Networks of Tiny Devices embedded in the Physical World David Culler Computer Science Division U.C. Berkeley Intel Research Berkeley

1/17/2002TinyOS CSTB2 Technology Push Complete network embedded systems going microscopic Processing Storage Sensing Actuation Communication LNA mixer PLL baseband filters I  Q  Power

1/17/2002TinyOS CSTB3 Application Pull Complete NW embedded systems going microscopic Huge space of new applications Circulatory Net Habitat Monitoring Condition-based maintenance Disaster Management Ubiquitous computing Monitoring & Managing Spaces

1/17/2002TinyOS CSTB4 Bridging the Technology-Application Gap Power-aware, communication-centric node architecture Tiny Operating System for Range of Highly- Constrained Application-specific environments Network Architecture for vast, self-organized collections Programming Environments for aggregate applications in a noisy world Distributed Middleware Services (time, trigger, routing, allocation) Techniques for Fine-grain distributed control Demonstration Applications

1/17/2002TinyOS CSTB5 A de facto platform for EmNets Developed a series of wireless sensor devices TinyOS concurrency framework Messaging Model Networking stacks (RF and Serial) Multihop routing Several Key components –sensing, logging, data filters, broadcast Simulation tools DARPA NEST OEP

1/17/2002TinyOS CSTB6 Many Research Groups on board UCB –NEST –SensorWeb –Blackout –Glaser structures –CBE –BFD –BRWC UCLA USC Rutgers winlab Intel Bosch Crossbow U Wash Rutgers UIUC NCSA U Virginia Ohio State UCSD Dartmouth MIT Accenture and soon many more

1/17/2002TinyOS CSTB7 A Operating System for Tiny Devices? Traditional approaches –command processing loop (wait request, act, respond) –monolithic event processing –bring full thread/socket posix regime to platform Alternative –provide framework for concurrency and modularity –never poll, never block –interleaving flows, events, energy management => allow appropriate abstractions to emerge

1/17/2002TinyOS CSTB8 Tiny OS Concepts 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 Messaging Component init Power(mode) TX_packet(buf) TX_pack et_done (success ) RX_pack et_done (buffer) Internal State init power(mode) send_msg (addr, type, data) msg_rec(type, data) msg_sen d_done) internal thread Commands Events

1/17/2002TinyOS CSTB9 Application = Graph of Components RFM Radio byte Radio Packet UART Serial Packet ADC Tempphoto Active Messages clocks bit byte packet Route map routersensor appln application HW SW Example: ad hoc, multi-hop routing of photo sensor readings 3450 B code 226 B data Graph of cooperating state machines on shared stack

1/17/2002TinyOS CSTB10 Demonstration applications 29 Palms Cory Hall network –½ million packets over 3 weeks Surge network and environment display 800 node ad hoc network CBE Glaser Shakes Granlibakken retreat watcher Robomote => continued application focus more real and long lived more dynamics extract architecture and create framework

1/17/2002TinyOS CSTB11 Example TinyOS study UAV drops 10 nodes along road, –hot-water pipe insulation for package Nodes self-configure into linear network Synchronize (to 1/32 s) 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! While servicing the radio in SW every 50 us!

1/17/2002TinyOS CSTB12 Structural performance due to multi-directional ground motions (Glaser & CalTech). Wiring for traditional structural instrumentation + truckload of equipment Mote infrastructure ` 5` Mote Layout Comparison of Results

1/17/2002TinyOS CSTB13 Cory Energy Monitoring/Mgmt System 50 nodes on 4 th floor 5 level ad hoc net 30 sec sampling 250K samples to database over 6 weeks

1/17/2002TinyOS CSTB14 Energy Monitoring Network Arch sensor net GW control net GW 20-ton chiller PC scada term modbus UCB power monitor net PC telegraph MYSQL Browser

1/17/2002TinyOS CSTB15 Wealth of Research Challenges Large numbers of highly constrained (energy & capability), connected devices –able to be casually deployed in infrastructure (existing or in design) –imperfect operation and reliability –operating in aggregate New family of issues across all the layers application service network system architecture technology mgmt / diag / debug algorithm / theory prog / data model

1/17/2002TinyOS CSTB16 Example: Networking Hands-on Experience with Large Networks of Tiny Network sensors  intense constraints, freedom of abstraction Re-explore entire range of networking issues –encoding, framing, error handling –media access control, transmission rate control –discovery, multihop routing –broadcast, multicast, aggregation –active network capsule (reprogramming) –localization, time synchronization –security, network-wide protection –density independent wake-up and proximity est. Fundamentally new aspects in each

1/17/2002TinyOS CSTB17 Simple Epidemic Algorithm Schema One (multicast) message handler if (new mcast) then take local action retransmit modified request Examples: Network wakeup, command propagation –Build spanning tree »record parent Naturally adapts to available connectivity Minimal state and protocol overhead => surprising complexity in this simple mechanism

1/17/2002TinyOS CSTB18 Network Discovery: Radio Cells

1/17/2002TinyOS CSTB19 Network Discovery

1/17/2002TinyOS CSTB20 Controlled Empirical Study Experimental Setup –13x13 grid of nodes –separation 2ft –flat open surface –Identical length antennas, pointing vertically upwards. –Fresh batteries on all nodes –Identical orientation of all nodes –The region was clean of external noise sources. Range of signal strength settings Log many runs

1/17/2002TinyOS CSTB21 Example “epidemic” tree formation

1/17/2002TinyOS CSTB22 Final Tree

1/17/2002TinyOS CSTB23 Power Laws ? Most nodes have very small degree (ave =.92) Some have degree = 15% of the population Few large clusters account for most of the edges

1/17/2002TinyOS CSTB24 Open Territory => Many Children Example: Level 1

1/17/2002TinyOS CSTB25 Open Territory => Many Children Example: Level 2 – variation in distance

1/17/2002TinyOS CSTB26 Open Territory => Many Children Example: Level 3 – long links

1/17/2002TinyOS CSTB27 Understanding Connectivity 16 transmit power settings For each transmit power setting, each node transmits 20 packets. Receivers log successfully received packets. Nodes transmit one after the other in a token-ring fashion No collisions. Contour plot show probability of reception from center node Define “range” a radius where 75% of enclosed nodes receive 75% of packets Often good nodes at a distance

1/17/2002TinyOS CSTB28 Link symmetry in open environment Asymmetric Link: Greater than 65% successful reception in one direction and less than 25% successful reception in the other direction Symmetric Link: Greater than 65% successful reception in both directions others are “bad” links A -> B B -> A Frequency

1/17/2002TinyOS CSTB29 Importance of Asymmetric Links 10%-25% asymmetric links. Many asymmetric links are long links –|| asymmetric long links|| ~ || symmetric long links || Why are long links useful? –Beacon-based Routing: Long links can be used to build low-depth routing trees –Diffusion: short routing paths Protocol design –When to confirm bidirectionality?

1/17/2002TinyOS CSTB30 Collisions are primary factor Nodes out of range may have overlapping cells –hidden terminal effect Collisions => these nodes hear neither parent and become stragglers As the tree propagates –folds back on itself –rebounds from the edge –picking up these stragglers. This effect was seen in many experiments

1/17/2002TinyOS CSTB31 Stragglers significant fraction of links point ‘backwards’

1/17/2002TinyOS CSTB32 Key Experience Really good at building tinyOS subsystems –non-blocking, split-phase event structures Internalized the “state of constant change” paradigm –ex: maintain routing tree by constantly rebuilding it –soft state that is always suspect –simple one-way protocols Operating in the aggregate Simple mechanisms to accomplish large goals –MAC, ATC Out of the box on networking abstractions –Low-power listen, wake-up, statistical sampling, weighted aggregation Understanding of large scale dynamics

1/17/2002TinyOS CSTB33 Rich set of additional challenges Efficient and robust security primitives Application specific virtual machines Time & space information in every packet Density independent wake-up, aggregation –sensor => can use radio in ‘analog’ mode Resilient aggregators Programming support for systems of generalized state machines Programming the unstructured aggregate –SPMD, Data Parallel, Query Processing, Tuples Understanding how an extreme system is behaving and what is its envelope –adversarial simulation Self-configuring, self-correcting systems

1/17/2002TinyOS CSTB34 The “Law of Miniaturization” Each major generation is increasingly smaller, more deeply interactive, arrives when previous is at its strength Vast majority of computing will be small, embedded, devices connected to the physical world –actually the case today, but –not connected to us, the web, or each other Time Integration Log R Mainframe 99 Innovation Minicomputer Personal Computer Workstation Server