Projects Using TinyOS

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• Adaptive Communication Networks Research Group Aston University, Dimitrios Georgoulas, In-Motes
  http://www50.brinkster.com/georgoud/Overview.html
  In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in Wireless Sensor Networks (WSNs). In-Motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception, cognition and control, forming the basis for its intelligence. Our middleware incorporates technologies such as Linda-like tuplespaces and federated system architecture in order to obtain a high degree of collaboration and coordination for the agent society. A set of behavioral rules inspired by a community of bacterial strains is also generated as the means for robustness of the WSN.
  
  
• AFRL/IFTA (USAF), Pat Marshall, Mag. Measurements
  Trying to conduct magnetic measuremnts with the MICA2DOT and an separate 3-axis mag.
  
  
• Aston University United Kingdom, Dimitrios Georgoulas, Application layer coding for optimising lifetime in ad-hoc networks
  http://www.ee.aston.ac.uk/research/acrg/acrg-student-projects.html
  The project will assess and optimise the use of application level coding in ad-hoc mobile networks and investigate the applicability of agent technologies towards that goal. By building example networks based on TinyOS and motes it will be possible to measure accurate energy use as a function of network traffic for different compression schemes and agent frameworks. Analytic models will be developed and network simulations will also be performed.
  
  
• Ben-Gurion University of the Negev ISRAEL, Reuven Yagel, SOS - Self-stabilzing Operating System
  http://www.cs.bgu.ac.il/~yagel/sos
  Research (& develop) the means of making the core parts of an OS behave in a Self-Stabilizing manner.
  
  
• Boeing, M&CT, Paul Murray, Robotic Grids
  Blimp localization using Crossbow Crickets. Part of a larger project targeting a swarming search and rescue using heterogeneous platforms.
  
  
• Boston University, Wei Li, Control and Optimization of Sensor Network
  http://people.bu.edu/wli
  
  
  
• Brilliant Technology Inc, Kevin Tseng, Structural Health Monitoring using Wireless Mesh Sensor Network
  http://www.tBrilliant.com
  Developing a Structural Health Monitoring System using Wireless Mesh Sensor Network
  
  
• Camalie Vineyards, Mark Holler, Camalie Net - Vineyard Management
  http://camalie.com/WirelessSensing/WirelessSensors.htm
  Optimization of irrigation to reduce water use and improve Cabernet Sauvignon grape quality. Monitor soil moisture at multiple locations and depths throughout the vineyard. Also monitor irrigation system pressures to verify operation. Control irrigation to match weather and avoid over watering. Water is scarce at this location and energy costs to pump water are also significant. Camalie Net was used in 2005, which produced our highest yields and best quality to date.
  
  
• Clemson University, Chris Post, Environmental Sensor Networks
  http://gis.clemson.edu
  We are working on environmental sensor network applications involving issues related to water quality.
  
  
• CSIRO, Peter Corke, Wireless Sensor and Actuator Networks
  http://www3.ict.csiro.au/ict/landing/channelandcontentwithrelatedlinks/0,,a16254_b209659,00.html
  Wireless, ad hoc sensor and actuation networks (WSANs) differ from the more commonly seen sensor networks in that they offer more than automated data collection and monitoring of systems. WSANs close the loop a system by allowing nodes within the network to perform actions (actuation) in response to sensed data and shared information.
  
  
• CSIRO, Philip Valencia, Fleck WSAN
  http://www3.ict.csiro.au/ict/landing/channelandcontentwithrelatedlinks/0,,a16254_b209659,00.html
  
  
  
• CSOIS, Utah State Univ., Zhen Song, MAS-net
  http://mechatronics.ece.usu.edu/mas-net/XbowComp/
  The MAS-net project merges the latest sensor network technology with mobile robot technology to set up a mobile ad-hoc actuator and sensor network for diffusing contamination monitoring and elimination, such as characterizing and removing poisonous fog.
  
  
• Datatronics, Spain, Frederic Simon, RFDetect
  http://www.datatronics.es/
  Detection of RF tag through motes
  
  
• EPFL (Switzerland), Thomas Schmid, Henri Dubois-Ferriere, SensorScope
  http://sensorscope.epfl.ch
  SensorScope is a wireless sensor network deployed in the new I&C building on the EPFL campus. The network currently consists of around 20 mica2 and mica2dot motes, equipped with a variety of sensors (such as light, temperature or acoustic). SensorScope's purpose is to serve as a realistic prototype deployment (motes run on batteries, no wired backchannel) for research activities within the MICS center.
  
  
• ETH Zurich, Jan Beutel, BTnode Project
  http://www.btnode.ethz.ch
  The BTnode is an autonomous wireless communication and computing platform based on a Bluetooth radio and a microcontroller. It serves as a demonstration platform for research in mobile and ad-hoc connected networks (MANETs) and distributed sensor networks. The BTnode has been jointly developed at ETH Zurich by the Computer Engineering and Networks Laboratory (TIK) and the Research Group for Distributed Systems. Currently, the BTnode is primarily used in two major research projects: NCCR MICS and Smart-Its. The low-power radio is the same as used on the Berkeley Mica2 Motes, making the BTnode rev3 a twin of both the Mote and the old BTnode. Both radios can be operated simultaneously or be independently powered off completely when not in use, considerably reducing the idle power consumption of the device.
  
  
• Fraunhofer Institute for Open Communication Systems, Germany, Lei Shi, Innovativer paddeln
  http://www.berlinews.de/archiv-2004/2409.shtml
  The goal of this project is to develop a real-time sensing system located on a canoe using with mica2dots and TinyOS. The mica2dots gather the pressure information from the paddels and transmit it back to a base mica exploiting the capacity of B-MAC.
  
  
• Freescale Semiconductor Danmark a/s, Peter Busk, Freescale Tiny Zigbee
  Test of TinyOS and TinyDB on the Freescale Zigbee development boards
  
  
• Georgia Institute of Technology, Tommaso Melodia, Wireless Sensor and Actor Networks
  http://www.ece.gatech.edu/research/labs/bwn/actors/
  Wireless Sensor and Actor Networks (WSANs) are composed of heterogeneous nodes referred to as sensors and actors. The collaborative operation of sensors enables the distributed sensing of a physical phenomenon, while the role of actors is to collect and process sensor data and perform appropriate actions.
  
  
• Harvard University, Matt Welsh, CodeBlue
  http://www.eecs.harvard.edu/~mdw/proj/codeblue
  Our group is exploring applications of wireless sensor network technology to a range of medical applications, including pre-hospital and in-hospital emergency care, disaster response, and stroke patient rehabilitation.
  
  
• Harvard University, Geoff Werner-Allen, Monitoring Volcanic Eruptions with a Wireless Sensor Network
  http://www.eecs.harvard.edu/~werner/projects/volcano
  This project is developing sensor networks for real-time monitoring of volcanic eruptions. We have deployed a sensor network on Volcan Tungurahua, Ecuador.
  
  
• Harvard University, Konrad Lorincz, MoteTrack
  http://www.eecs.harvard.edu/~konrad/projects/motetrack/
  MoteTrack is a robust, decentralized location tracking system based on TinyOS motes (Mica2, MicaZ, Telos). MoteTrack allows motes can determine their own location to within 1-2 meter accuracy by comparing received radio signals to a replicated database of stored signatures.
  
  
• Harvard University, Victor Shnayder, PowerTOSSIM
  http://www.eecs.harvard.edu/~shnayder/ptossim/
  Adding support for power simulation to TOSSIM.
  
  
• Harvard University, Chaki Ng, Mirage
  https://mirage.berkeley.intel-research.net
  150-node testbed hosted by Intel Research Berkeley.
  
  
• Helmut-Schmidt-University, Hamburg, Hans-Joerg Koerber, Embedding of a PIC based platform in TinyOS for industrial applications
  http://www.hsu-hh.de/emt/index_1P3YcVDCx1Br8tob.html
  
  
  
• Intel Research, Eric Paulos, Activating Environments and Objects
  http://paulos.net/teaching/2005/DM150/
  This is a course being taught at the San Francisco Art Institute using motes as tools for artists and designers to create and activate new media objects.
  
  
• Luxoft Labs, Alexander Belenki, IEEE 802.15.4 MAC for Chipcon CC2420
  http://www.luxoft.com/
  IEEE 802.15.4 MAC for Chipcon CC2420
  
  
• MIT, David Moore, A Distributed Localization Algorithm
  http://cgr.csail.mit.edu/netloc
  Design and implementation of a distributed localization algorithm using Crickets running TinyOS.
  
  
• RLW Inc., Matt Orlofsky, Advanced Energy Scavenging
  http://www.rlwinc.com
  A wireless sensor that derives the power necessary for it operation from environmental vibrations. The primary purpose of the project is to demonstrate vibration-based power scavenging and its integration into a self-contained wireless sensor that measures and communicates some measured property of the platform, in the present case the temperature.
  
  
• TU Delft/TNO, Tom Parker, T-MAC
  http://www.consensus.tudelft.nl/documents_delft/03vandam.pdf
  We have implemented T(imeout)-MAC on TinyOS, a low-power MAC protocol that switches the radio off up to 96% of the time. It is now available in contrib/t-mac/ in the main TinyOS CVS tree.
  
  
• Tyndall National Institute, Gearoid Hynes, Plants
  http://plants.edenproject.com
  The PLANTS project is an EU-funded Fifth Framework Programme Research and Development project that combines microelectronics, software, telecommunications and plant science research. The project builds on the concept of "hidden computers". Specific sensors, such as for touch, are integrated within an object or ‘artefact’ with localised computation and communication components. These artefacts are thus capable of sensing their environment, communicating with each other or otherwise acting upon the environment. They can be created to respond to our requirements, sometimes acting in an intelligent way (known as "ambient intelligence"). As a simple example, consider an "intelligent building" that senses which room you walk in; lights are turned on as you enter and telephone calls are forwarded to the area in which you are present. The PLANTS project extends this vision further and into the natural world: it will be the first time that ambient intelligence technology will be used to encompass plant requirements, via establishing three-way interaction between plants, people and objects.
  
  
• Ubiquitous Networking Lab, NRL, Tokyo Denki University, Yoshito Tobe, WISER
  http://www.unl.im.dendai.ac.jp/wiser/
  We are considering about platform-system of multi-robot sensor netoworks.we can utilize the movement of nodes as a means of transferring data. The movement of a node can be controlled by other nodes for the sake of communications.
  
  
• UC Berkeley, Jonathan Hui, Deluge
  http://www.cs.berkeley.edu/~jwhui/research/projects/deluge/
  Network programming allows for the programming of nodes by propagating a new program image over the wireless network and having each node program themselves with the new image. Features include: multihop support, epidemic propagation, redundant data integrity checks, multiple program images, golden image support, isolated bootloader, rollback gesture support, and a small RAM footprint.
  
  
• UC Berkeley, Phil Levis, Maté
  http://www.cs.berkeley.edu/~pal/mate-web/
  Maté allows you to program TinyOS networks using simple, high-level scripts. These scripts compile to the instruction set of an application specific virtual machine.
  
  
• UC Berkeley, Barbara Hohlt, FPS
  http://www.cs.berkeley.edu/~hohltb/fps
  Flexible Power Scheduling provides network layer communication scheduling to reduce radio power consumption. The scheduling continuosly adapts over time allowing for fluctuation in the network thereby avoiding static schedules and fixed duty cycles.
  
  
• UC Berkeley, Sukun Kim, Structural Health Monitoring of the Golden Gate Bridge
  http://www.cs.berkeley.edu/~binetude/ggb
  Golden Gate Bridge is one of the landmarks of the state of California. It is located in a seismically high risk region, and is subject to high wind seasons. The objective of the project is to instrument the bridge using a MEMS sensor network, and monitor the structural health of the bridge, detect possible damage in the event of an earthquake and monitor the maximum displacement of the main span and the towers in the wind season for traffic control.
  
  
• UC Berkeley, Kamin Whitehouse, Calamari
  http://www.cs.berkeley.edu/~kamin/calamari
  Sensor Field Localization System
  
  
• UC Berkeley, Gilman Tolle, Nucleus
  http://www.cs.berkeley.edu/~get/nucleus
  Bringing interactive network management to the TinyOS space.
  
  
• UC Berkeley, Phoebus Chen, NEST
  http://www.eecs.berkeley.edu/~phoebusc/330NEST/welcome.html
  Control over Sensor Networks
  
  
• UC Berkeley, Joel Wilson, Fire Information and Rescue Equipment
  http://fire.me.berkeley.edu
  We are developing IT decision-support tools for firefighters that will enable tracking firefighters in buildings and monitoring building conditions.
  
  
• UC Berkeley, Yao-Jung Wen, Intelligent Daylighting System
  http://best.me.berkeley.edu/research/smartLighting/info.php
  The overall goal of this project is to develop an intelligent daylighting system that can outperform today's commercially available systems. Specifically, we aim to increase user satisfaction while minimizing energy consumption and expense. We propose to achieve this through the use of several intelligent techniques including influence-diagram based decision-making, fuzzy-based sensor validation and fusion, and agency. The assumed underlying sensor technology is Smart Dust Motes, a wireless sensing and communications platform currently under development at U.C. Berkeley and various private companies.
  
  
• UC Berkeley, Farzad Eskafi, PicoRadio
  http://bwrc.eecs.berkeley.edu
  We have implemented RICER/TICER along with Opportunistic Routing over low power telos motes
  
  
• UCD, Antonio Ruzzelli, AIC
  http://www.adaptiveinformation.ie/home.asp
  The mission of the AIC is to integrate research on adaptive sensor networks, content extraction and adaptive utilization and to collaborate with industry partners and state bodies to develop applications in areas such as health management, traffic management, environmental monitoring and personalized retailing.
  
  
• UCLA, Shahin Farshchi, A TinyOS-Based Wireless Neural Interface
  http://www.ee.ucla.edu/~judylab/research/projects/Shahin/index.htm
  This research project investigates methods of implementing a wireless neural recording interface. Such a system must be capable of sensing, amplifying, and transmitting neural signals with a sampling frequency of at least 100 Hz per channel, while being small, low cost, lightweight, and low power. The system also requires a receiver to receive, demodulate and display the transmitted neural signals. Existing approaches to develop a wireless EEG measurement tool have ranged from designing a custom microfabricated recording and telemetry system, to the use of commercial-off-the-shelf (COTS) PC technology. Each approach has its own set of advantages and drawbacks. A novel approach would be a compromise between custom designing each sub-system and using PC-COTS components. This approach would achieve a balance between low-noise and low-power signal transmission, data communication, and networking performance. Global efforts, led by the Computer Science Department at the University of California at Berkeley, have succeeded in developing an operating system with a component-based runtime environment (called TinyOS) designed to provide support for embedded systems with a minimal amount of physical hardware to keep the system size very small. The primary goal of this effort has been to facilitate the creation of ultra-low-power miniature devices that can be widely distributed in mesh networks (otherwise known as "multi-hop") to remotely monitor low-frequency phenomena. The wireless sensor nodes, which are commonly referred to as “motes”, have been designed to operate using TinyOS and are currently being used in wildfire-instrumentation, habitat-monitoring, and global-positioning applications to mention just a few. The data-throughput performance of the motes is severely constrained by their ultra-low-power operation and large-scale mesh networking capabilities. Conventional data-acquisition and communication protocols could increase data throughput at the expense of increased power-consumption and mote-to-mote networking capabilities. So far, we have successfully demonstrated the design of a TinyOS-based wireless neural interface. The system is capable of amplifying, sampling, transmitting, and reconstructing input signals at a rate of 5600 8-bit samples per second. This data rate allows for the reliable transmission of 8 EEG channels, or 1 channel at 5.6 kSamples/sec for single-unit recording from live, mobile test subjects. We are currently investigating methods for increasing the data-throughput capabilities of TinyOS-Based sensor networks and designing front-end neural amplifier circuits to interface with test subjects.
  
  
• UCLA Cens, , TinyDiffusion
  http://www.cens.ucla.edu/~mmysore/Design/
  
  
  
• Univ of Louisiana, Louisiana State University, and Southern Univ. at Baton Rouge, Dr. Nian-Feng Tzeng, UCoMS: Ubiquitous Computing and Monitoring System for Oil/Gas Exploitation and Management
  http://www.ucoms.org
  This UCoMS research aims to develop and deploy a Ubiquitous Computing and Monitoring System (UCoMS) for oil/gas exploitation and management.The technical solutions will be generally applicable to sensor networks, wireless communications, and grid computing. These solutions will effectively facilitate drilling and operational data logging and processing, on-platform information distribution and displaying, infrastructure monitoring/intrusion detection, seismic processing and inversion, and management of complex surface facilities and pipelines. Decommissioned well platforms can be monitored and safeguarded using UCoMS, with a potential of fostering new industries as well in the future.
  
  
• Universidade Federal de Minas Gerais, Luiz Correia, Sensornet
  http://www.sensornet.dcc.ufmg.br/
  Architecture, Protocols, Management and Applications over Wireless Sensor Networks The SensorNet project is granted by the National Council for Scientific and Technological Development - CNPq, and is part of the Program for Support Research, Development and Technological Innovations in Information Technology (PDI-TI). Until now, takes part in the SensorNet project the research groups in Wireless Networks, Mobile Robotics and Wireless Communications of the Federal University of Minas Gerais (UFMG) and Federal University of Pernambuco (UFPE).
  
  
• University Bremen (Germany), Markus Becker, Autonomous Cooperating Logistic Processes - A Paradigm Shift and its Limitations
  http://www.sfb637.uni-bremen.de/index.php?id=8&L=2
  The dynamic and structural complexity of logistics networks makes it very difficult to provide all information necessary for a central planning and control instance. It requires, therefore, adaptive logistic processes including autonomous capabilities for the decentralised coordination of autonomous logistic objects in a heterarchical structure. The autonomy of the logistic objects such as cargo, transit equipment and transportation systems can be realised by novel communication technologies such as Radio Frequency Identification (RFID) and wireless communication networks. These and others permit and require new control strategies and autonomous decentralised control systems for logistic processes. In this setting, aspects like flexibility, adaptivity and reactivity to dynamically changing external influences while maintaining the global goals are of central interest.
  
  
• University College Dublin, Richard Tynan, Tinyos IDE
  http://tinyoside.ucd.ie
  The purpose of this project is to create an Integrated Development Environment (IDE) to facilitate the implementation of an application based on TinyOS
  
  
• University College London, University of Cambridge, Royal Veterinary College, University of Wales, Marcelo Pias, SESAME: SEnsing for Sport And Managed Exercise
  http://www.sesame.ucl.ac.uk/
  The SESAME consortium is a multidisciplinary group formed to investigate the use of wireless sensor-based systems with offline and real-time processing and feedback in enhancing the performance of elite athletes and young athletes who have been identified as having world class potential. The overall goals of the project lie in enhancing performance, improving coach education, and advancing sports science using a range of both hardware and software technologies to achieve this. In so doing, we will build on the extensive experience that exists both within and outside the consortium in the application of sensor systems to human and animal monitoring, and we will seek to advance that knowledge both in terms of outcomes that are specific to sports and in terms of computer science fundamentals. Despite a specific focus on athletics, which provides a challenging but achievable demonstration domain and is timely in view of the national importance of the 2012 Olympics, the SESAME technical approach and its solutions will be deliberately generic, to enable their subsequent application to a wider range of training and health care scenarios including, for example, the rehabilitation of patients following surgery, stroke or injury, and support for people with physical disabilities.
  
  
• University of Alabama in Huntsville, Emil Jovanov, Wearable Health Monitoring Systems
  http://www.ece.uah.edu/~jovanov/whrms/
  Development of wireless intelligent sensors and wearable monitoring systems for ambulatory health monitoring.
  
  
• University of California at Irvine, Pat Lee, System Test Laboratory
  http://testlab.ics.uci.edu/
  This lab is devoted to the study of testing problems in hardware and hardware/software systems. For large hardware and software design projects, it is typical that over 50% of design effort and cost is dedicated to testing and debugging. Our research includes testing for design errors and testing for physical defects occuring during the VLSI manufacturing process. The laboratory is directed by Prof. Ian G. Harris and research projects include Covalidation of Embedded Hardware-Software Systems, FPGA testing, Behavioral Design Validation, and Partial Scan/BIST Insertion.
  
  
• University of California, Berkeley, Rodrigo Fonseca, BVR
  http://www.cs.berkeley.edu/~rfonseca/bvr/bvr.html
  Beacon Vector Routing is a point to point protocol that uses virtual coordinates to find routes. The protocol uses a subset of the nodes as beacons, and each node's coordinates it its distance in hops to each beacon. Routing is done greedly. There is also work going on for implementing a lookup service for BVR.
  
  
• University of California, Davis, James P. Crutchfield, Dynamics of Learning
  cse.ucdavis.edu/~dynlearn
  The Dynamics of Learning project is headed by Professor Jim Crutchfield and sponsored by DARPA through its TASK program. Like much of the work associated with complex systems research, the Dynamics of Learning project is agent-based, but not in the usual way. Most agent-based research designs agents for a particular task, or for simulating a particular model; some focus on building general simulation systems for agent-design. While these efforts have been valuable and (mostly) successful, they haven't given us a theory of agents or their collective behavior. This is the gap the project hopes to fill. The goal is a general, quantitative, predictive theory of cognitive agents and of agent collectives, applying both to natural systems (e.g., the immune system, or insect swarms) and artificial ones (e.g., a group of autonomous robots). The theory would be analytical, predicting what a given system would do, rather than synthetic, saying how to design a system with some desired behaviors, but the analytical methods ought to be useful to designers.
  
  
• University of California, Davis ECE department, Daniel Scholl, Agent programming
  http://www.ece.ucdavis.edu/~lpszumel/
  Agent programming of wireless sensor networks.
  
  
• University of Cambridge, Computer Laboratory, Marcelo Pias, Sentient Sports
  http://www.cl.cam.ac.uk/Research/DTG/research/sentient/sports.php
  Sports users would benefit from tailored technology if commercially available to: (a) support athlete's training by the provision of fine-grained information about their actions and performance; (b) model an athlete's body and its actions; (d) compare and evaluate different athletes' actions and performance. To pursue these goals, we take the research approach of active tracking of position and medical data of athletes by instrumenting the athlete's body and equipment with customised tiny wireless sensor devices.
  
  
• University of Colorado, Boulder, Anmol Sheth, MANTIS
  http://mantis.cs.colorado.edu/
  The MANTIS group is a part of the Computer Science Department at the University of Colorado, Boulder. We are focused on research in the area of wireless sensor networking, which is bringing together aspects of operating systems, networking and embedded systems design. MOS, the MANTIS Operating System, is a multi-threaded OS designed specifically for sensor networking, and all of our current research utilizes this system development framework. MOS has been designed to make programming wireless sensor nodes a very similar process to programming a normal PC.
  
  
• university of memphis, caleb goodwin, center for advanced senors: onto sensor
  http://www.ee.memphis.edu/cas/projects.htm
  OntoSensor: a prototype sensor knowledge repository compatible with evolving Semantic Web infrastructure. OntoSensor includes definitions of concepts and properties adopted (in part) from SensorML, extensions to IEEE SUMO and references to ISO 19115. Simple queries have been developed and tested using Protégé 2000 and Prolog. Although OntoSensor is in the early development stage, it presents a practical approach to building a sensor knowledge repository. It is proposed that OntoSensor may serve as a component in comprehensive applications that include more advanced inference mechanisms. Such comprehensive applications will be used for synergistic fusion of heterogeneous data in a network-centric environment.
  
  
• University of Stuttgart, Germany, Andreas Lachenmann, TinyCubus: A Flexible and Adaptive Cross-Layer Framework for Sensor Networks
  http://www.ipvs.uni-stuttgart.de/abteilungen/vs/forschung/projekte/tinycubus/start
  With the proliferation of sensor networks and sensor network applications, the overall complexity of such systems is continuously increasing. Sensor networks are now heterogeneous in terms of their hardware characteristics and application requirements even within a single network. In addition, the requirements of currently supported applications are expected to change over time. All of this makes developing, deploying, and optimizing sensor network applications an extremely difficult task. In TinyCubus we research the necessary infrastructure to support the complexity of such systems.

  The architecture of TinyCubus consists of a data management framework, a cross-layer framework, and a configuration engine. The data management framework allows the dynamic selection and adaptation of system and data management components. The cross-layer framework supports data sharing and other forms of interaction between components in order to achieve cross-layer optimizations. The configuration engine allows code to be distributed reliably and efficiently by taking into account the topology of sensors and their assigned functionality.
  
  

• University of Tennessee, Kiran Jaladhi, power control for wireless sensor networks
  www.ece.utk.edu/~djouadi
  Trying to implement power control algorithms for wireless networks
  
  
• University of Texas at Arlington, Brent Lagesse, PICO
  http://www.cse.uta.edu/pico@cse/
  Pervasive Information Communities organization (PICO) is a framework to create mission-oriented dynamic communities of software entities that perform tasks on behalf of users and devices autonomously. PICO can be used effectively in many dynamically changing time-critical applications that demand proactive real-time collaborations among physical devices, services, and personnel in heterogeneous environments. The novel features of PICO include: i) creation of mission oriented dynamic communities of software agents, ii) just-in-time communication and proactive collaboration among communities, and iii) adaptability to hardware and software changes and application requirements. PICO has applications in many domains such as telemedicine, military, crisis management, manufacturing and many day-to-day activities.
  
  
• University of Utah, John Regehr, stacktool
  http://www.cs.utah.edu/~regehr/stacktool/
  Compute an upper bound on stack memory consumption of a TOS program.
  
  
• University of Victoria, Tereus Scott, Sensor Localization with Ring Overlapping
  http://www.tereus.net/project.htm
  Implementation and analysis of the ROCRSSI (Ring Overlapping Comparison or Received Signal Strength Indication) method of sensor localization. This goals of the project are to assess the performance of this algorithm and to identify real world factors that affect the ability to use signal strength for sensor localization in the real world.
  
  
• University of Victoria, Canada, Kui Wu, Wireless Sensor Networks and Mobile Computing
  http://www.cs.uvic.ca/~wkui/research/researchProjects.htm
  1. Sensor Localization 2. Energy Efficient Information Collection Framework 3. Acoustic Monitoring and Audio Recognition With Sensor Networks 4. Mica Mote Antenna Radiation Pattern Analysis
  
  
• Universität Karlsruhe, Institute of Telematics, Hans-Joachim Hof, Secure Service Discovery in Service Centric Sensor Networks
  http://www.tm.uka.de/itm/projects.php?id=7
  The Goal of the project is to make it possible to insert and lookup a service description for a service in service centric sensor networks.
  
  
• Univsersity of Rome "La Sapienza", Andrea Vitaletti, Eyes
  http://eyes.eu.org
  The EYES project is a three years European research project (IST-2001-34734), on self-organizing and collaborative energy-efficient sensor networks. It address the convergence of distributed information processing, wireless communications, and mobile computing
  
  
• USC, Avinash sridharan, wireless link layer modeling
  http://ceng.usc.edu/%7Ebkrishna/research/papers/channelmodellingSECON04.pdf
  We are implementing a link layer model for the TOSSIM simulator that is conformat to the traces foound with MICA 2 radios
  
  
• Wayne State University, Weisong Shi, SPIRIT
  http://mist.cs.wayne.edu/spirit/spirit.html
  Waste Management System Monitoring using Wireless Sensors Networks