Assessment of performance of a distributed information system based on time profile
DOI:
https://doi.org/10.15587/1729-4061.2017.116019Keywords:
distributed information system, time profile, serial actor, throughput capacity, system response timeAbstract
The problem of determining performance parameters for distributed information systems, which are formed by heterogeneous hardware, is examined. The information system, designed to perform distributed computing, based on the interaction between elements, is presented in the form of a combination of operation processes of software objects (agents) in interaction with operators.
To provide a possibility of algorithmic and quantitative analysis of the system’s operation process, the authors used time diagrams, which can be obtained based of time profiles of serial and distributed actors. Construction of the time profile of an actor is provided by knowledge of the sequence of performed actions and the average time to perform each action. Based on the knowledge of a typical time profile, estimations of different kinds of performance were obtained and the ratio, linking the main forms of performance to a variety of quantitative characteristics of the system, was derived.
As the key indicator of performance assessment, it is proposed to apply throughput, which for a serial actor is the ratio of loading of an actor and total time of actions per task. It was shown that within a single distributed actor, total throughput remains constant regardless of redistribution of the number of tasks between serial actors.
As another performance indicator, it is proposed to apply response time of the system as the average time to fulfil a task by an actor. Relationship between response time and throughput of the system was established analytically. It was determined by modeling that at an increase in throughput, response time of the system decreases, reaching 0 at a certain ratio of throughput and the number of fulfilled tasks.
The introduction of these ratios, in addition to the key indicators, also makes it possible to determine derivative parameters of the system, such as minimal computation time, average time of waiting for requests and amount of memory, required to fulfil tasks. In this case, it was determined that the minimum computation time is a magnitude, dependent on the capacity of an actor and the number of actions performed, as well as the ratio of computation time and exchange time. The average time of waiting for a request is the difference between total operation time and direct time for fulfilling the task by actors. The amount of required memory is determined based on knowledge of amount of memory, involved in performance of certain processes and atomic operations.
Presented ratios make it possible to evaluate quantitatively parameters of distributed information systems and to synthesize systems with assigned parameters of throughput and response timeReferences
- Report on ERP Systems and Enterprise Software (2017). Panorama Consulting Solutions. Available at: http://go.panorama-consulting.com/rs/603-UJX-107/images/2017-ERP-Report.pdf
- Hoshaba, O. M. (2016). Research of Calibration Method as an Important Part of the Theory of Computer Systems Performance. III International Scientific Conference “Information Technologies in Education, Science and Technics”. Cherkasy, 52–54.
- Sukhoroslov, O. V., Nazarenko, A. M. (2017). Comparative study of scheduling algorithms for distributed computing environments. Program Systems: Theory and Applications, 8 (1), 63–81. doi: 10.25209/2079-3316-2017-8-1-63-81
- Afanasiev, A. P., Posypkin, M. A., Khritankov, A. S. (2009). The Analytical Model of Distributed Systems Performances Assessment. Program Products and Systems, 4, 60–64.
- Khritankov, A. S. (2010). Performance Evaluation Model for Distributed Systems and Tasks with Variable Size. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2 (66), 66–71.
- Posypkin, M. A. (2010). Methods and Distributed Software Infrastructure for the Numeric Solution of the Task of Molecular Clusters Search with Minimal Energy. Vestnik Nizhegorodskogo universiteta im. N. I. Lobachevskogo, 1, 210–219.
- Kovalenko, T. N. (2012). Analysis of Productivity of Distributed Systems with Service Oriented Architecture under Conditions of Limited Link and Buffer Resources of Telecommunication Network. Electronic Scientific Specialized Edition Journal “Telecommunications Problems”, 1 (6), 3–11.
- Rauber, T., Runger, G. (2013). Parallel Programming for Multicore and Cluster Systems. Springer, 516. doi: 10.1007/978-3-642-37801-0
- Kahanwal, B. (2014). Towards High Performance Computing (HPC) Through Parallel Programming Paradigms and Their Principles. International Journal of Programming Languages and Applications, 4 (1), 45–55. doi: 10.5121/ijpla.2014.4104
- Hajibaba, M., Gorgin, S. (2014). A Review on Modern Distributed Computing Paradigms: Cloud Computing, Jungle Computing and Fog Computing. Journal of Computing and Information Technology, 22 (2), 69. doi: 10.2498/cit.1002381
- Savchenko, V. A. (2011). The Productivity of Multiagent Decision Support System on the Basement of Time Profile. Modeling and Information Technologies, 59, 67–72.
- Smelianskii, R. L. (2013). The Model of Distributed Computing System with Time. Programming, 5, 22–34.
- Smelianskii, R. L. (2011). Automated Control Systems Networks. Computer Networks, 2.
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Copyright (c) 2017 Vitalii Savchenko, Oleksander Matsko, Viktoria Vorobiova, Yaroslav Kizyak, Viktor Duhanets
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