research activities in 2007 - CSEM

More documents

Recommendations

Info

Optimum Operating Regimes for Wireless Sensor Networks A. El-Hoiydi, J. Rousselot, J.-D. Decotignie Wireless sensor networks are used in applications that have constraints in terms of metrics such as timeliness, lifetime and reliability. The WSN designer needs to find a solution that meets the required objective metrics. Most of the time, applications have sets of objective metric values, depending on the operating regime. This can be exploited to find a better solution to the needs by trading one objective value against another. This study explores the potential of tuning in a combined manner the parameters of protocol stacks to achieve the best performance trade-off. Although low power operation is often quoted as the main quality of Wireless Sensor Networks (WSNs), such networks may also need to satisfy other goals, depending on the operating regime of the applications. For instance, a fire detection application in a Mediterranean country may privilege battery life in the winter when fires are unlikely. However, when some humidity and temperature conditions are met, the same application would place the priority on reactivity or timeliness with respect to the propagation of the information. This study shows the potential of tuning key protocol parameters in order to achieve the best possible compromise between operationally dependent and potentially divergent performance metrics. The objective is to optimize the operations of the WSN at run time. In WSNs, three key performance metrics have been identified [1] : timeliness which refers to the time to transport some information from its source to its destination, reliability which is the probability that a packet emanating from a source is eventually received at its destination, and lifetime which is the duration during which the network will operate continuously Energy (J) Latency (ms) 2.5 2 1.5 x 104 3 1 0.5 -10 -5 0 Tx Power 5 10 12 10 8 6 4 2 0 -10 -5 0 Tx Power 5 10 Figure 1: Total required energy and average latency with a varying transmit power (CC2420 transceiver) Emission power is one of the parameters that impact several communication layers and may be tuned to look for the best tradeoff between some of the metrics. It is controlled by the physical layer, influences the link layer for instance by changing the collision probability and impacts routing because the number of direct neighbors and paths will change with the power. Intuitively, the higher the power the higher the consumption and the lower the latency (end-to-end delay). The main question is whether there is a value of the transmitted power that leads to a better trade-off between consumption and latency. Power consumption and latency have been evaluated by simulation (OMNET++) using a IEEE 802.15.4 radio (Chipcon CC2420), a contention MAC with ideal wake-up scheme and routes generated by the Dijsktra algorithm. The network has 120 nodes distributed over a field of 300 x 300m. One of the nodes, the sink, collects messages sent by all other nodes. Figure 1 shows the total energy required to forward all generated packets to the sink (upper graph) and the average end-to-end latency experienced by those packets (lower graph). Every different random position of the nodes results in different blue curves. The red solid line curves represent the average over all random positions. From the curves, it is clear that with the CC2420 chip, there is no trade-off to make (at least in low traffic situation) with the choice of the transmit power. The maximum output power provides the best results both in terms of consumed energy and in terms of latency. The potential advantage of using multiple-hops to reduce the consumed energy is not present with the CC2420 because of its high base current consumption (8 mA in transmit mode and 18 mA in receive mode). If this radio had a base current consumption of 2 mA both in receive and transmit mode, the latency versus energy curve would be as illustrated in Figure 2. In this case, latency and energy could be traded. Latency (ms) 12 10 -10 8 -8 -9 -7 6 -6 -5 4 2 -4 -3 -2 -1 0 1 2 3 4 5 7 6 8910 0 4000 4500 5000 5500 6000 6500 Energy (J) Figure 2: Latency versus Energy when varying the transmit power (hypothetical transceiver) An additional degree of optimisation in WSNs may be reached by run-time tuning of certain protocol parameters in order to tailor them to the application needs. CSEM has shown here that there is potential tradeoff between reactivity and consumption by tuning the transmitted power if the base consumption can be reduced. Other parameters are under investigation under the IST WASP project. [1] IST-034963 WASP Project, Deliverable D4.2, http://www.wasp-project.org/ 85
Wireless Sensor Networks for Monitoring Cliffs in the Alps A. El-Hoiydi, J.-D. Decotignie In November 2006, CSEM in collaboration with CREALP and MAD technologies installed a wireless sensor network to monitor rock movements on a cliff near Sion. Since then, it has been running without interruption and without battery change. This report describes the settings and the intermediate results of this experiment. Wireless sensor networks find natural application areas in the domain of environmental sensing. In such networks, sensors are connected to small battery powered nodes that include a CPU and radio transceiver. The information sensed on the node is transmitted to a sink node that is often connected to some infrastructure (GSM, LAN, ...). CSEM, like many other institutes, has deployed such applications for short-term experiments. In this report, CSEM presents results of one of the first long-term experiments without human intervention. Figure 1: The Chandoline site with the sensor locations The selected site is a cliff in the vicinity of the city of Sion in the Swiss Alps. The cliff is under observation because numerous rocks have fallen, jeopardizing an industrial zone located at the bottom of the cliff (Figure 1). Monitoring is done by measuring the relative movement of rocks using extensometers. Figure 2: An open sensor node with the extensometer The site was originally equipped with extensometers wired to a central monitoring station at the top of the cliff. For security 86 reasons, the existing monitoring installation was maintained during the test phase. A new set of 3 extensometers has been installed. Each accelerometer is connected to a wireless sensor network node (Figure 2). Due to the propagation conditions, an additional node is used as a relay between the sensors and the sink node that collects all the measurements. Each sensor node is built around the Xemics XE88LC05 processor and a radio module based on the XE1203 transceiver operating in the 868 MHz band. The protocol stack includes Wisemac, a simple dynamically built routing protocol and clock synchronisation. Wisemac is an ultra low power contention medium access control based on an adaptive preamble sampling technique [1] developed at CSEM under the WisenetTM project. Nodes and sensors are powered by a single 20 A.h Li Battery. Every minute each sensor node transmits the reading of the extensometer and the local temperature (used for compensation) to the sink node (Figure 3). Battery voltage and other statistics are also sent regularly. Figure 1 shows the routes (from the nodes to the sink) that were found best by the routing algorithm. Position [mm] Temperature Figure 3: Plot of the sensor measurements over a week The system has been running without human intervention for more than a year. Measurements match those captured by the pre-existing installation. This shows that such a system offers a viable solution. Compared to wired systems, it is easier to install and does not suffer from potential damage to the wires. The predicted battery life is around 10 years for the sensor nodes but less for the relay and the sink node. Long term campaigns in isolated locations are possible. [1] A. El-Hoiydi, et al., “WiseMAC: An Ultra Low Power MAC Protocol for Multi-hop Wireless Sensor Networks”, ALGOSENSORS 2004, 18-31
Page 1 and 2:
centre suisse d’électronique et
Page 4 and 5:
CONTENTS PREFACE 5 RESEARCH ACTIVIT
Page 6:
PREFACE Dear Reader, In this report
Page 9 and 10:
TissueOptics - Portable SpO2 Monito
Page 11 and 12:
Counterfeit - Machine Readable Cove
Page 13 and 14:
ArrayFM - An Atomic Force Microscop
Page 15 and 16:
Encoder - Nanometric Optical Absolu
Page 17 and 18:
PackTime - Zero-Level Packaging of
Page 19 and 20:
TissueOptics - Portable SpO2 Monito
Page 21 and 22:
spectrometer applications so CSEM h
Page 23 and 24:
As a first step, CSEM is building s
Page 25 and 26:
Data Fusion for Wireless Distribute
Page 27 and 28:
A High-Performance 2.4 GHz RF Front
Page 29 and 30:
Quasi-Harmonic Quadrature CMOS Rela
Page 31 and 32:
icycam, a System-On Chip (SoC) for
Page 34 and 35:
PHOTONICS Nicolas Blanc The Photoni
Page 36 and 37: Optoelectronic Test Equipment for I
Page 38 and 39: Compact Illumination Modules Based
Page 40 and 41: Efficient Screening and Formulation
Page 42: Optical Fill Factor Enhancement for
Page 45 and 46: Dissolved Oxygen Sensor with Self-C
Page 47 and 48: Metal Micro-Parts Fabrication F. Ca
Page 49 and 50: Towards an Optical Switch with J-ag
Page 51 and 52: Towards Plasmon Enhanced Detectors
Page 53 and 54: Sol-Gel based Nanoporous Layers as
Page 55 and 56: Nanoporous Membranes for Medical Di
Page 57 and 58: Parallel Nanoscale Dispensing of Li
Page 59 and 60: Detection Methods for Nanotoxicolog
Page 61 and 62: Composite Materials for Bone Implan
Page 63 and 64: Smart Wound Dressing with Integrate
Page 65 and 66: Food Safety with the Help of a Mini
Page 68 and 69: NANOMEDICINE Peter Seitz Mandated b
Page 70: X-Ray Microscopy and Micrometer-Res
Page 73 and 74: Micro-Vibration Analysis Setup for
Page 75 and 76: the signals with a reference to sta
Page 77 and 78: Prediction of Neurocardiovascular E
Page 79 and 80: Continuous Arterial Blood Pressure
Page 81 and 82: UWB Antenna with Improved Bandwidth
Page 83 and 84: A Wireless Sensor Network for Fire
Page 85: A MAC Protocol for UWB-IR Wireless
Page 89 and 90: Wearable Systems to Protect Rescuer
Page 91 and 92: . 90
Page 93 and 94: NanoHand - A System for Automated N
Page 95 and 96: Isolation and Reversible Immobiliza
Page 97 and 98: Sensor and Connector Integration in
Page 99 and 100: Pressure Sensing Strip - Packaging
Page 101 and 102: Optical / Fluidic Integration of Si
Page 103 and 104: 102
Page 105 and 106: PRN-cw Backscatter Lidar Prototype
Page 107 and 108: 106
Page 109 and 110: Quality Control A. Dommann, A. Ibza
Page 111 and 112: [18] A.-C. Pliska, C. Bosshard "Adh
Page 113 and 114: [21] E. Onillon, P. Theurillat, A.
Page 115 and 116: A. Bonfiglio, N. Carbonaro, C. Chuz
Page 117 and 118: H. Heinzelmann "CSEM and CSEM Brazi
Page 119 and 120: C. Piguet "High Level Energy and Po
Page 121 and 122: J. Solà I Caros "Annual meeting of
Page 123 and 124: 8241.2 DCPP-NM SOLID Solid on Liqui
Page 125 and 126: LISA-PAAM Development, demonstratio
Page 127 and 128: University Institute Professor Fiel
Page 129 and 130: 128 Title of lecture Context Locati
Page 131 and 132: Name Professor / University Theme /
Page 133 and 134: C. Piguet Member of the Board of th
show all

research activities in 2007 - CSEM

Create successful ePaper yourself

Delete template?

Save as template?