41,143 research outputs found
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
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
Local Cyber-Physical Attack for Masking Line Outage and Topology Attack in Smart Grid
Malicious attacks in the power system can eventually result in a large-scale
cascade failure if not attended on time. These attacks, which are traditionally
classified into \emph{physical} and \emph{cyber attacks}, can be avoided by
using the latest and advanced detection mechanisms. However, a new threat
called \emph{cyber-physical attacks} which jointly target both the physical and
cyber layers of the system to interfere the operations of the power grid is
more malicious as compared with the traditional attacks. In this paper, we
propose a new cyber-physical attack strategy where the transmission line is
first physically disconnected, and then the line-outage event is masked, such
that the control center is misled into detecting as an obvious line outage at a
different position in the local area of the power system. Therefore, the
topology information in the control center is interfered by our attack. We also
propose a novel procedure for selecting vulnerable lines, and analyze the
observability of our proposed framework. Our proposed method can effectively
and continuously deceive the control center into detecting fake line-outage
positions, and thereby increase the chance of cascade failure because the
attention is given to the fake outage. The simulation results validate the
efficiency of our proposed attack strategy.Comment: accepted by IEEE Transactions on Smart Grid. arXiv admin note: text
overlap with arXiv:1708.0320
Recommended from our members
Evolutionary optimization within an intelligent hybrid system for design integration
An intelligent hybrid approach has been developed to integrate various stages in total design, including formulation of product design specifications, conceptual design, detail design, and manufacture. The integration is achieved by blending multiple artificial intelligence (AI) techniques and CAD/CAE/CAM into a single environment. It has been applied into power transmission system design. In addition to knowledge-based systems and artificial neural networks, another AI technique, genetic algorithms (GAs), are involved in the approach. The GA is used to conduct optimization tasks: (1) searching the best combination of design parameters to obtain optimum design of gears, and (2) optimization of the architecture of the artificial neural networks used in the hybrid system. In this paper, after a brief overview of the intelligent hybrid system, the GA applications are described in detail
- …