Model Problem (CrowdNav) and Framework (RTX) for Self-Adaptation Based on Big Data Analytics (Artifact)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10370582" target="_blank" >RIV/00216208:11320/17:10370582 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.4230/DARTS.3.1.5" target="_blank" >http://dx.doi.org/10.4230/DARTS.3.1.5</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Model Problem (CrowdNav) and Framework (RTX) for Self-Adaptation Based on Big Data Analytics (Artifact)

Popis výsledku v původním jazyce

This artifact supports our research in self-adaptation in large-scale software-intensive distributed systems. The main problem in making such systems self-adaptive is that their adaptation needs to consider the current situation in the whole system. However, developing a complete and accurate model of such systems at design time is very challenging. We are instead investigating a novel approach where the system model consists only of the essential input and output parameters and Big Data analytics is used to guide self-adaptation based on a continuous stream of operational data. In this artifact, we provide a concrete model problem that can be used as a case study for evaluating different self-adaptation techniques pertinent to complex large-scale distributed systems. We also provide an extensible tool-based framework for endorsing an arbitrary system with self-adaptation based on analysis of operational data coming from the system. The model problem (CrowdNav) and the framework (RTX) have been packaged together in this artifact, but can also work independently.

Název v anglickém jazyce

Model Problem (CrowdNav) and Framework (RTX) for Self-Adaptation Based on Big Data Analytics (Artifact)

Popis výsledku anglicky

This artifact supports our research in self-adaptation in large-scale software-intensive distributed systems. The main problem in making such systems self-adaptive is that their adaptation needs to consider the current situation in the whole system. However, developing a complete and accurate model of such systems at design time is very challenging. We are instead investigating a novel approach where the system model consists only of the essential input and output parameters and Big Data analytics is used to guide self-adaptation based on a continuous stream of operational data. In this artifact, we provide a concrete model problem that can be used as a case study for evaluating different self-adaptation techniques pertinent to complex large-scale distributed systems. We also provide an extensible tool-based framework for endorsing an arbitrary system with self-adaptation based on analysis of operational data coming from the system. The model problem (CrowdNav) and the framework (RTX) have been packaged together in this artifact, but can also work independently.

Druh

R - Software

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Interní identifikační kód produktu

D3S-SW-2017-04

Technické parametry

software je volně stažitelný open-source

Ekonomické parametry

software je volně stažitelný open-source, jednotky stažení ročně

IČO vlastníka výsledku

00216208

Název vlastníka

Univerzita Karlova v Praze