Tiny Networking

1. Tiny Networking David Culler University of California, Berkeley Intel Research Berkeley http://webs.cs.berkeley.edu

2. Vast Networks of Tiny Devices • Past 25 years of internet technology built up around powerful dedicated devices that are carefully configured and very stable • local high-power wireless subnets at the edges • 1-1 communication between named computers • Here, ... • every little node is potentially a router • work together in application specific ways • collections of data defined by attributes • connectivity is highly variable • must self-organize to manage topology, routing, etc • and for power savings, radios may be off 99% of the time NEC Networking

3. Directed Diffusion Concept • Nodes express ‘interest’ in data with certain attributes (sinks) • Establishes gradient from sources Estrin, Govindan, Heideman NEC Networking

4. Directed Diffusion Concept • Nodes express ‘interest’ in data with certain attributes (sinks) • Establishes gradient from sources • Sources generate data • Useful paths reinforced, others suppressed • in-network aggregation • nested queries NEC Networking

5. Huge Design Space: Application • Traffic • any-to-any, all-to-one, one-to-all, collection of sub-groups, ... • steady low-BW steam of readings/findings, bursts of data, periodic logs, ... • Duration • years (hazard alarm), months (field season), when the big red button is pressed • Available infrastructure • power, base-stations, location • Mobility, Stationary • all fixed, all mobile, mixture, changing environment • Placement / Physical Topology / Scale • arbitrary, controlled, unknown • Network Services • time synchronization, localization, proximity, ... => Best way to get a networking solution now is to define your application context NEC Networking

6. Design Space: Underlying Technology • Link (Radio) Technology • range, control of signal strength, noise tolerance • channel capacity, coding, error rates • single channel, multi-channel, tunable • Device Density, Failures over time • MAC (media access control) • channel sensing, back-off, protocols, collision behavior, link-level acks • time synch, energy aware • Power management & Energy Constraints • scheduling, functional allocation • Transmission Rate Control • Topology Formation • hierarchical spine, geographic, static, dynamic • Routing • single path, multipath, passive participation • explicit vs implicit nbhd detection NEC Networking

7. Losing the forest for the trees • Systems side • clever fix to one particular aspect, but only looking at it in sliver of the design space • Theory side • assuming cell coverage is a disk of radius r with sharp boundary • within radius Pconnect = 1, outside Pconnect = 0 • eg., unit disk-graphs for routing, maximal independent sets, min. dominating sets, leader election • Wireless communication between small devices is inherently noisy, unpredictable, & non-deterministic • Radio signal fades with distance • Interference • Multipath (reflections) • Collisions • Mobility or not NEC Networking

8. Surge Demo NEC Networking

9. Local Operations => Global Behavior • Nodes ‘sense’ network environment • uncertain, partial information • Packets directed to a “parent” neighbor • all other neighbors “hear” too • carry additional organizational information • Each nodes builds estimate of neighborhood • adjusted with every packet and with time • Interactively selects parent • Routes traffic upward • Collectively they build and maintain a stable spanning tree • takes energy to maintain structure Predictable global behavior built from local operations on uncertain data NEC Networking

10. Wireless “Connectivity” • Controlled study on 13x13 array of Rene nodes • Single transmitter • Record fraction of packets received at each node • Many packets at each of several transmit power levels • complex fall-off over substantial range • ‘range’ defined by CEP Contours of probability of reception from center node for range of transmit power strengths with Ganesan, Woo, Krishnamacheti, Estrin NEC Networking

11. Alternative Perspective • Develop algorithms that are built fundamentally upon a probabilistic connectivity structure • Embrace noise, rather than fight it • the network is really another sensor (and actuator) • Utilize simple, local rules, rather than complex protocols • Challenge: obtain predictable global behavior • Challenge: interfaces for imperfect operation NEC Networking

12. Simple Epidemic Broadcast Schema Local Rule: if (new mcast) then take local action retransmit modified request • Should forms roughly breadth-first spanning tree • 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 NEC Networking

13. Network Discovery: Radio Cells NEC Networking

14. Network Discovery NEC Networking

15. Behavior at Scale • Variations in connectivity • With many nodes, likely that one far away will hear • Long links tend to be asymmetric • Structure dominated by contention NEC Networking

16. Final Tree NEC Networking

17. 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 NEC Networking

18. Open Territory => Many Children • Example: Level 1 NEC Networking

19. Open Territory => Many Children • Example: Level 2 – variation in distance NEC Networking

20. Open Territory => Many Children • Example: Level 3 – long links NEC Networking

21. Importance of Asymmetric Links • Asymmetric Link: • >65% successful reception in one direction • <25% successful reception in the other direction • 10%-25% of links are asymmetric • Many long links are asymmetric • in large field it is likely that someone far away can hear you • what does this mean for protocol design? NEC Networking

22. Collisions are primary factor • Nodes out of range may have overlapping cells • hidden terminal effect • Collisions => these nodes hear neither ‘parent’ • become stragglers • As the tree propagates • folds back on itself • rebounds from the edge • picking up these stragglers. • Seen in many experiments • Mathematically complex because behavior is not independent beyond singe cell NEC Networking

23. Probabilistic Connectivity Model • Radio signal fades with distance in complex manner depending on environment • Radio receiver has complex behavior to extract signal • What matters to algorithms is whether packets are delivered or not • work directly with probabilistic communication model • but which one? • Calculate comm. rates for numerous transmit/receive pairs at range of distances NEC Networking

24. Fall-off of Probability of Comm. Low Power High Power NEC Networking

25. silent transition clear Drive Simulation from Empirical Stochastic behavior NEC Networking

26. Example Cell Coverage from Model feet feet NEC Networking

27. Reception Model with Collisions • Second experiment with two nodes sending at once, record which nodes hear which one • follows P success closely • When does a second sender collide? • Clear comm. region => YES • silent region => NO • transition region => collides if would have communicated • Reception Model • Assume pij is the probability of success (i->j), Probability for B to receive A’s message = pab* i=collider(1-pib) NEC Networking

28. Common Special Case: Data Gathering • Collection of nodes take periodic samples • Stream data towards a root node • Root announces interest • depth = 0 • Nodes listen to neighbors • When hear neighbor with smaller depth • start transmitting data to good neighbor with smallest depth • set own depth to one greater and include with data • Data transmission continuously reinforces / adjusts routes NEC Networking

29. Use Case Assumptions • Application • N-to-1 all data, no aggregation • Each node generates small packets at regular interval • Appln phase shift on collision • Routed to a specific node, e.g, base station or root of request • data rate below saturation • 7x7 grid, 10 ft spacing => several hops • Underlying • link-level acknowledgement (may be used for retransmission) • CSMA with simple channel sensing, fixed backoff, initial random delay • Receivers always attentive • may use sampled listening • Broadcast: choose parent = first contact • Shortest Path: choose parent = closer (which one) • Min path loss: choose parent = next step on min loss path NEC Networking

30. P=0.86 95 65 95 70 60 95 99 Max-Path-Reliability routing • each node maintains estimate of loss rate over entire path to root • select nbr on the minimum loss path as parent • Pi[to root] through j = P[link i,j] * Pj[to root] • assuming loss rate along path is independent of how packets enter the path • Subtleties • estimating link rates • transient error in link rate may lead to cycles • rate of updates • stability vs responsiveness • congestion • warm-up phase NEC Networking

31. Broadcast • overall success rate: 18.9% NEC Networking

32. SP50 Path reliability • overall success rate: 44.8% NEC Networking

33. MPR path reliability • overall success rate: 54.7% NEC Networking

34. Routing Distance Distribution SD50 MPR NEC Networking

35. Distribution of success rates MPR SP50 NEC Networking

36. Observations • Better success rate with more, better hops • Partial information causes temporary loss • cycles introduced when link error estimates are poor • tracks std. dev. of link error rates • if difference between candidates not statistically significant, choose based on hop count • especially important during warm-up phase • also after topology changes • Shortest Path will tend to use most marginal neighbors • although range is highly variable, for particular pairs of nodes at particular distances connectivity is very bimodal NEC Networking

37. SP75 Path Reliability • overall success rate: 52.7% (vs 54.7% for MPR) NEC Networking

38. Multihop Path-Rate Contours Min Hop (75% nbr) Min Path Loss NEC Networking

39. Hop-by-hop retransmission • Decent neighbors become good neighbors if you are willing to chat for a moment • may choose parent that is on “path of least transmissions” • expected number of transmissions = 1 / P(success) • Distributed computation is estimate of SUM of retransmissions • A few retransmissions make large difference in success rate NEC Networking

40. Overall Results NEC Networking

41. Fairness SP75 MRP Broadcast NEC Networking

42. Stability • How often does the routing algorithm change? • # of parent changes per unit time MRP SP75 NEC Networking

43. Stability (Broadcast) NEC Networking

44. Key Building Block: Link estimator • Nodes assess quality of link from packets they hear • directed to them or snoop • sequence number => infer losses between packets • For each new packet (or empty window) revise estimate of link probability • classic EWMA • P i+1 = aP i + (1-a) X i , where X i = 0,1 if loss, success NEC Networking

45. Link Probability Changes Dynamically NEC Networking

46. Revisit Classic Estimator • Want estimator that is responsive to change, but stable with low error • Candidates • EWMA stable, agile, flip-flop • Moving Average • ... • Best ended up being the own that we eyeballed • EWMA cascaded with average over a time window NEC Networking

47. Estimator driven from prob. generator NEC Networking

48. Empirical Trace NEC Networking

49. Bottom Line • Can only estimate link rate to within ~10% • Takes about 100 packets to settle • Design distributed algorithms with this kind of approximation of an inherently noisy world NEC Networking

50. So how about that demo? NEC Networking