23,934 research outputs found
A New Approach for Quality Management in Pervasive Computing Environments
This paper provides an extension of MDA called Context-aware Quality Model
Driven Architecture (CQ-MDA) which can be used for quality control in pervasive
computing environments. The proposed CQ-MDA approach based on
ContextualArchRQMM (Contextual ARCHitecture Quality Requirement MetaModel),
being an extension to the MDA, allows for considering quality and
resources-awareness while conducting the design process. The contributions of
this paper are a meta-model for architecture quality control of context-aware
applications and a model driven approach to separate architecture concerns from
context and quality concerns and to configure reconfigurable software
architectures of distributed systems. To demonstrate the utility of our
approach, we use a videoconference system.Comment: 10 pages, 10 Figures, Oral Presentation in ECSA 201
Re-reengineering the dream: agility as competitive adaptability
Organizational adaptation and transformative change management in technology-based organizations is explored in the context of collaborative alliances. A Re-reengineering approach is outlined in which a new Competitive Adaptability Five-Influences Analysis approach under conditions of collaborative alliance, is described as an alternative to Porter’s Five-Forces Competitive Rivalry Analysis model. Whilst continuous change in technology and the associated effects of technology shock (Dedola & Neri, 2006; Christiano, Eichenbaum & Vigfusson, 2003) are not new constructs, the reality of the industrial age was and is a continuing reduction in timeline for relevance and lifetime for a specific technology and the related skills and expertise base required for its effective implementation. This, combined with increasing pressures for innovation (Tidd & Bessant, 2013) and at times severe impacts from both local and global economic environments (Hitt, Ireland & Hoskisson, 2011) raises serious challenges for contemporary management teams seeking to strategically position a company and its technology base advantageously, relative to its suppliers, competitors and customers, as well as in predictive readiness for future technological change and opportunistic adaptation. In effect, the life-cycle of a technology has become typically one of disruptive change and rapid adjustment, followed by a plateau as a particular technology or process captures and holds its position against minor challenges, eventually to be displaced by yet another alternative (Bower & Christensen, 1995)
Semantic-based adaptive mission planning for unmanned underwater vehicles
Current underwater robotic platforms rely upon waypoint-based scripted missions which
are described by the operator a-priori. This renders systems incapable of reacting to
the unexpected. In this thesis, we claim that the ability to autonomously adapt the
decision making process is the key to facilitating the change over from human intervention
to intelligent autonomy. We identify goal-based declarative mission planning
as an attractive solution to autonomous adaptability because it combines autonomous
decision making with higher levels of human interaction.
Goal-based mission planning requires the use of abstract knowledge representation
and situation awareness to link the prior knowledge provided by the operator with
the information coming from the processed sensor data. To achieve this, we propose
a semantic-based knowledge representation framework that allows this integration of
prior and processed information among all different agents available in the platform.
In order to evaluate adaptive mission planning techniques, we also introduce a novel
metric which measures the proximity between plans. We demonstrate that this metric
is better informed than previous metrics for measuring the adaptation process.
In this thesis we implement three different approaches to goal-based mission planning
in order to investigate which approach is most appropriate under different circumstances.
The first approach, continuous mission planning, focusses on long-term
deployment. This approach is based on a continuous re-assessment of the status of
the mission environment. Using our proximity metric, we evaluated this approach
and show that there is a high degree of similarity between our approach and the humanly
driven adaptation, both in a known static environment and in a partially-known
dynamic discoverable environment. The second, service-oriented mission planning,
makes use of the semantic framework to provide autonomous mission planning for
the dynamic discovery of the services published by the different agents in the system.
This allows platform independence, easing the manual creation of mission plans, and
robustness to changes. We show that this approach produces the same plans as the
baseline which was explicitly provided with the platform configuration. The last approach,
mission plan repair, handles the scenario where small changes occur in the
mission environment and there are limited resources for planning. We develop and
deploy a mission plan repair approach within a semantic-based autonomous planning
system in a real underwater vehicle. Experiments demonstrate that the integrated system
is capable of providing mission adaptation for maintaining the operability of the
host platform in the face of unexpected events
Engineering Crowdsourced Stream Processing Systems
A crowdsourced stream processing system (CSP) is a system that incorporates
crowdsourced tasks in the processing of a data stream. This can be seen as
enabling crowdsourcing work to be applied on a sample of large-scale data at
high speed, or equivalently, enabling stream processing to employ human
intelligence. It also leads to a substantial expansion of the capabilities of
data processing systems. Engineering a CSP system requires the combination of
human and machine computation elements. From a general systems theory
perspective, this means taking into account inherited as well as emerging
properties from both these elements. In this paper, we position CSP systems
within a broader taxonomy, outline a series of design principles and evaluation
metrics, present an extensible framework for their design, and describe several
design patterns. We showcase the capabilities of CSP systems by performing a
case study that applies our proposed framework to the design and analysis of a
real system (AIDR) that classifies social media messages during time-critical
crisis events. Results show that compared to a pure stream processing system,
AIDR can achieve a higher data classification accuracy, while compared to a
pure crowdsourcing solution, the system makes better use of human workers by
requiring much less manual work effort
Quality assessment technique for ubiquitous software and middleware
The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future
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