2,193 research outputs found
Hardware Architectures for Low-power In-Situ Monitoring of Wireless Embedded Systems
As wireless embedded systems transition from lab-scale research prototypes to large-scale commercial deployments, providing reliable and dependable system operation becomes absolutely crucial to ensure successful adoption. However, the untethered nature of wireless embedded systems severely limits the ability to access, debug, and control device operation after deployment—post-deployment or in-situ visibility. It is intuitive that the more information we have about a system’s operation after deployment, the better/faster we can respond upon the detection of anomalous behavior. Therefore, post-deployment visibility is a foundation upon which other runtime reliability techniques can be built. However, visibility into system operation diminishes significantly once the devices are remotely deployed, and we refer to this problem as a lack of post-deployment visibility
Survey and Benchmark of Block Ciphers for Wireless Sensor Networks
Cryptographic algorithms play an important role in the security architecture of wireless sensor networks (WSNs). Choosing the most storage- and energy-efficient block cipher is essential, due to the facts that these networks are meant to operate without human intervention for a long period of time with little energy supply, and that available storage is scarce on these sensor nodes. However, to our knowledge, no systematic work has been done in this area so far.We construct an evaluation framework in which we first identify the candidates of block ciphers suitable for WSNs, based on existing literature and authoritative recommendations. For evaluating and assessing these candidates, we not only consider the security properties but also the storage- and energy-efficiency of the candidates. Finally, based on the evaluation results, we select the most suitable ciphers for WSNs, namely Skipjack, MISTY1, and Rijndael, depending on the combination of available memory and required security (energy efficiency being implicit). In terms of operation mode, we recommend Output Feedback Mode for pairwise links but Cipher Block Chaining for group communications
Pervasive Games in a Mote-Enabled Virtual World Using Tuple Space Middleware
Pervasive games are a new and exciting field where the user experience benefits from the blending of real and virtual elements. Players are no longer confined to computer screens. Rather, interactions with devices embedded within the real world and physical movements become an integral part of the gaming experience. Several prototypes of pervasive games have been proposed by both industry and academia. However, in such games the issues arising from the integration of players and real world, the management of the context surrounding the players, and the need for communication and distributed coordination are often addressed in an ad-hoc fashion. Therefore, the underlying software fabric is often not reusable, ultimately slowing down the diffusion of pervasive games.
In this paper we describe the design and implementation of a pervasive game on top of TinyLIME, a middleware system supporting data sharing among mobile and embedded devices. By illustrating the design of a pervasive game we developed, we argue concretely that the programming abstractions supported by TinyLIME greatly simplify the data and context management characteristics of pervasive games, and provide an effective and reusable building block for their development.
TinyLIME was originally designed to support applications where mobile users collect data from sensors scattered in the physical environment. We build upon this capability to put forth a second contribution, namely, the use of wireless sensor devices (or motes) as a computing platform for pervasive games. Besides reporting physical data for the sake of the game, we use motes to store information relevant to the game plot, e.g., virtual objects. Motes are typically very small in size, and therefore can be hidden in the environment, enhancing the sense of immersion in a virtual world. To the best of our knowledge, this original use of wireless sensor devices is novel in the scientific and gaming literature. Furthermore, it is naturally supported by TinyLIME, yielding a unified programming abstraction that spans the heterogeneous gaming platform we propose
CITRIC: A low-bandwidth wireless camera network platform
In this paper, we propose and demonstrate a novel wireless camera network system, called CITRIC. The core component of this system is a new hardware platform that integrates a camera, a frequency-scalable (up to 624 MHz) CPU, 16 MB FLASH, and 64 MB RAM onto a single device. The device then connects with a standard sensor network mote to form a camera mote. The design enables in-network processing of images to reduce communication requirements, which has traditionally been high in existing camera networks with centralized processing. We also propose a back-end client/server architecture to provide a user interface to the system and support further centralized processing for higher-level applications. Our camera mote enables a wider variety of distributed pattern recognition applications than traditional platforms because it provides more computing power and tighter integration of physical components while still consuming relatively little power. Furthermore, the mote easily integrates with existing low-bandwidth sensor networks because it can communicate over the IEEE 802.15.4 protocol with other sensor network platforms. We demonstrate our system on three applications: image compression, target tracking, and camera localization
Deploying RIOT operating system on a reconfigurable Internet of Things end-device
Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e ComputadoresThe Internet of Everything (IoE) is enabling the connection of an infinity of
physical objects to the Internet, and has the potential to connect every single
existing object in the world. This empowers a market with endless opportunities
where the big players are forecasting, by 2020, more than 50 billion connected
devices, representing an 8 trillion USD market.
The IoE is a broad concept that comprises several technological areas and will
certainly, include more in the future. Some of those already existing fields are the
Internet of Energy related with the connectivity of electrical power grids, Internet
of Medical Things (IoMT), for instance, enables patient monitoring, Internet of
Industrial Things (IoIT), which is dedicated to industrial plants, and the Internet
of Things (IoT) that focus on the connection of everyday objects (e.g. home
appliances, wearables, transports, buildings, etc.) to the Internet.
The diversity of scenarios where IoT can be deployed, and consequently the
different constraints associated to each device, leads to a heterogeneous network
composed by several communication technologies and protocols co-existing on the
same physical space. Therefore, the key requirements of an IoT network are
the connectivity and the interoperability between devices. Such requirement is
achieved by the adoption of standard protocols and a well-defined lightweight network
stack. Due to the adoption of a standard network stack, the data processed
and transmitted between devices tends to increase. Because most of the devices
connected are resource constrained, i.e., low memory, low processing capabilities,
available energy, the communication can severally decrease the device’s performance.
Hereupon, to tackle such issues without sacrificing other important requirements,
this dissertation aims to deploy an operating system (OS) for IoT, the
RIOT-OS, while providing a study on how network-related tasks can benefit from
hardware accelerators (deployed on reconfigurable technology), specially designed
to process and filter packets received by an IoT device.O conceito Internet of Everything (IoE) permite a conexão de uma infinidade
de objetos à Internet e tem o potencial de conectar todos os objetos existentes no
mundo. Favorecendo assim o aparecimento de novos mercados e infinitas possibilidades,
em que os grandes intervenientes destes mercados preveem até 2020 a
conexão de mais de 50 mil milhões de dispositivos, representando um mercado de
8 mil milhões de dólares.
IoE é um amplo conceito que inclui várias áreas tecnológicas e irá certamente
incluir mais no futuro. Algumas das áreas já existentes são: a Internet of Energy
relacionada com a conexão de redes de transporte e distribuição de energia à
Internet; Internet of Medical Things (IoMT), que possibilita a monotorização de
pacientes; Internet of Industrial Things (IoIT), dedicada a instalações industriais
e a Internet of Things (IoT), que foca na conexão de objetos do dia-a-dia (e.g.
eletrodomésticos, wearables, transportes, edifícios, etc.) à Internet.
A diversidade de cenários à qual IoT pode ser aplicado, e consequentemente,
as diferentes restrições aplicadas a cada dispositivo, levam à criação de uma rede
heterogénea composto por diversas tecnologias de comunicação e protocolos a coexistir
no mesmo espaço físico. Desta forma, os requisitos chave aplicados às redes
IoT são a conectividade e interoperabilidade entre dispositivos. Estes requisitos
são atingidos com a adoção de protocolos standard e pilhas de comunicação bem
definidas. Com a adoção de pilhas de comunicação standard, a informação processada
e transmitida entre dispostos tende a aumentar. Visto que a maioria dos
dispositivos conectados possuem escaços recursos, i.e., memória reduzida, baixa
capacidade de processamento, pouca energia disponível, o aumento da capacidade
de comunicação pode degradar o desempenho destes dispositivos.
Posto isto, para lidar com estes problemas e sem sacrificar outros requisitos importantes,
esta dissertação pretende fazer o porting de um sistema operativo IoT,
o RIOT, para uma solução reconfigurável, o CUTE mote. O principal objetivo
consiste na realização de um estudo sobre os benefícios que as tarefas relacionadas
com as camadas de rede podem ter ao serem executadas em hardware via aceleradores
dedicados. Estes aceleradores são especialmente projetados para processar
e filtrar pacotes de dados provenientes de uma interface radio em redes IoT periféricas
Visual on-line learning in distributed camera networks
Automatic detection of persons is an important application in visual surveillance. In general, state-of-the-art systems have two main disadvantages: First, usually a general detector has to be learned that is applicable to a wide range of scenes. Thus, the training is time-consuming and requires a huge amount of labeled data. Second, the data is usually processed centralized, which leads to a huge network traffic. Thus, the goal of this paper is to overcome these problems, which is realized by a person detection system, that is based on distributed smart cameras (DSCs). Assuming that we have a large number of cameras with partly overlapping views, the main idea is to reduce the model complexity of the detector by training a specific detector for each camera. These detectors are initialized by a pre-trained classifier, that is then adapted for a specific camera by co-training. In particular, for co-training we apply an on-line learning method (i.e., boosting for feature selection), where the information exchange is realized via mapping the overlapping views onto each other by using a homography. Thus, we have a compact scenedependent representation, which allows to train and to evaluate the classifiers on an embedded device. Moreover, since the information transfer is reduced to exchanging positions the required network-traffic is minimal. The power of the approach is demonstrated in various experiments on different publicly available data sets. In fact, we show that on-line learning and applying DSCs can benefit from each other. Index Terms — visual on-line learning, object detection, multi-camera networks 1
Design Experiences on Single and Multi Radio Systems in Wireless Embedded Platforms
The progress of radio technology has made several flavors of radio available on the market.Wireless sensor network platform designers have used these radios to build a variety of platforms. Withnew applications and different types of radios on wireless sensing nodes, it is often hard to interconnectdifferent types of networks. Hence, often additional radios have to be integrated onto existingplatforms or new platforms have to be built. Additionally, the energy consumption of these nodes have to be optimized to meetlifetime requirements of years without recharging.In this thesis, we address two issues of single and multi radio platform designfor wireless sensor network applications - engineering issues and energy optimization.We present a set of guiding principles from our design experiences while building 3 real life applications,namely asset tracking, burglar tracking and finally in-situ psychophysiological stress monitoring of human subjects in behavioral studies.In the asset tracking application, we present our design of a tag node that can be hidden inside valuable personal assets such asprinters or sofas in a home. If these items are stolen, a city wide anchor node infrastructure networkwould track them throughout the city. We also present our design for the anchor node.In the burglar tracking application, we present the design of tag nodes and the issueswe faced while integrating it with a GSM radio. Finally, we discuss our experiencesin designing a bridge node, that connects body worn physiological sensorsto a Bluetooth enabled mobile smartphone. We present the software framework that acts as middleware toconnect to the bridge, parse the sensor data, and send it to higher layers of the softwareframework.We describe 2 energy optimization schemes that are used in the Asset Tracking and the Burglar Tracking applications, that enhance the lifetime of the individual applications manifold.In the asset tracking application,we design a grouping scheme that helps increase reliability of detection of the tag nodes at theanchor nodes while reducing the energy consumption of the group of tag nodes travelling together.We achieve an increase of 5 times improvement in lifetime of the entire group. In the Burglar Tracking application, weuse sensing to determine when to turn the GSM radio on and transmit data by differentiatingturns and lane changes. This helps us reduce the number of times the GSM radio is woken up, thereby increasing thelifetime of the tag node while it is being tracked. This adds 8 minutes of trackablelifetime to the burglar tracking tag node. We conclude this thesis by observing the futuretrends of platform design and radio evolution
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