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Cognitive networks

by Ryan W. Thomas, Luiz A. DaSilva, Allen B. MacKenzie - IN PROC. OF IEEE DYSPAN 2005 , 2005
"... This paper presents a definition and framework for a novel type of adaptive data network: the cognitive network. In a cognitive network, the collection of elements that make up the network observes network conditions and then, using prior knowledge gained from previous interactions with the network ..."
Abstract - Cited by 1106 (7 self) - Add to MetaCart
is needed to translate the user’s end-to-end goals into a form understandable by the cognitive process. The cognitive network also depends on a Software Adaptable Network that has both an external interface accessible to the cognitive network and network status sensors. These devices are used to provide

Review Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors

by Yueng Santiago Delahoz, Miguel Angel Labrador , 2014
"... sensors ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
sensors

The synchronous approach to reactive and real-time systems

by Albert Benveniste, Gerard Berry - Proceedings of the IEEE , 1991
"... This special issue is devoted to the synchronous approach to reactive and real-time programming. This introductory paper presents and discusses the application fields and the principles of synchronous programming. The major concern of the synchronous approach is to base synchronous programming langu ..."
Abstract - Cited by 436 (15 self) - Add to MetaCart
to call real-time a program or system that receives external interrupts or reads sensors connected to the physical world and outputs commands to it. Real-time programming is an essential industrial activ-

Cartel: a distributed mobile sensor computing system

by Bret Hull, Vladimir Bychkovsky, Yang Zhang, Kevin Chen, Michel Goraczko, Allen Miu, Eugene Shih, Hari Balakrishnan, Samuel Madden - In 4th ACM SenSys , 2006
"... CarTel is a mobile sensor computing system designed to collect, process, deliver, and visualize data from sensors located on mobile units such as automobiles. A CarTel node is a mobile embedded computer coupled to a set of sensors. Each node gathers and processes sensor readings locally before deliv ..."
Abstract - Cited by 327 (30 self) - Add to MetaCart
delivering them to a central portal, where the data is stored in a database for further analysis and visualization. In the automotive context, a variety of on-board and external sensors collect data as users drive. CarTel provides a simple query-oriented programming interface, handles large amounts

Building Efficient Wireless Sensor Networks with Low-Level Naming

by John Heidemann, Fabio Silva, Chalermek Intanagonwiwat, Ramesh Govindan, Deborah Estrin, Deepak Ganesan , 2001
"... In most distributed systems, naming of nodes for low-level communication leverages topological location (such as node addresses) and is independent of any application. In this paper, we investigate an emerging class of distributed systems where low-level communication does not rely on network topol ..."
Abstract - Cited by 257 (17 self) - Add to MetaCart
topological location. Rather, low-level communication is based on attributes that are external to the network topology and relevant to the application. When combined with dense deployment of nodes, this kind of named data enables in-network processing for data aggregation, collaborative signal processing

An Overview of Kinematic and Calibration Models Using Internal/External Sensors or Constraints to Improve the Behavior of Spatial Parallel Mechanisms

by Ana C. Majarena, Jorge Santolaria, David Samper, Juan J. Aguilar - SENSORS , 2010
"... ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
Abstract not found

Inferring High-Level Behavior from Low-Level Sensors

by Donald J. Patterson, Lin Liao, Dieter Fox, Henry Kautz , 2003
"... We present a method of learning a Bayesian model of a traveler moving through an urban environment. This technique is novel in that it simultaneously learns a unified model of the traveler's current mode of transportation as well as his most likely route, in an unsupervised manner. The model ..."
Abstract - Cited by 200 (17 self) - Add to MetaCart
. The model is implemented using particle filters and learned using Expectation-Maximization. The training data is drawn from a GPS sensor stream that was collected by the authors over a period of three months. We demonstrate that by adding more external knowledge about bus routes and bus stops, accuracy

Tinypk: securing sensor networks with public key technology

by Ronald Watro, Derrick Kong, Sue-fen Cuti, Charles Gardiner, Charles Lynn, Peter Kruus - In SASN ’04: Proceedings of the 2nd ACM Workshop on Security of Ad Hoc and Sensor Networks , 2004
"... Wireless networks of miniaturized, low-power sensor/actuator devices are poised to become widely used in commercial and military environments. The communication security problems for these networks are exacerbated by the limited power and energy of the sensor devices. In this paper, we describe the ..."
Abstract - Cited by 151 (0 self) - Add to MetaCart
. As part of our solution, we exploit the efficiency of public operations in the RSA cryptosystem and design protocols that place the computationally expensive operations on the parties external to the sensor network, when possible. Our protocols have been implemented on UC Berkeley MICA2 motes using

Linear Controller Design: Limits of Performance Via Convex Optimization

by Stephen Boyd, Craig Barratt, Stephen Norman , 1990
"... this paper, we first give a very brief overview of control engineering. The goal of control engineering is to improve, or in some cases ena- ble, the performance of a system by the addition of sensors, which measure various signals in the system and external command signals, control processors, whic ..."
Abstract - Cited by 202 (25 self) - Add to MetaCart
this paper, we first give a very brief overview of control engineering. The goal of control engineering is to improve, or in some cases ena- ble, the performance of a system by the addition of sensors, which measure various signals in the system and external command signals, control processors

Atpc: Adaptive transmission power control for wireless sensor networks

by Shan Lin, Jingbin Zhang, Gang Zhou, Lin Gu, Tian He, John A. Stankovic - In Proceedings of the Fourth International Conference on Embedded Networked Sensor Systems (SenSys , 2006
"... Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmissi ..."
Abstract - Cited by 146 (10 self) - Add to MetaCart
, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks
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