18,290 research outputs found
Feedback and time are essential for the optimal control of computing systems
The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are used to design these algorithms are validated using open-loop metrics. By using closed-loop metrics instead, such as the gap metric developed in the control community, it should be possible to develop improved scheduling algorithms and computing systems that have not been over-engineered. Furthermore, scheduling problems are most naturally formulated as constraint satisfaction or mathematical optimization problems, but these are seldom implemented using state of the art numerical methods, nor do they explicitly take into account the fact that the scheduling problem itself takes time to solve. This paper makes the case that recent results in real-time model predictive control, where optimization problems are solved in order to control a process that evolves in time, are likely to form the basis of scheduling algorithms of the future. We therefore outline some of the research problems and opportunities that could arise by explicitly considering feedback and time when designing optimal scheduling algorithms for computing systems
CBR and MBR techniques: review for an application in the emergencies domain
The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system.
RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to:
a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions
b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location.
In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations.
This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version
Systems approaches and algorithms for discovery of combinatorial therapies
Effective therapy of complex diseases requires control of highly non-linear
complex networks that remain incompletely characterized. In particular, drug
intervention can be seen as control of signaling in cellular networks.
Identification of control parameters presents an extreme challenge due to the
combinatorial explosion of control possibilities in combination therapy and to
the incomplete knowledge of the systems biology of cells. In this review paper
we describe the main current and proposed approaches to the design of
combinatorial therapies, including the empirical methods used now by clinicians
and alternative approaches suggested recently by several authors. New
approaches for designing combinations arising from systems biology are
described. We discuss in special detail the design of algorithms that identify
optimal control parameters in cellular networks based on a quantitative
characterization of control landscapes, maximizing utilization of incomplete
knowledge of the state and structure of intracellular networks. The use of new
technology for high-throughput measurements is key to these new approaches to
combination therapy and essential for the characterization of control
landscapes and implementation of the algorithms. Combinatorial optimization in
medical therapy is also compared with the combinatorial optimization of
engineering and materials science and similarities and differences are
delineated.Comment: 25 page
Water Quality Management of the Nitra River Basin (Slovakia): Evaluation of Various Control Strategies
The Nitra is one of the most polluted rivers in Slovakia due to numerous municipal and industrial discharges, and the low level of waste water treatment. The ongoing economic transition and lack of financial resources for environmental management calls for the development of short-run least-cost policies on the basis of ambient standards (or a combination of ambient and effluent ones). A water quality control policy model was developed which incorporates dissolved oxygen simulation models, municipal wastewater treatment alternatives, an optimization model based on dynamic programming, a data base, and a graphical user interface. Least-cost policies to achieve various water quality goals were developed and compared to effluent standard based strategies (including that deriving from the application of the "best available technology"). The role of industrial emissions was demonstrated in a sensitivity fashion, while the influence of parameter uncertainty on the developed policies was analyzed in a multiobjective framework. The study shows that significant cost savings are possible in comparison to uniform, effluent standard policies. They also suggest that a long-term strategy should be realized on the basis of a sequence of properly phased least-cost policies corresponding to ambient standards to be tightened gradually
Antifragility = Elasticity + Resilience + Machine Learning: Models and Algorithms for Open System Fidelity
We introduce a model of the fidelity of open systems - fidelity being
interpreted here as the compliance between corresponding figures of interest in
two separate but communicating domains. A special case of fidelity is given by
real-timeliness and synchrony, in which the figure of interest is the physical
and the system's notion of time. Our model covers two orthogonal aspects of
fidelity, the first one focusing on a system's steady state and the second one
capturing that system's dynamic and behavioural characteristics. We discuss how
the two aspects correspond respectively to elasticity and resilience and we
highlight each aspect's qualities and limitations. Finally we sketch the
elements of a new model coupling both of the first model's aspects and
complementing them with machine learning. Finally, a conjecture is put forward
that the new model may represent a first step towards compositional criteria
for antifragile systems.Comment: Preliminary version submitted to the 1st International Workshop "From
Dependable to Resilient, from Resilient to Antifragile Ambients and Systems"
(ANTIFRAGILE 2014), https://sites.google.com/site/resilience2antifragile
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