4,542 research outputs found
Prototyping Component-Based Self-Adaptive Systems with Maude
Software adaptation is becoming increasingly important as more and
more applications need to dynamically adapt their structure and behavior to
cope with changing contexts, available resources and user requirements. Maude
is a high-performance reflective language and system, supporting both equational
and rewriting logic specification and programming for a wide range of
applications. In this paper we describe our experience in using Maude for prototyping
component-based self-adaptive systems so that they can be formally
simulated and analyzed. In order to illustrate the benefits of using Maude in this
context, a case study in the robotics domain is presented.Ministerio de Ciencia e Innovación TIN2009-08572Fundación Séneca-CARM 15374/PI/1
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
Special Session on Industry 4.0
No abstract available
Software Design Criteria for Maintainability
One of the current issues in the software engineering community is related to
problems of software maintenance. It is a common belief that these problems
are caused by bad software design and poor maintenance practices. The first of
these is the concern of this paper. We argue that the existing software design
methodologies are not properly developed based on criteria for easy software
maintenance at later stages. Therefore, with a set of software design criteria for
maintainability, software is believed to be more maintainable. In this paper we
shall identify those criteria followed by assessment of several software design
methodologies
Contracts and Behavioral Patterns for SoS: The EU IP DANSE approach
This paper presents some of the results of the first year of DANSE, one of
the first EU IP projects dedicated to SoS. Concretely, we offer a tool chain
that allows to specify SoS and SoS requirements at high level, and analyse them
using powerful toolsets coming from the formal verification area. At the high
level, we use UPDM, the system model provided by the british army as well as a
new type of contract based on behavioral patterns. At low level, we rely on a
powerful simulation toolset combined with recent advances from the area of
statistical model checking. The approach has been applied to a case study
developed at EADS Innovation Works.Comment: In Proceedings AiSoS 2013, arXiv:1311.319
STV-based Video Feature Processing for Action Recognition
In comparison to still image-based processes, video features can provide rich and intuitive information about dynamic events occurred over a period of time, such as human actions, crowd behaviours, and other subject pattern changes. Although substantial progresses have been made in the last decade on image processing and seen its successful applications in face matching and object recognition, video-based event detection still remains one of the most difficult challenges in computer vision research due to its complex continuous or discrete input signals, arbitrary dynamic feature definitions, and the often ambiguous analytical methods. In this paper, a Spatio-Temporal Volume (STV) and region intersection (RI) based 3D shape-matching method has been proposed to facilitate the definition and recognition of human actions recorded in videos. The distinctive characteristics and the performance gain of the devised approach stemmed from a coefficient factor-boosted 3D region intersection and matching mechanism developed in this research. This paper also reported the investigation into techniques for efficient STV data filtering to reduce the amount of voxels (volumetric-pixels) that need to be processed in each operational cycle in the implemented system. The encouraging features and improvements on the operational performance registered in the experiments have been discussed at the end
A Conceptual Framework for Adapation
This paper presents a white-box conceptual framework for adaptation that promotes a neat separation of the adaptation logic from the application logic through a clear identification of control data and their role in the adaptation logic. The framework provides an original perspective from which we survey archetypal approaches to (self-)adaptation ranging from programming languages and paradigms, to computational models, to engineering solutions
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
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