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Endeavouring to Build Networks of Tiny Devices

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Presentation on theme: "Endeavouring to Build Networks of Tiny Devices"— Presentation transcript:

1 Endeavouring to Build Networks of Tiny Devices
David Culler Computer Science Division U.C. Berkeley

2 Background Q1: design principles for Extremely Diverse system architectures? immense services (Millennium, Ninja) tiny devices appln as graph of state machines concurrency intensive, variation in load, robustness reactive tiny devices became “eyes and ears” of ubiquitous computing become source of control as well 4/2001 TinyOS

3 Emerging Microscopic Devices
CMOS trend is not just Moore’s law Micro Electical Mechanical Systems (MEMS) rich array of sensors are becoming cheap and tiny LNA mixer PLL baseband filters I SD Q SD Low-power Wireless Communication Imagine, all sorts of chips that are connected to the physical world and to cyberspace! 4/2001 TinyOS

4 Current One-Inch Networked Sensor
1” x 1.5” motherboard ATMEL 4Mhz, 8bit MCU, 512 bytes RAM, 8K pgm flash 900Mhz Radio (RF Monolithics) ft. range ATMEL network pgming assist Radio Signal strength control and sensing I2C EPROM (logging) Base-station ready stackable expansion connector all ports, i2c, pwr, clock… Several sensor boards basic protoboard tiny weather station (temp,light,hum,press) vibrations (2d acc, temp, LIGHT) accelerometers magnetometers 4/2001 TinyOS

5 TinyOS Approach Stylized programming model with extensive static information Program = graph of TOS components TOS component = command/event interface + behavior Rich expression of concurrency Events propagate across many components Tasks provide internal concurrency Regimented storage management Very simple implementation Broad range of alternative execution mechanisms For More see 4/2001 TinyOS

6 Tiny OS Concurrency Framework
Scheduler + Graph of Components constrained two-level scheduling model: threads + events Component: Commands, Event Handlers Frame (storage) Tasks (concurrency) Constrained Storage Model frame per component, shared stack, no heap Very lean multithreading Efficient Layering msg_rec(type, data) msg_send_done) Commands Events send_msg(addr, type, data) power(mode) init Messaging Component internal thread Internal State Power(mode) TX_packet(buf) init TX_packet_done (success) RX_packet_done (buffer) 4/2001 TinyOS

7 Application = Component Graph
Route map router sensor appln application Active Messages packet Radio Packet Serial Packet Temp photo SW HW Radio byte UART byte ADC Example: ad hoc, multi-hop routing of photo sensor readings bit RFM clocks 4/2001 TinyOS

8 DARPA-esq demo UAV drops nodes along road,
hot-water pipe insulation for package Nodes self configure into linear network Calibrate magnetometers Each detects passing vehicle Share filtered sensor data with 5 neighbors Each calculates estimated direction & velocity Share results As plane passes by, joins network upload as much of missing dataset as possible from each node when in range 7.5 KB of code! 4/2001 TinyOS

9 Cory Energy Monitoring/Mgmt System
50 nodes on 4th floor 5 level ad hoc net 30 sec sampling 250K samples to database over 6 weeks 4/2001 TinyOS

10 Energy Monitoring Network Arch
20-ton chiller sensor net control net GW GW GW 802-11 PC telegraph PC MYSQL modbus scada term UCB power monitor net Browser 4/2001 TinyOS

11 Directions Systems technology: long-term management Power management
integrate new MAC and rate control (Alec Woo) in situ network programming (Rob Szewczyk) node query scheme (Sam Madden) implicit discovery (Phil Levi) signal strength adaptation telegraph Power management Battery monitoring and adaptation current and voltage sensors non-intrusive load monitoring integrate with broader sensor net alert response 4/2001 TinyOS

12 Emerging “de facto” tiny system
Feb. bootcamp 40 people UCB, UCLA, USC, Cornell, Rutgers, Wash., LANL, Bosch, Accenture, Intel, crossbow Several groups actively developing around tinyOS on “rene” node Concurrency framework has held up well. Next generation(s) selected as DARPA networked embedded system tech (NEST) open platform Smaller building blocks for ubicomp 4/2001 TinyOS

13 NEST Program Structure – evolution
Challenge Application composition services coordination services synthesis Composition Open Platform SW platform HW platform sensors processing communication actuators storage initial low-power wireless Open Platform 100+ tiny devices for alg. dev. year 3 2 1 4/2001 TinyOS

14 HW Platforms Current: SmartDust MacroMOTE => Renes =>
Phase 1: 6 months => algorithm studies Mote++, MEMS sensors, TinyOS more microcontroller atmega163 => 2x storage atmega103 => 128K flash, 4k ram TIMSP430 => 60k flash, 2k ram, HW *, ... many subtle factors RFM with “ASH” 100 kb/s too early for bluetooth 100+ nodes for < 20K$ Phase 2: 30 months => composition of alg’s ARM-power, Bluetooth physical integrated system OS?? 4/2001 TinyOS

15 SW Platform Tiny event-driven component OS
allows NEST abstractions to emerge and each level Language-based robustness and optimization eg., critical path and jitter analysis inter-component transformations narrow interface with simple IDL Tiny networking power-aware appln-specific ad hoc routing, MAC, transmission control in network aggregation in situ programming Algorithm building blocks Local multicast event-driven reception intelligent pruning of retransmission non-blocking execution 4/2001 TinyOS

16 Programming Environment & Tools
Provide support for: event-driven programming, composition, debugging & visualization in the small (node) and large (collection) Emulation => simulation => real devices identical APIs, range of visibility, and reality Debugging and visualization tools geared toward many interacting nodes & event-centric development Application-Specific Virtual Machines analogous to query-plan vs query-processing engine FSM-based programming abstractions Macrocomputing 4/2001 TinyOS

17 FSM-based Software Approach
Fundamentally, we are not computing, we are moving data intelligently threads are a computing abstraction, FSMs are a protocol abstraction use FSMs as the base then add some computing natural high concurrency natural handling of events, exceptions, and the environment tools for understanding stability (e.g markov models, game theory, control theory) composition is separate from creation late bind the callee in a separate step called "composition" 4/2001 TinyOS

18 Macrocomputing Program a large, unstructured collection in aggregate
Single program, multiple data but errors and probabilistic behavior unstructured collection “global” variables that reflect collections need to handle error propagation scatter/gather for collections? online query processing? multi-WEbS abstractions 4/2001 TinyOS

19 Security Individual nodes may be compromised, but hard to get large fraction of nodes. Attacks introduce another form of unreliability in the data. Lightweight encryption/decryption, authentication. Novel protocols to support aggregate operations, eg., broadcast, w/o shared root key Resilient aggregation 4/2001 TinyOS

20 Resilient Aggregators
operate in the face of faulty nodes, intermittent communication, and security attacks ex max is not resilient, nine-tile is. develop algebra of resilient aggregators Random sampling as implementation foundation for security model easy to attack a node hard to attack large fraction of the nodes 4/2001 TinyOS

21 Simulation Large-scale NEST simulator Adversarial simulation mode
very large number of small nodes integrated with event-driven OS design for efficiency checkpointing Adversarial simulation mode Detecting “composition” bugs and scaling bugs Target failure: search for bugs test race conditions automatically pick orders that consume resources more efficient than random-walk testing simulator is an adversary… guided search Hybrid simulator/testbed 4/2001 TinyOS

22 Test-bed Kits in situ programming/upgrade and debugging
synchronized logging (trace extraction) passive monitoring data collection 4/2001 TinyOS

23 Challenge Applications
active markers sequence of applications interactive spaces flock of model cars Multi-agent pursuit-evasion also environmental monitoring stunt ranch “whole canopy ecophysiology” with UCLA obstacles UAVs evader 4/2001 TinyOS

24 Closed-loop at many levels
Within a node behavior adapts to available energy, physical measurements, network condition Across the network discovery and routing, transmission rate and schedule adopting roles, Within the middleware components synchronization, scheduling On the vehicle direction, stability, probabalistic map building Among the vehicles competitive, hidden markov decision processes 4/2001 TinyOS

25 New building blocks for Ubicomp
4/2001 TinyOS

26 New Collaboration Intel Berkeley Lablet Extreme Interconnected Systems (XIS) lab 4/2001 TinyOS


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