3 research outputs found
A Systematic Approach to Constructing Families of Incremental Topology Control Algorithms Using Graph Transformation
In the communication systems domain, constructing and maintaining network
topologies via topology control (TC) algorithms is an important cross-cutting
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 TC 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 TC algorithms. Furthermore, even though many TC
algorithms share substantial parts (such as structural patterns or tie-breaking
strategies), few works constructively leverage these commonalities and
differences of TC 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 TC algorithms. Valid and high-quality topologies are characterized
using declarative graph constraints; TC algorithms are specified using
programmed graph transformation. We applied a well-known static analysis
technique to refine a given TC 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 TC algorithms. To show the feasibility
of our approach, we reneging six existing TC algorithms and develop e-kTC, a
novel energy-efficient variant of the TC algorithm kTC. Finally, we evaluate a
subset of the specified TC algorithms using a new tool integration of the graph
transformation tool eMoflon and the Simonstrator network simulation framework.Comment: Corresponds to the accepted manuscrip
A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation
Communication networks form the backbone of our society. Topology control
algorithms optimize the topology of such communication networks. Due to the
importance of communication networks, a topology control algorithm should
guarantee certain required consistency properties (e.g., connectivity of the
topology), while achieving desired optimization properties (e.g., a bounded
number of neighbors). Real-world topologies are dynamic (e.g., because nodes
join, leave, or move within the network), which requires topology control
algorithms to operate in an incremental way, i.e., based on the recently
introduced modifications of a topology. Visual programming and specification
languages are a proven means for specifying the structure as well as
consistency and optimization properties of topologies. In this paper, we
present a novel methodology, based on a visual graph transformation and graph
constraint language, for developing incremental topology control algorithms
that are guaranteed to fulfill a set of specified consistency and optimization
constraints. More specifically, we model the possible modifications of a
topology control algorithm and the environment using graph transformation
rules, and we describe consistency and optimization properties using graph
constraints. On this basis, we apply and extend a well-known constructive
approach to derive refined graph transformation rules that preserve these graph
constraints. We apply our methodology to re-engineer an established topology
control algorithm, kTC, and evaluate it in a network simulation study to show
the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the
referenced journal articl
kTC - Robust and Adaptive Wireless Ad-hoc Topology Control
Topology control for Wireless Sensor Networks
(WSN) is a frequently tackled challenge, for which no satisfying
general solution for realistic deployments has been found to the
current day. Aiding to minimize unnecessary transmissions, it
nevertheless represents a crucial function of WSN, in the light
of their pursuit of efficiency.
kTC is a new WSN topology control that unlike prior art
neither relies on location information, nor on complex geometric
structures, which could leave doubts about a practical feasibility.
Even though location-free approaches have been proposed to
circumvent systematic problems, they do not address issues
like robustness and adaptability satisfyingly, which may lead
to disconnection in real world deployments. kTC is a locationfree
approach that adapts topologies dynamically in face of
changing environmental influences. It is based on a local, patternbased
heuristic, and transmitting only two messages per node
to construct the topology it is highly scalable. The graphs kTC
creates are symmetric, connected, and planar; they have bounded
degree and nodes are off-separated. Simulative evaluations indicate
that kTC outperforms known topology control schemes. A
preliminary deployment on a sensor testbed corroborates the
obtained results and acts as proof of concept for kTC