27,148 research outputs found
CERN Storage Systems for Large-Scale Wireless
The project aims at evaluating the use of CERN computing infrastructure for next generation sensor networks data analysis. The proposed system allows the simulation of a large-scale sensor array for traffic analysis, streaming data to CERN storage systems in an efficient way. The data are made available for offline and quasi-online analysis, enabling both long term planning and fast reaction on the environment
Middleware for Wireless Sensor Networks: An Outlook
In modern distributed computing, applications are rarely built directly atop operating system facilities, e.g., sockets. Higher-level middleware abstractions and systems are often employed to simplify the programmer’s chore or to achieve interoperability. In contrast, real-world wireless sensor network (WSN) applications are almost always developed by relying directly on the operating system.
Why is this the case? Does it make sense to include a middleware layer in the design of WSNs? And, if so, is it the same kind of software system as in traditional distributed computing? What are the fundamental concepts, reasonable assumptions, and key criteria guiding its design? What are the main open research challenges, and the potential pitfalls? Most importantly, is it worth pursuing research in this field?
This paper provides a (biased) answer to these and other research questions, preceded by a brief account on the state of the art in the field
Project based learning on industrial informatics: applying IoT to urban garden
Copyright (c) 2018 IEEEThe fast evolution of technologies forces teachers to
trade content off for self-learning. PBL is one of the best ways
to promote self-learning and simultaneously boost motivation. In
this paper, we present our experience introducing project-based
learning in the last year subject. New Internet of Things (IoT) topic
allows us to carry out complete projects, integrating different
technologies and tools. Moreover, the selection of open-source and
standard free technologies makes easy and cheap the access to
hardware and software platforms used. We carefully have picked
communication, data management, and programming tools that
we think would be attractive to our students. They can start
making fast prototyping with little initial skills and, at the same
time, these are serious and popular tools widely used in the
industry. In this paper, we report on the design of a project-based
learning for our course and the impact this has on the
student satisfaction and motivation. Surveys taught us that tuning
the courses towards developing real projects on the field, has a
large impact on acceptance, learning objectives achievements and
motivation towards the course content.”I Plan Propio Integral de Docencia de la Universidad de Málaga” y Proyecto de InnovaciĂłn Educativa PIE17/085, de la Universidad de Málaga. Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
Robust Component-based Network Localization with Noisy Range Measurements
Accurate and robust localization is crucial for wireless ad-hoc and sensor
networks. Among the localization techniques, component-based methods advance
themselves for conquering network sparseness and anchor sparseness. But
component-based methods are sensitive to ranging noises, which may cause a huge
accumulated error either in component realization or merging process. This
paper presents three results for robust component-based localization under
ranging noises. (1) For a rigid graph component, a novel method is proposed to
evaluate the graph's possible number of flip ambiguities under noises. In
particular, graph's \emph{MInimal sepaRators that are neaRly cOllineaR
(MIRROR)} is presented as the cause of flip ambiguity, and the number of
MIRRORs indicates the possible number of flip ambiguities under noise. (2) Then
the sensitivity of a graph's local deforming regarding ranging noises is
investigated by perturbation analysis. A novel Ranging Sensitivity Matrix (RSM)
is proposed to estimate the node location perturbations due to ranging noises.
(3) By evaluating component robustness via the flipping and the local deforming
risks, a Robust Component Generation and Realization (RCGR) algorithm is
developed, which generates components based on the robustness metrics. RCGR was
evaluated by simulations, which showed much better noise resistance and
locating accuracy improvements than state-of-the-art of component-based
localization algorithms.Comment: 9 pages, 15 figures, ICCCN 2018, Hangzhou, Chin
A Low-Overhead Script Language for Tiny Networked Embedded Systems
With sensor networks starting to get mainstream acceptance, programmability is of increasing importance.
Customers and field engineers will need to reprogram existing deployments and software developers
will need to test and debug software in network testbeds. Script languages, which are a popular
mechanism for reprogramming in general-purpose computing, have not been considered for wireless sensor
networks because of the perceived overhead of interpreting a script language on tiny sensor nodes.
In this paper we show that a structured script language is both feasible and efficient for programming
tiny sensor nodes. We present a structured script language, SCript, and develop an interpreter for the
language. To reduce program distribution energy the SCript interpreter stores a tokenized representation
of the scripts which is distributed through the wireless network. The ROM and RAM footprint of the
interpreter is similar to that of existing virtual machines for sensor networks. We show that the interpretation
overhead of our language is on par with that of existing virtual machines. Thus script languages,
previously considered as too expensive for tiny sensor nodes, are a viable alternative to virtual machines
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