TU Darmstadt / ULB / TUbiblio

A systematic approach to constructing families of incremental topology control algorithms using graph transformation

Kluge, Roland ; Stein, Michael ; Varró, Gergely ; Schürr, Andy ; Hollick, Matthias ; Mühlhäuser, Max (2019)
A systematic approach to constructing families of incremental topology control algorithms using graph transformation.
In: Software & Systems Modeling, 18 (1)
doi: 10.1007/s10270-017-0587-8
Article

Abstract

In the communication system domain, constructing and maintaining network topologies via topology control algorithms is an important crosscutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of topology control algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of topology control algorithms. Furthermore, even though many topology control algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of topology control algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual topology control algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; topology control algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given topology control algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of topology control algorithms. To show the feasibility of our approach, we reengineering six existing topology control algorithms and develop e-kTC, a novel energy-efficient variant of the topology control algorithm kTC. Finally, we evaluate a subset of the specified topology control algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.

Item Type: Article
Erschienen: 2019
Creators: Kluge, Roland ; Stein, Michael ; Varró, Gergely ; Schürr, Andy ; Hollick, Matthias ; Mühlhäuser, Max
Type of entry: Bibliographie
Title: A systematic approach to constructing families of incremental topology control algorithms using graph transformation
Language: English
Date: February 2019
Publisher: Springer Nature
Journal or Publication Title: Software & Systems Modeling
Volume of the journal: 18
Issue Number: 1
DOI: 10.1007/s10270-017-0587-8
URL / URN: https://link.springer.com/article/10.1007%2Fs10270-017-0587-...
Abstract:

In the communication system domain, constructing and maintaining network topologies via topology control algorithms is an important crosscutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of topology control algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of topology control algorithms. Furthermore, even though many topology control algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of topology control algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual topology control algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; topology control algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given topology control algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of topology control algorithms. To show the feasibility of our approach, we reengineering six existing topology control algorithms and develop e-kTC, a novel energy-efficient variant of the topology control algorithm kTC. Finally, we evaluate a subset of the specified topology control algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.

Uncontrolled Keywords: Graph transformation, Graph constraints, Static analysis, Model-driven engineering, Wireless networks, Network simulation
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Real-Time Systems
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
20 Department of Computer Science
20 Department of Computer Science > Telecooperation
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology > Subproject A1: Modelling
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms > Subproject C1: Network-centred perspective
Date Deposited: 09 Mar 2017 08:26
Last Modified: 28 Sep 2021 09:49
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details