14,715 research outputs found
Blackboard Rules for Coordinating Context-aware Applications in Mobile Ad Hoc Networks
Thanks to improvements in wireless communication technologies and increasing
computing power in hand-held devices, mobile ad hoc networks are becoming an
ever-more present reality. Coordination languages are expected to become
important means in supporting this type of interaction. To this extent we argue
the interest of the Bach coordination language as a middleware that can handle
and react to context changes as well as cope with unpredictable physical
interruptions that occur in opportunistic network connections. More concretely,
our proposal is based on blackboard rules that model declaratively the actions
to be taken once the blackboard content reaches a predefined state, but also
that manage the engagement and disengagement of hosts and transient sharing of
blackboards. The idea of reactiveness has already been introduced in previous
work, but as will be appreciated by the reader, this article presents a new
perspective, more focused on a declarative setting.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432
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Multimodal and ubiquitous computing systems: supporting independent-living older users
We document the rationale and design of a multimodal interface to a pervasive/ubiquitous computing system that supports independent living by older people in their own homes. The Millennium Home system involves fitting a resident’s home with sensors – these sensors can be used to trigger sequences of interaction with the resident to warn them about dangerous events, or to check if they need external help. We draw lessons from the design process and conclude the paper with implications for the design of multimodal interfaces to ubiquitous systems developed for the elderly and in healthcare, as well as for more general ubiquitous computing applications
Teleo-Reactive policies for managing human-centric pervasive services.
Event-Condition-Action (ECA) policies are often used to manage various aspects of adaptation and execution of pervasive systems. Such policies are well suited for services where: 1) given actions are reliably executed when they are requested, 2) there is no priority ordering amongst multiple available actions, and 3) execution is instantaneous with respect to the validity of conditions under which they were initiated. However, for a pervasive service that integrates human agents and human activities, these assumptions do not generally hold. Humans may misbehave by postponing the execution of certain actions or ignoring them all together. Performing an action may take a long time so that the action is no longer needed or more important actions may need to be executed. Managing such behaviours through ECA policies is complex and difficult to implement. This paper introduces a new management policy type, called a Teleo-Reactive policy, whose semantics are based on continuous monitoring of the environment and prioritising available actions. The semantics result in more flexible and concise formulation of management policies for human-centric pervasive services. We demonstrate how these policies can be applied in a real-world use case scenario set in a nursing home and describe the underlying implementation based on the Androids Java platform. © 2010 IEEE
A meta-model for dataflow-based rules in smart environments: Evaluating user comprehension and performance
NOTICE: this is the author’s version of a work that was accepted for publication in Science of Computer Programming Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Science of Computer Programming, [Volume 78, Issue 10, 1 October 2013, Pages 1930–1950] DOI 10.1016/j.scico.2012.06.010A considerable part of the behavior in smart environments relies on event-driven and rule specification. Rules are the mechanism most often used to enable user customization of the environment. However, the expressiveness of the rules available to users in editing and other tools is usually either limited or the available rule editing interfaces are not designed for end-users with low skills in programming. This means we have to look for interaction techniques and new ways to define user customization rules. This paper describes a generic and flexible meta-model to support expressive rules enhanced with data flow expressions that will graphically support the definition of rules without writing code. An empirical study was conducted on the ease of understanding of the visual data flow expressions, which are the key elements in our rule proposal. The visual dataflow language was compared to its corresponding textual version in terms of comprehension and ease of learning by teenagers in exercises involving calculations, modifications, writing and detecting equivalences in expressions in both languages. Although the subjects had some previous experience in editing mathematical expressions on spreadsheets, the study found their performance with visual dataflows to be significantly better in calculation and modification exercises. This makes our dataflow approach a promising mechanism for expressing user-customized reactive behavior in Ambient Intelligence (AmI) environments. The performance of the rule matching processor was validated by means of two stress tests to ensure that the meta-model approach adopted would be able to scale up with the number of types and instances in the space. © 2012 Elsevier B.V. All rights reserved.This work received financial support from the Spanish Ministry of Education under the National Strategic Program of Research and Project TSI2010-20488. Our thanks also go to the high school "Collegi Parroquial D. Jose Lluch - Alboraya", especially to the teachers and students that participated in the empirical study reported in this paper. A. Catala is supported by an FPU fellowship from the Ministry of Education of Spain with reference AP2006-00181.Catalá Bolós, A.; Pons, P.; Jaén Martínez, FJ.; Mocholi Agües, JA.; Navarro Martínez, EM. (2013). A meta-model for dataflow-based rules in smart environments: Evaluating user comprehension and performance. Science of Computer Programming. 78(10):1930-1950. doi:10.1016/j.scico.2012.06.010S19301950781
Model reproduces individual, group and collective dynamics of human contact networks
Empirical data on the dynamics of human face-to-face interactions across a variety of social venues have recently revealed a number of context-independent structural and temporal properties of human contact networks. This universality suggests that some basic mechanisms may be responsible for the unfolding of human interactions in the physical space. Here we discuss a simple model that reproduces the empirical distributions for the individual, group and collective dynamics of face-to-face contact networks. The model describes agents that move randomly in a two-dimensional space and tend to stop when meeting ‘attractive’ peers, and reproduces accurately the empirical distributions.Postprint (author's final draft
Modelling Energy Consumption based on Resource Utilization
Power management is an expensive and important issue for large computational
infrastructures such as datacenters, large clusters, and computational grids.
However, measuring energy consumption of scalable systems may be impractical
due to both cost and complexity for deploying power metering devices on a large
number of machines. In this paper, we propose the use of information about
resource utilization (e.g. processor, memory, disk operations, and network
traffic) as proxies for estimating power consumption. We employ machine
learning techniques to estimate power consumption using such information which
are provided by common operating systems. Experiments with linear regression,
regression tree, and multilayer perceptron on data from different hardware
resulted into a model with 99.94\% of accuracy and 6.32 watts of error in the
best case.Comment: Submitted to Journal of Supercomputing on 14th June, 201
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