A Preliminary Proposal A Method of Forming Self-Healing Patterns on Amorphous Computing Agents A Preliminary Proposal

The Amorphous Computing Group Many identical “agents” Mass produced – Not reliable and no global clocks or beacons. “Throw at a problem.” Connected in changing, unpredictable ways. Goal: Coherent, robust behavior to achieve jobs

Motivation Researchers’ inspiration from living things Examples of life from engineering standpoint: Bees build a hive Wolves hunt in packs People build civilizations Most impressive: Cells, roughly identically programmed, create us

Why Now? Abundance of Microelectronic devices and MEMS Cilia clean rooms Smart paint Sound cancellation

Why Now? Advances in biotechnology We are able to “reprogram” genetic information of cells Can grow quickly and cheaply Don’t have concepts to allow us to engineer how life does Yet good processors, mobile, sensing.

Research at MIT Biology: Morphogenesis and self assembly as inspiration. - Use insights to understand biological phenomena Sensor Networks: Amorphous computers. More from a CS perspective.

Specific Project Area Radhika Nagpal, Daniel Coore: Complex Pattern formation. Fixed agents Made of lines and endpoints. Importance Differentiating function Determine distance and orientation

Healing Lines Lauren Clement – Self-healing lines Agents in line die – reform line Nagpal deals only with points and lines

Ex. Of How to Build a Line Fixed, randomly placed agents. Build a line connecting two given points Idea of gradient to tell distance Constant local communciation: - Random ID - Successor ID - Line? - Gradient value

Ex. How to Build a Line Endpoint A initiates gradient Each agent determines max gradient value, stores “successor ID” Gradient reaches Endpoint B, line back propagates. Successor Grad = 41 Grad = 35

Self-Healing Method 1 Endpoint A never stops outputting gradient Gradients and successor ID’s expire Line redrawn over and over Advantages: Can handle multiple gaps, good for large gaps Disadvantages: Redraw whole line when gap

Self-Healing Method 2 Only send gradient value once and then forget When break detected, successor listens, predecessor initiates gradient. Advantages: Good for small holes Disadvantages: Cannot handle multiple breaks with one gradient

My Project Extend Clement’s algorithms to deal with multiple lines. Requires sending, receiving, storing multiple gradients Way to choose method - Gradient to tell size of gap. Integrate into Nagpal’s compiler.

And if possible Enable Nagpal’s compiler to output to MICA Motes 4MHz Processor, wireless radio communication, sensors, batteries, TinyOS

Technical Risks Able to get number of motes (>= 50) - $, production ability Able to drive LED’s on motes. Able to get Nagpal’s algorithm to program motes (too much work?)

Milestones Find out detailed specifications for MICA Motes. March 2003. Understand algorithms and existing code for Nagpal’s compiler and Clement’s self-healing methods. April 2003. Full design with a design document. July 2003. Obtain motes. August 2003. Have first draft of code ready for testing. October 2003. Have final version of code working: December 2003. Have the motes tested running the programs produced by the compiler: February 2003. Have thesis written and finished: April 2003.

Resources Required Motes, LED’s Access to code and the people who wrote it HLSIM simulator