Network Embedded Systems Technology
Summer 2003 Retreat
January 17-18, 2003

 [ Slides Directory Listing |  Papers ]

Tuesday, June 17

• Session 1
  • Introduction and Introductions - David Culler
  • NEST demo: framework, integration and the dry run - Cory Sharp
  • nesC: 1.1 bumps and Future Directions  - David Gay
• Session 2
  • TinyDB / GSK Past, Present, Future  - Sam Madden
  • Scalable and Efficient Viral Code Propagation - Phil Levis
  • Multichannel Scheduling and Communication for Sensor Networks  - Umesh Shankar
• Open Demo and Poster Session
  • TinySec: Status and Progress - Chris Karlof and Naveen Sastry
  • Flexible Power Scheduling For Sensor Networks - Barbara Hohlt
  • Chipcon Localization - Jaein Jeong and Sukun Kim
  • Wildfire Instrumentation - Steve Glaser et al.
• Evening Panel: "From here to really real"
  • Sensor Networks for the Third World - Eric Brewer
  • Sensor Networks for Science - Deborah Estrin: 
  • The Difficulty of Entering a Sensor Network Market - Rick McGeer
  • The Problem of Privacy in Sensor Networks - Pamela Samuelson
  • The Sensor Network Startup - Robert Poor

Wednesday, June 18

• Session 3
  • Multi-hop Data Collection - Alec Woo, Terrance Tong, Phil Buonadonna
  • Calamari - Kamin Whitehouse
  • Error Encoding on Chipcon - Jaein Jeong and Cheng Tien Ee
• Session 4
  • Fresh off the boat: GDI - Rob Szewczyk, Joe Polastre, Alan Mainwaring
  • Security Roundup - David Wagner
  • Distributed Control - Shawn Schaffert and Bruno Sinopoli
• Session 5
  • Algorithmic Issues in Embedded Networks - Anish Aurora
  • Sensor Network Standardization panel - Jan Rabaey, Lakshman Krishnamurthy

Papers

• TinyOS: An Operating System for Sensor Networks
  We present TinyOS, a flexible, application-specific operating system for sensor networks. Sensor networks consist of (potentially) thousands of tiny, low-power nodes, each of which execute concurrent, reactive programs that must operate with severe memory and power constraints. The sensor network challenges of limited resources, event-centric concurrent applications, and low-power operation drive the design of TinyOS. Our solution combines flexible, fine-grain components with an execution model that supports complex yet safe concurrent operations. TinyOS meets these challenges well and has become the platform of choice for sensor network research; it is in use by over a hundred groups worldwide, and supports a broad range of applications and research topics. We provide a qualitative and quantitative evaluation of the system, showing that it supports complex, concurrent programs with very low memory requirements (many applications fit within 16KB of memory, and the core OS is 400 bytes) and efficient, low-power operation. We present our experiences with TinyOS as a platform for sensor network innovation and applications.
  
  
• Viral Code Propagation in Wireless Sensor Networks
  We present scalable and rapid algorithms for disseminating code through a sensor network. Unlike prior broadcast approaches, these algorithms are continuous processes, and therefore resistant to transient and high-loss networks. We evaluate implementations of the algorithms with a high fidelity simulation, quantifying their overhead and performance. We show that by dynamically adjusting transmission rates, networks can reprogram very quickly while having a low overhead when stable.
  

• The nesC Language: A Holistic Approach to Networked Embedded Systems
  We present nesC, a programming language for networked embedded systems, such as sensor network “motes,” which represent a new design space for application developers. Sensor networks consist of (potentially) thousands of tiny, low-power “motes,” each of which execute concurrent, reactive programs that must operate with severe memory and power constraints. nesC’s contribution is to support the special needs of this domain by exposing a programming model that incorporates event-driven execution, a flexible concurrency model, and component-oriented application design. Restrictions on the programming model allow the nesC compiler to perform whole-program analyses, including data-race detection (which improves reliability) and aggressive function inlining (which reduces resource consumption). nesC has been used to implement TinyOS, a small operating system for sensor networks, as well as several significant sensor applications. nesC and TinyOS have been adopted by a large number of sensor network research groups, and our experience and evaluation of the language shows that it is effective at supporting the complex, concurrent programming style demanded by this new class of deeply networked systems.