Towards a Deadline-Based Simulation Experimentation Framework Using Micro-Services Auto-Scaling Approach
| Autor: | James DesLauriers, Simon J. E. Taylor, Gabor Terstyanszky, Tamas Kiss, Anastasia Anagnostou, Gregoire Gesmier, Nura Tijjani Abubakar, Péter Kacsuk, József Kovács |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
computational modeling
education.field_of_study Computer science media_common.quotation_subject Distributed computing Population cloud computing 020206 networking & telecommunications 02 engineering and technology runtime Modeling and simulation monitoring Order (exchange) tools 0202 electrical engineering electronic engineering information engineering containers 020201 artificial intelligence & image processing Quality (business) Micro services measurement education Scaling Physical activity behavior media_common |
| Zdroj: | 2019 Winter Simulation Conference WSC |
| Popis: | There is growing number of research efforts in developing auto-scaling algorithms and tools for cloud resources. Traditional performance metrics such as CPU, memory and bandwidth usage for scaling up or down resources are not sufficient for all applications. For example, modeling and simulation experimentation is usually expected to yield results within a specific timeframe. In order to achieve this, often the quality of experiments is compromised either by restricting the parameter space to be explored or by limiting the number of replications required to give statistical confidence. In this paper, we present early stages of a deadline-based simulation experimentation framework using a micro-services auto-scaling approach. A case study of an agent-based simulation of a population physical activity behavior is used to demonstrate our framework. |
| Databáze: | OpenAIRE |
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