stabilizing tracking : demos on berkeley’s mote platform
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Stabilizing Tracking :Demos on Berkeley’s Mote Platform
Anish Arora, Murat Demirbas, Sandip Bapat, Sohail Munir
Ohio State
Tracking Problem
• Consider an undirected graph where any two nodes connected by an edge are called neighbors
• There is an evader that moves from a node to a neighboring node each Te seconds
• There is a pursuer that moves from any node to a neighboring node each Tp seconds, where Tp < Te
• Associate a “sensor process” with each node so that the pursuer catches up with the evader in short time
Two Approaches to Stabilization
• OSU tracking protocol sensor processes communicate periodically with neighbors stabilizes and tracks faster
• UT tracking protocol sensor processes communicate with neighbors only upon
request minimizes number of messages and energy efficient
OSU Tracking Protocol
Sensor process
• Processes communicate periodically (four times per second) with their neighbors
• Message format Src: Id of sender Parent: Id of parent of Src Dist: Distance from root to Src Value: The logical timestamp when the bug was detected by
the root mote of Src
• Processes run stabilizing tree algorithm to form the
tracking tree
Stabilizing Tree Algorithm
• Dynamic-rooted minimum-distance spanning tree algorithm
• Self stabilizing to the invariant that the tree is rooted at the bug
• Asynchronous Does not require any underlying synchronization
mechanism, or local clocks
• Ad hoc Works for any topology
A Tracking Tree Forms…with Bug at Root
• Bug is on mote 2
• Visualization tool shows tracking tree formed with root at mote 2
Video Screenshot
Tree Stabilizes…when Motes State gets Corrupted
• Tree rooted at mote 2, where bug is located
• State of mote 16 is transiently corrupted
• Two trees, with roots at motes 2 and 16, are formed
• Source of corruption at mote 16 is removed
• A single tree, potentially different from the original one, is (re)formed
Video Screenshot1 Screenshot2
Tree Stabilizes…even when Motes Failstop
• Tree is rooted at mote 2
• Mote 14 points to mote 10 as the next hop on its shortest path to the root
• Mote 10 fails (is turned off, radio unit fails, or runs out of battery)
• Mote 14 now points to mote 13 or mote 15 instead of the failed mote 5
• Tree (re)stabilizes
Video Screenshot1 Screenshot2
Spider Modes
• Line following If spider goes off line, it searches for line and follows it until it
reaches the end of the line
• Direction tracking Colored lines encode the four directions
e.g. Long Yellow + Short Black = North Spider calculates its direction after a complete line traversal
• Reading from mote Motes blink IR LEDs at four different frequencies to communicate
the four directions On reaching a mote, spider detects the frequency of emitted IR
signals and decides how to turn
The Spider Converges to the Grid...and Tracks the Tree
• Spider converges to the grid from any point within grid, without falling off the edge
• Upon converging, spider regains its sense of direction within one complete line traversal
• Upon regaining sense of direction, spider tracks tree by following direction signals from the motes
Video
The Spider Catches the Bug…assuming Spider is Faster
• Spider follows the tree all the way to the root, where the bug is located and catches the bug
• Even if the bug moves, the tree reconfigures when the bug is detected at the next mote
• So, if the bug stops or is slower than the spider, the spider eventually catches the bug
Video
The Spider Catches the Bug…even if Motes Failstop
• If spider reaches a failed mote, it cannot get a direction signal
• Spider then chooses a random direction to follow. If this direction leads it off the grid, it backs up and retries till it finds a grid direction
• On reaching the next non-failed node, the spider gets a proper direction to follow and catches the bug eventually
Video
Engineering tricks
• Main problem – Lack of a fat communication pipe between spider and motes
• Encoding directions using line colors
• Using IR LEDs on motes to communicate with spider
• Ensuring that motes do not detect spider as the bug using a light source
Future work: Hybrid approaches
• Proxy Pursuer or Agent
• Publish/Subscribe service for interest based information propagation to pursuer
• On-demand stabilization of the spanning tree
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