Wireless Sensor Network (WSN) CS526 Advanced Internet and Web

Wireless Sensor Network (WSN) CS526 Advanced Internet and Web Systems C. Edward Chow 03/17/23 cs526 WSN 1

Wireless Sensors Low-power microscopic sensors with wireless communication capability Miniaturization of computer hardware Intelligence Micro Electro-Mechanical Structures (MEMS) Sensing Low-cost CMOS-based RF Radios Wireless Communications 03/17/23 cs526 WSN 2

Wireless Sensor Networks(WSN) Even though wireless sensors has limited resources in memory, computation power, bandwidth, and energy. With small physical size Can be embedded in the physical environment. Support powerful service in aggregated form (interacting/collaborating among nodes) Self-organizing multi-hop ad-doc networks Pervasive computing/sensoring 03/17/23 cs526 WSN 3

WSN Applications Wide area monitoring tools supporting Scientific Research – Wild life Habitat monitoring projects Great Duck Island (UCB), James Reserve (UCLA), ZebraNet (Princeton. – Building/Infrastructure structure study (Earthquake impact) Military Applications – Shooter Localization – Perimeter Defense (Oil pipeline protection) – Insurgent Activity Monitoring (MicroRadar) Commercial Applications – Light/temperature control – Precision agriculture (optimize watering schedule) – Asset management (tracking freight movement/storage) 03/17/23 cs526 WSN 4

Senor Network/Great Duck Island 2003 03/17/23 cs526 WSN 5

Vanderbuilt’s Shooter Localization 03/17/23 cs526 WSN 6

Related Info Alec Woo’s dissertation (Chapters 1-2) http://www.cs.berkeley.edu/ awoo/thesis.pdf Networking of Sensor System (NOSS) workshop presentations CACM WSN special issue, Vol. 47, Issue 6, June 2004. (this url required uccs vpn access) – The platforms enabling wireless sensor netwo rks , by Jason Hill et al. 03/17/23 cs526 WSN 7

What is a mote? Imote2 06 with enalab camera mote noun [C] LITERARY something, especially a bit of dust, that is so small it is almost impossible to see ---Cambridge Advanced Learner’s Dictionary http://dictionary.cambridge.org/define.asp?key 52014&dic t CALD Evolution of Sensor Hardware Platform (Berkeley), [Alec Woo 2004] 03/17/23 cs526 WSN 8

Mica2 Wireless Sensors CACM June 2004 pp. 43. MTS310 Sensor Boards Acceleration, Magnetic, Light, Temperature, Acoustic, Sounder New MicaZ follows IEEE 802.15.4 Zigbee standard with direct sequence sprad spectrum radio and 256kbps data rate 03/17/23 cs526 WSN Adapted from Crossbow web site 9

Wireless Sensor Network Stargate 802.11a/b Ethernet Mica2 PCMCIA Compactflas h USB JTAG RS232 03/17/23 cs526 WSN 10

Motes and TinyOS Motes (Mica2, Mica2dot, MicaZ) – Worked well with existing curriculum ATMega128L microcontroller 128KB program flash; 512KB measurement Flash; 4KB EEPROM – Standard platform with built-in radio chicon1000 (433MHz, 916MHz, 2.4GHz) 38.4kb; 256kbps for MicaZ IEEE 802.15.4. (1000ft, 500ft; 90/300ft) range – AA battery – Existing TinyOS code base – Convenient form factor for adding sensors TinyOS – Event-based style helped students understand: Time constraints Code structure (need to write short non-blocking routines) – Existing modular code base saved time 03/17/23 Made a more complex project possible Provided a degree of abstraction cs526 WSN 11

Comparison of Energy Sources 03/17/23 cs526 WSN Source: UC Berkeley 12

Communication/Computation Technology Projection Source: ISI & DARPA PAC/C Program 03/17/23 cs526 WSN 13

Energy Management Issues Actuation energy is the highest – Strategy: ultra-low-power “sentinel” nodes Wake-up or command movement of mobile nodes Communication energy is the next important issue – Strategy: energy-aware data communication Adapt the instantaneous performance to meet the timing and error rate constraints, while minimizing energy/bit Processor and sensor energy usually less important 03/17/23 cs526 WSN 14

Wireless Sensor Network(WSN) vs. Mobile Ad Hoc Network (MANET) WSN MANET Similarity Wireless Multi-hop networking Security Symmetric Key Cryptography Public Key Cryptography Routing Support specialized traffic pattern. Cannot afford to have too many node states and packet overhead Support any node pairs Some source routing and distance vector protocol incur heavy control traffic Resource Tighter resources (power, processor speed, bandwidth) Not as tight. 03/17/23 cs526 WSN 15

Unusual WSN Link Characteristics Packet Success Rate Contour Open Tennis Court with 150 motes 03/17/23 cs526 WSN 16

Challenges in Self-organizing Multihop Ad-doc Networks Problems has been studied in packet radio network and mobile computing. However in sensor networks, it is unique in: – Lossy short-range wireless ratio Need more cross-layer interaction – Tight resource constraints – Traffic pattern differences – In-Network Processing 03/17/23 cs526 WSN 17

Cluster /Sink Tree Formation IX VIII V IX L9 VIII V L9 L7 VII L7 VII L8 L8 VI VI L5 L6 L5 L6 L10 X L10 X G II C G III B II L4 H II I C L4 H I D L1 A B L2 L3 Cluster Formation Phase IV D L1 I A L2 L3 IV Sink Tree Formation Phase Node with Double Circle: Sink Node Node with Single Circle: Chosen Cluster Leader Red Arcs forms the sink tree Should there be direct link between leaders? (Wendi Heinzelman) 03/17/23 cs526 WSN 18

SNATool: Sensor Network Analysis Tool 03/17/23 cs526 WSN 19

Cluster/Sink Tree Formation Problems How to make cluster size more even? All leaders will consume power evenly. How to form a sink tree with smallest link distance? shorter link less radio power How to avoid frequent cluster/sink tree formation? avoid disrupt normal data collection traffic How to perform tracking responsively? How to extend the life time of WSN? These are conflict requirements. How to resolve it? 03/17/23 cs526 WSN 20

Common system services Localization & Time Synchronization Calibration In Network Processing Programming Model Routing and Transport Event Detection Needed: Reusable, Modular, Flexible, Well-characterized Services/Tools Routing and Reliable transport Time synchronization, Localization, Calibration, Energy Harvesting In Network Storage, Processing (compression, triggering), Tasking Programming abstractions, tools Development, simulation, testing, debugging 03/17/23 cs526 WSN 21

WSN Architecture David Culler, Scott Shenker, Ion Stoica, UC Berkely. Creating an Architecture for Wireless Sensor Networks –in a nutshell. 03/17/23 cs526 WSN 22

Key Properties Networks meaningfully distributed over physical space Large numbers of nodes Long duration Irregular, varying connectivity Variations in density Loss & interference Constrained resources & Energy Connected to deeper infrastructure 03/17/23 cs526 WSN 23

So how do we go about it? 03/17/23 cs526 WSN 24

Wirelss Sensor Network and Pervasive Computing D.Raychaudhuri, Rutgers WINLAB. Research Challenges in Sensor Nets and Pervasive Systems. Including a presentation on writing effective grant proposals. 03/17/23 cs526 WSN 25

Mobile Sensor Networks William J Kaiser, UCLA CENS. On Constrained Actuation for Sensor Networks. Challenges – Sustainability Solutions in Constrained Actuation and Infrastructure – Limited dimension, limited range mobility – Infrastructure-supported mobility New Research Area – – – – 03/17/23 Adaptive sampling and deployment Coordinated mobile embedded sensors Adaptation of network resources Active Fusion cs526 WSN 26

Networked Infomechanical Systems (NIMS) Networked mobile nodes – Sensing – Sampling – Energy logistics – Communication Infrastructure – Deterministic and precise motion – 3-D volume access – Mass transport at low energy System Ecology for Sustainability – Fixed nodes – Mobile nodes – Infrastructure 03/17/23 cs526 WSN 27

System Ecology : Introduces New Design Rules Tiers Sensing Accuracy Energy Efficiency Mobile Nodes Adaptive Topology and Perspective Low Energy Transport/ Comm Connected Fixed Nodes Optimal, Precise Deployment Energy Production and Delivery Optimized Location in 3-D Continuous, In Situ SensingSampling Untethered Fixed Nodes Localized Sensing and Sampling Alert and Guide Mobile Assets Access to NonNavigable Areas Continuous Low Energy Vigilance 03/17/23 cs526 WSN Spatial Coverage Temporal Coverage Both Sensing Enable Long and Term Sampling in Sustainability 3-D 28

Security and Privacy in Sensor Networks: Research Challenges Radha Poovendran, U. Washington. Resource constrains on WSN devices. Energy, computation, memory 03/17/23 cs526 WSN 29

WSN Education Waylon Brunette, U. Washington. The Flock project. 03/17/23 cs526 WSN 30