Time Synchronization for Wireless Sensor Networks Proposal for Ph.D. Thesis University of California, Los Angeles Department of Computer Science April 10, 2001 Jeremy Elson

wireless sensor networks Environmental Monitoring New technologies have reduced the cost, size, and power of micro-sensors and wireless interfaces. Systems can Sense phenomena at close range Embedded into environment These systems will revolutionize Environmental monitoring Disaster scenarios Fantastic Voyage? Circulatory Net

new challenges Energy constraints imposed by unattended systems. Scaling challenges due to very large numbers of sensors. Level of dynamics: Environmental: obstacles, weather, terrain, etc. System: large number of nodes, failures.

Part I: Defining the Problem

time synchronization Time sync is critical at many layers

time synchronization Time sync is critical at many layers Beam-forming, localization, distributed DSP

time synchronization Time sync is critical at many layers Beam-forming, localization, distributed DSP Data aggregation & caching t=1 t=0 t=2 t=3

time synchronization Time sync is critical at many layers Beam-forming, localization, distributed DSP Data aggregation & caching TDMA guard bands Radio On Radio Off Sender Radio Off Receiver Guard band due to clock skew; receiver can’t predict exactly when packet will arrive Time

time synchronization Time sync is critical at many layers Beam-forming, localization, distributed DSP Data aggregation & caching TDMA guard bands Clock sync for TDMA is more important in sensor nets, compared to traditional nets: Listening is EXPENSIVE Infrequent data means infrequent sync Small data means guard band is relatively big

time synchronization Time sync is critical at many layers Beam-forming, localization, distributed DSP Data aggregation & caching TDMA guard bands “Traditional” uses (debugging, user interaction, certain crypto algorithms, database consistency, etc.)

time synchronization Time sync is critical at many layers Beam-forming, localization, distributed DSP Data aggregation & caching TDMA guard bands “Traditional” uses (debugging, user interaction…) But time sync needs are non-uniform Maximum Error Lifetime Scope & Availability Efficiency (use of power and time) Cost and form factor

related work Clock sync over computer networks Protocols: NTP, Berkeley, Cristian’s probabilistic alg Stable frequency standards Cesium, Rubidium, temperature-controlled… National time standards USNO’s time, UTC/TAI Two-way satellite time transfer, GPS Virtual clocks (Lamport)

what’s wrong with what’s there? Existing work is a critical building block BUT... Energy e.g., we can’t always be listening or using CPU! Wide range of requirements within a single app; no method optimal on all axes Cost and form factor: can disposable motes have GPS receivers, expensive oscillators? Completely changes the economics…

our approach Use multiple modes Use tiered architectures Extend existing sync methods Develop new methods, and compositions of methods Characterize these methods Use tiered architectures Not a single hardware platform but a range of hardware Analogy: memory hierarchy The set as a whole can (?) be necessary and sufficient, to minimize resource waste Don’t spend energy to get better sync than app needs

a palette of sync methods Goal: make the set rich enough to minimize waste Time Sync Parameter Space: (max error, lifetime, scope, etc.) Available Sync Methods Better Application Requirement Better

a palette of sync methods Goal: make the set rich enough to minimize waste Time Sync Parameter Space: (max error, lifetime, scope, etc.) Ideally, methods should be tunable Better Application Requirement Better

Part II: Initial Experimentation

post-facto sync Basic idea: A set of receivers is waiting for an event Locally timestamp an event when it happens After the fact, reconcile clocks Allows us to avoid wasting energy on sync when it is not needed Train clocks with NTP; beacon after event NTP is good at correcting frequency A local “pulse” is good at correcting phase How well does the combination work?

expected error sources Clock skew We hope to reduce this with NTP; BUT Temperature variations likely in sensor nets Nondeterministic delays on receivers Not considering senders to be synced helps! Propagation delay Using RF to sync works if we’re measuring sound, not if we’re measuring RF

an initial experiment Create a (wired) stimulus sent to 10 nodes… We know it arrives at each node simultaneously With how much error can we timestamp it? (All timestamps should be the same) Four methods: NTP alone Sync pulse alone Pulse + active NTP Pulse + disconnected NTP

the experiment says…? Sync pulse much better than NTP: 100usec vs. 1usec (clock resolution=1usec) At the cost of a localized timebase Pulse+NTP=10x better than either alone Multi-modal solutions are good! Important: We do as well when we train NTP first, then cut off its time source No time source needed = no radio listening = much lower energy expenditure

Part III: Thesis Plan

future work: 1 Repeat experiment in wireless context Test determinism of different ways of sending the pulse (radios, light?) Multi-hop sync: pulse chaining Characterize - error vs. distance analogous to our current “error vs. time” Better understand limitations and uses of existing methods (NTP, GPS, etc.)

future work: 2 Testbed for object tracking In cooperation with Girod: acoustic ranging Uses time sync in two ways: Each localization point requires sync Integration of points over time requires sync Implement “synched msg” primitive using beacons

future work: 3 Work in simulation (somewhat less well defined) Explore aspects of sync without “burden” of real implementations: Scaling Adaptive fidelity Automatic mode selection Certain “tuning knobs”

that’s all, folks! Thank you!