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Sensor Network Publication Trend

Sensor Networks, Aeroacoustics, and Signal Processing ICASSP 2004 Tutorial Brian M. Sadler Richard J. Kozick 17 May 2004. Sensor Network Publication Trend. NSF Boost Phase. Source: IEEE Xplore, “sensor networks” (IEEE only).

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Sensor Network Publication Trend

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  1. Sensor Networks, Aeroacoustics,and Signal ProcessingICASSP 2004 TutorialBrian M. SadlerRichard J. Kozick17 May 2004 ICASSP Tutorial

  2. Sensor Network Publication Trend NSF Boost Phase Source: IEEE Xplore, “sensor networks” (IEEE only) ICASSP Tutorial

  3. Sensor Networks, Aeroacoustics,and Signal ProcessingIntl. Conf. on Acoustics,Sensor-Nets, and Signal Proc.Brian M. SadlerRichard J. Kozick17 May 2004 ICASSP Tutorial

  4. CaveatsSP & SP-Comms Perspective, Finite Citations, RMF*AcknowledgementsS. Collier, M. Dong, P. Marshall, S. Misra, T. Moore, R. Moses, T. Pham, N. Shroff, N. Srour, A. Swami, R. Tobin, L. Tong, D. K. Wilson, Q. Zhao, T. Zhou, etc! *rapidly moving field ICASSP Tutorial

  5. Outline • Part 1: Overview of Sensor Networks • Consider the rich interplay between sensing, signal processing, and communications, with a focus on energy preserving strategies. • Part 2: Aeroacoustic Sensor Networks • Application of aeroacoustic sensing with distributed nodes, including propagation effects, and optimal signal processing, under communication constraints. ICASSP Tutorial

  6. Sensor Networks, Aeroacoustics,and Signal ProcessingICASSP 2004 TutorialPart I: Overview of Sensor NetworksBrian M. SadlerRichard J. Kozick17 May 2004 ICASSP Tutorial

  7. Modalities and Applications Application Domains • Point sources • Detection, estimation, geolocation, tracking moving sources • Imaging: sampling a field • Environment (e.g., temperature, atmosphere) • Monitoring: dedicated sensor / source groupings (IEEE 802.15.4 / ZigBee) • Assembly lines, machines, hospital patients, home intrusion • Logistics: where is it?, what condition? • Warehouse, dock, container, on-ship • Mobility & Control • Robotics, UAV’s Sensing Modalities • acoustic, seismic • vibration, tilt • thermal, humidity, barometer • NBC (nuke / bio / chemical) • magnetic, RF • light • high bandwidth (video, IR) • etc! Active sensing • radar, RF tags A range of environments • home, office, factory • toxic, inhospitable, remote • etc! ICASSP Tutorial

  8. Ad hoc networking Sensing / physics / propagation Low power / adaptive hardware Controls, robotics, avionics Rich Multi-Disciplinary Interplay Types of constraints • Energy • battery vs continuous power supply • Wireless communications • 1 or multi-hop to fixed infrastructure vs no fixed infrastructure • homogeneous vs non-homogeneous nodes (“base stations”) • synchronization (beacons, message passing) & geolocation • degree of robustness • highly variable RF propagation conditions • and more • random vs deterministic placement • sensor density ICASSP Tutorial

  9. What is a Sensor Network? • Postulate (something for everyone) • Given any definition of a sensor network, there exists a counter-example. • Extremely varied requirements, environments, comms ranges and propagation conditions, and power constraints. • Our focus • Energy constrained, battery driven, robust radio communications with little or no fixed infrastructure • (other possible comms: acoustic, laser, UV) • DSP / MEMS / Nano & Moore’s Law vs Shannon / Maxwell • Digital Processing Power Requirements Drop by Factor of 1.6/Year • Eb/No Required Remains Constant • Maximum lifetime implies minimal communications ICASSP Tutorial

  10. DIE HARD Mobility and Overhead Ad Hoc Mobile Network Aggregate 200 Mbps Capability • DoD ad hoc network experiment (mobile & high QoS) • Network overhead dominates • Fixed overhead increasingly less efficient as duty cycle decreases 512 byte packet, 32 mcps & FEC = 1/2 @ 4000 kbps maximum burst Headers for each level Timing Status etc From SUO SAS TIM, June 12 & 13 2001 • Does Not Include Initial Acquisition, Other Entry Requests, TCP, Routing Table, and Related Bandwidth Requirements Chip-scale sensor Chip-scale radio Actual Application 1.8 Mbps Data  0.9 % The future? ICASSP Tutorial

  11. Energy Themes • Reduce communications to a minimum • Idle listening & duty cycling • Reduction of protocol overhead • Common channel access limits communications performance • Medium access control (MAC) a critical element • Coordinated signal processing • Collaborative & distributed signal processing vs centralized • Optimality and performance under communications constraints • Specialized low power hardware • DSP, clocks, radios ICASSP Tutorial

  12. Outline • Intro & Energy Themes • Architectures & Connectivity • Some Fundamental Limits • Clocks & Synchronization • Hardware Trends • Node Localization • Medium Access Control & Routing • Conclusions ICASSP Tutorial

  13. Architectures • flat • cluster, hierarchical • mobile collectors • mobile nodes / robotics / UAVs • k-hop to fixed infrastructure (k=1) • the likely dominant commercial paradigm ICASSP Tutorial

  14. Connectivity • Connectivity: multi-hop path exists between all (or desired) nodes • Connectivity is a function of: • Radio channels, power assignment (control), node locations (density), traffic matrix • Model • n total nodes, obey Poisson distribution • geometric path loss • radius r connectivity • What density to ensure connectivity? • Does this scale with area for fixed density? r ICASSP Tutorial

  15. Connectivity • [1970’s - 80’s] “Magic number” = 6(2 to 8 perhaps) • Postulate: connecting with approx 6 neighbors ensures connectivity with very high probability • Under Poisson model with fixed node density, as area grows then there is a finite probability of disconnection • Scaling • Each node should be connected to O(log n) nearest neighbors, so prob(connected)  1. [Philips, et al 1989; Xue Kumar 2004] • Implies a connectivity – capacity tradeoff due to increased multi-user interference • Relation with sensor coverage? • e.g., Nyquist sampling, detection coverage ICASSP Tutorial

  16. Ad Hoc Network Capacity • Define new notion of network capacity [Gupta Kumar 2000] • (aggregate transport capacity, bit-meters / sec) • Comms between random i-j node pairs (peer-to-peer, multi-hop, random planar network) • For n nodes, and W Hz shared channel, at best throughput (bits/sec) for each node scales as • Fundamental limit due to common access • Splitting channel does not change things • e.g., FDMA, base-stations • P-to-P traffic model for sensor nets • the right one? Assumptions • Fully connected • Geolocated nodes • Global routes known • Perfect slot timing & scheduling • Power control • Interference = noise (no multi-user det.) • Arbitrary delay ICASSP Tutorial

  17. Correlated Traffic • Many (most?) sensor network traffic models are highly correlated • Correlation can be exploited with distributed compression (coding) when transmitting to a common destination [Slepian Wolf 1973] • fundamental limit on data reduction • requires known correlation model • Many-to-One Transport Capacity • Even with optimal (Slepian-Wolf) compression assumed, flat architecture with single collector does not scale [Marco, Duarte-Melo, Liu, Neuhoff, 2003] • Leads naturally to routing schemes, e.g., trees, data aggregation • [Scaglione, Servetto, 02, 04] • Development of practical distributed coding schemes continues • e.g., [Pradhan, Kusuma, Ramchandran, 02] ICASSP Tutorial

  18. Mobility brings Diversity • Dramatic gains in capacity limit if mobility is introduced, i.e., network topology is time-varying [Grossglauser Tse 02] • store and forward paradigm, delay finite but arbitrary • throughput can now be , i.e., not decreasing with n • Delay – Capacity tradeoff in mobile ad hoc networks • e.g., mobile network capacity can exceed that of stationary network, even with bounded delay [Lin Shroff 04] • “iid mobility” model • Mobility (time / channel diversity) can greatly increase throughput in random access schemes (e.g., ALOHA), when channel knowledge or multi-packet reception is utilized, e.g., [Tong Naware Venkitasubramaniam 04] ICASSP Tutorial

  19. Time Synchronization • Levels of Timing • (carrier phase, symbol boundary) • data fusion, event detection, state update • MAC: scheduling / duty cycling, TDMA slots • Message frequency vs timing accuracy • exploit piggy-backing, broadcasting • extrapolation possible (forward and backward) • Pairwise vs global synch • e.g., iterative global LS solution • several protocols devised in literature • comms update rates critical • micro-secs accuracies reported experimentally circa 1908 ICASSP Tutorial

  20. Oscillator Accuracy o • Increased network timing accuracy increases lifetime and throughput • With high duty cycling, clock becomes dominant energy consumer • Low power GPS clocks likely to be developed, but … • Beacons must be robust for DoD application ICASSP Tutorial

  21. Clock Drift and Resync Times ICASSP Tutorial

  22. Hardware Trends • Sensing, signal processing, radio • clock, PA, receiver complexity • State transitions • duty cycling: off, idle, SP, listen, communicate • turn-on consumes energy, balance against length of off-time • Performance – energy tradeoffs • dynamic voltage scaling yields variable latency • slow DSP clock to accommodate time allowed for the job • multiple DSP bit-widths, i.e., FLOPS at different quantizations • “domain-specific” DSP suite • Energy harvesting • vibration, solar, thermal ARL “Blue” Radio ICASSP Tutorial

  23. An Energy Model • Coarse energy consumption • receiver energy may dominate • idle listening vs duty cycling & synch on receive • scheduling: multiple listeners vs perfect scheduling • short range desirable, but node density high (application?) • Definition of Network Lifetime? - application & node density dependent • (i) first (or j) node failures • (ii) first (or k) network partitions appear Total will incorporate duty cycles ICASSP Tutorial

  24. Power Amplifier & Efficiency • Power control vs PA efficiency • variable voltage supply to maximize PA use • PAPR an issue with non-constant modulus modulations (OFDM) ICASSP Tutorial

  25. Localization & Calibration Where are my nodes? Location, orientation, & calibration. • Employ internal / external beacons • Deploy beacons within network; GPS limitations & cost • Self-localization – use radio or exploit sensor modality • RF requires sufficient TB product, acoustic / other possible • Mixed modality possible, e.g, rcvd signal strength (RSS) & AOA mix • Fundamental limits: CRB analysis [Garber Moses 2003] • desired sensor connectivity approx 5 • always have residual uncertainty • Relative vs absolute location • Anchored network (e.g., GPS) • Sensor calibration • Temperature, aging ICASSP Tutorial

  26. Medium Access Control (MAC) How do we efficiently share the common medium? • Scheduling & duty cycling to eliminate idle listening (TDMA) • Deterministic (peer-to-peer), perhaps pseudo-random, in clusters • Issues: • scalability • latency vs energy (duty cycle rate) • time variation (new joins, drop outs, channel changes, mobility) • synchronization (clock drift) • broadcasting (mode switch) • Random access (e.g., ALOHA) • Issues: collisions & energy loss, idle listening • Slotted employs scheduling (hybrid: random access & TDMA) • Optimal duty cycle possible • low – energy to find neighbor dominates • high – energy spent listening dominates ICASSP Tutorial

  27. Medium Access Control (MAC) PHY / MAC cross-layer design • Multi-user detection significantly enhances random access performance (2 or 3 users, relatively simple SP), e.g., [Adireddy, Tong, 02] • Dual-channel transceiver • e.g., busy-tones in random access (CSMA-MA) • Further issues: • broadcasting • monitoring, “heartbeat” & synch, maintain connectivity • polling from clusterhead vs event driven • adaptive frame size & heavy-tailed (bursty) traffic ICASSP Tutorial

  28. Medium Access Control (MAC) • MAC typically comes with large range of tunable parameters • Analysis challenging, reliant on simulations & small experiments • Optimality measures? • Scalability? • Markov model for energy consumption, e.g., [Zorzi, Rao, 03] • Optimality depends on variable factors • Applications & traffic models • Node density (perhaps highly varying in same network) • QoS required? (may be time varying, e.g., how & when to ACK?) • Latency required? (see QoS above) Solutions provide various tradeoffs. Provable performance elusive. Adaptability and flexibility important if variety of service desired. ICASSP Tutorial

  29. Sampling & MAC - 1 Consider field reconstruction fidelity under 2 sampling schemes. Random Access Deterministic Scheduling Performance a function of: Poisson sensor distribution sensor density & SNR MAC throughput (finite collection time) = probability no sensor in interval Processing Steps 1 sensor snapshot 2 information retrieval 3 field reconstruction ICASSP Tutorial [Dong, Tong, Sadler, 02, 04]

  30. Sampling & MAC - 2 A Mobile Collection Architecture • Move network functions away from sensors to mobile APs • Network via mobility • Connect only when needed • Design for fraction of packets, from fraction of sensors (no one sensor is critical) ICASSP Tutorial

  31. Sampling & MAC - 3 (1-D) Signal Field Reconstruction • The signal field (Gaussian, Markov) • Poisson sensor field with density • Signal reconstruction via MMSE smoothing • Performance measure: average maximum distortion of reconstruction (pair-wise sensor spacing critical) ICASSP Tutorial

  32. Sampling & MAC - 4 • MAC Assumptions: • Slotted transmission in a collision channel • Fixed collection time: M slots • # of packets collection is a r.v. (1) Random Access (2) Deterministic Scheduling MAC Throughput packets/slot Sensor Outage Probability (no sensor in interval) Schedule one packet per resolution interval of length ICASSP Tutorial

  33. Sampling & MAC - 5 r = distortion ratio of random access to scheduling • Relative performance depends critically on • (scheduling less robust) • Random access may be easier to implement ICASSP Tutorial

  34. Sampling & MAC - 6 Deterministic scheduling random access • If expect # of sensors in interval > , then • scheduled collection is preferred • Or, given sensor density , choice of dictates • appropriate collection regime ICASSP Tutorial

  35. Routing Some rough classes of algorithms • Energy-aware cost • parameters: delay, range, hop count, battery level, etc • heterogeneous nodes with highly variable energy resources • Directed Diffusion: • Query-based, data-dependent routes, controlled flooding (establish “gradients”), e.g., tracking • Clustering algorithms • Supports hierarchical signal processing • Geographically-based (e.g., geographic forwarding) Issues: route discovery, scalability [Santivanez et al 02], global vs local, provably good performance, comms load (energy), mobility ICASSP Tutorial

  36. Odds and Ends • Security, authentication, encryption • Broadcasting • Node management & maintenance • Collaborative transmission • Relay • regenerative and non-regenerative • analog vs digital • Antennas, propagation • Iterative distributed detection & estimation • Tracking ICASSP Tutorial

  37. Conclusions • Its all about energy • Reduce idle listening, new adaptive hardware, accurate & low power clocks • SP, MAC, and Routing are fundamentally interrelated • application dependent, cross-layer design • Large scaling is problematic • Common channel = interference, correlated traffic flows, leads naturally to clustering • Exploit mobility, heterogeneous nodes • No Moore’s Law for batteries (ever?) • Energy harvesting • Local vs global SP tradeoffs • Maximum performance with minimal communications ICASSP Tutorial

  38. Conclusions – Cross-Layer Design • Layered architecture • takes long term view • facilitates parallel engineering, ensures interoperability • lowers cost, leads to wide implementation • “Tension between performance and architecture” [Kawadia Kumar 2003] • cross-layer = tangled spaghetti ? • What architecture for low-energy sensor nets? • limits on performance • optimal layer interaction & feedback • what information is passed? • provable stability needed • widely varying application space OSI Wired World Wireless Sensor-Net World • Multi-antenna • Multi-user detection • Synchronization • Beacons & robust comm • Adapt. modulation & coding • Geolocation • Hierarchical & distr. SP • Mobility • Variable QoS • Routing metric • Non peer-to-peer ICASSP Tutorial

  39. Sensor Networks, Aeroacoustics,and Signal ProcessingICASSP 2004 TutorialEnd of Part I: Overview of Sensor NetworksBrian M. SadlerRichard J. Kozick17 May 2004 ICASSP Tutorial

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