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-37061 (URN)10.1109/IECON.2017.8217475 (DOI)000427164808042 ()2-s2.0-85046624820 (Scopus ID)978-1-5386-1127-2 (ISBN)
Conference
43rd Annual Conference of the IEEE Industrial Electronics Society IECON 2017, 30 Oct 2017, Beijing, China
Projects
DAGGERS - Data aggregation for embedded real-time database systemsAdequacy-based Testing of Extra-Functional Properties of Embedded Systems (VR)
Available from: 2017-11-07 Created: 2017-11-07 Last updated: 2018-05-24Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2017). DAGGTAX: A Taxonomy of Data Aggregation Processes. Västerås
Open this publication in new window or tab >>DAGGTAX: A Taxonomy of Data Aggregation Processes
2017 (English)Report (Other academic)
Abstract [en]

Data aggregation processes are essential constituents in many data management applications. Due to their complexity, designing data aggregation processes often demands considerable efforts. A study on the features of data aggregation processes will provide a comprehensive view for the designers and ease the design process. Existing works either propose application-specific aggregation solutions, or focus on particular aspects of aggregation processes such as aggregate functions, hence they do not offer a high-level, generic description. In this paper, we propose a taxonomy of data aggregation processes called DAGGTAX, which builds on the results of an extensive survey within various application domains. Our work focuses on the features of aggregation processes and their implications, especially on the temporal data consistency and the process timeliness. We present our taxonomy as a feature diagram, which is a visual notation with formal semantics. The taxonomy can then serve as the foundation of a design tool that enables designers to build an aggregation process by selecting and composing desired features. Based on the implications of the features, we formulate three design rules that eliminate infeasible feature combinations. We also provide a set of design heuristics that could help designers to decide the appropriate mechanisms for achieving the selected features. 

Place, publisher, year, edition, pages
Västerås: , 2017
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-35366 (URN)MDH-MRTC-319/2017-1-SE (ISRN)
Projects
DAGGERS
Funder
Knowledge Foundation
Available from: 2017-05-22 Created: 2017-05-22 Last updated: 2017-05-29Bibliographically approved
Cai, S., Gallina, B., Nyström, D. & Seceleanu, C. (2017). DAGGTAX: A taxonomy of data aggregation processes. In: Lecture Notes in Computer Science, vol. 10563: . Paper presented at 7th International Conference on Model and Data Engineering (MEDI), Barcelona, SPAIN, OCT 04-06, 2017 (pp. 324-339). Springer Verlag
Open this publication in new window or tab >>DAGGTAX: A taxonomy of data aggregation processes
2017 (English)In: Lecture Notes in Computer Science, vol. 10563, Springer Verlag , 2017, p. 324-339Conference paper, Published paper (Refereed)
Abstract [en]

Data aggregation processes are essential constituents for data management in modern computer systems, such as decision support systems and Internet of Things (IoT) systems. Due to the heterogeneity and real-time constraints in such systems, designing appropriate data aggregation processes often demands considerable effort. A study on the characteristics of data aggregation processes is then desirable, as it provides a comprehensive view of such processes, potentially facilitating their design, as well as the development of tool support to aid designers. In this paper, we propose a taxonomy called DAGGTAX, which is a feature diagram that models the common and variable characteristics of data aggregation processes, with a special focus on the real-time aspect. The taxonomy can serve as the foundation of a design tool, which we also introduce, enabling designers to build an aggregation process by selecting and composing desired features, and to reason about the feasibility of the design. We apply DAGGTAX on industrial case studies, showing that DAGGTAX not only strengthens the understanding, but also facilitates the model-driven design of data aggregation processes. © 2017, Springer International Publishing AG.

Place, publisher, year, edition, pages
Springer Verlag, 2017
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10563 LNCS
Keywords
Data aggregation taxonomy, Feature model, Real-time data management, Artificial intelligence, Decision support systems, Internet of things, Real time systems, Taxonomies, Aggregation process, Data aggregation, Feature modeling, Industrial case study, Internet of Things (IOT), Modern computer systems, Real time constraints, Real time data management, Information management
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-38313 (URN)10.1007/978-3-319-66854-3_25 (DOI)000439935200025 ()2-s2.0-85030711559 (Scopus ID)9783319668536 (ISBN)
Conference
7th International Conference on Model and Data Engineering (MEDI), Barcelona, SPAIN, OCT 04-06, 2017
Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-08-17Bibliographically approved
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