Wireless Sensor Networks Craig Ulmer. Background: Sensor Networks n Array of Sensor Probes (10-1000) n Collect In-Situ Data about Environment n Wireless.

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Presentation transcript:

Wireless Sensor Networks Craig Ulmer

Background: Sensor Networks n Array of Sensor Probes ( ) n Collect In-Situ Data about Environment n Wireless Links –Relay Data –Collaboration

NASA Applications n Primary –In-Situ Data Collection –Precision Landing Guidance –Vehicle Health Sensors n Secondary –Trail Markers –Relay Networks

Motivating Application: Exploration of Mars n Scientific Phenomena: –Thermal Currents –Dust Storms –Seismology n Engineering Challenge: –No GPS –No Communication Infrastructure –Size, Mass, & Power Constraints

Modern Sensor Nodes UC Berkeley: COTS Dust UC Berkeley: Smart Dust UCLA: WINS Rockwell: WINS JPL: Sensor Webs

Node Hardware Embedded Processor Transceiver Memory Sensors Battery Limited Lifetime 8-bit, 10 MHz Slow Computations 1Kbps - 1Mbps, Meters, Lossy Transmissions 128KB-1MB Limited Storage 66% of Total Cost Requires Supervision

Networking n Multi-Hop Routing –Limited Transmission Range n Routing Issues: –Irregular Topologies – Data Transport Aware –Power Aware– Fault Tolerant

Scientific Value n Multiple Data Points: Time and Position n Temporal Synchronization –Hierarchical Schemes n Position Estimation –Digital Ranging –Offline Triangulation d1d1 d2d2 d3d3 

Sensor Network Initialization Deploy Wake/Diagnosis Organize into ClustersRoute

SensorSim n Sensor Network Simulator –How well do Algorithms Perform? –Algorithms as State Machines n Configurable Modules for Flexibility –Simulation at Different Levels n Java Based –Platform Independent

Simulator Node Layers Application Routing Link Sensor Triggers Clustering Algorithms, Reliable Routing Data Fusion Clock Synchronization Medium Access, Commercial Chipsets Node

Example: Election Clustering n Distributed Algorithm n Nodes Elect Leaders, Form Groups n Limited Knowledge Trial Member Trial Leader Member Undecided Join Nearest

Example: Fixed Leader Clustering n Predefined Cluster Leaders n Find Nearest Leader n “Mutiny” if Leader too Far Away Sleep LeaderUndecided Member

Other Simulators n ns –CMU Monarch Extensions for Ad Hoc Wireless –WiNS: Wireless Network Simulator –LEACH/PEGASIS Extensions to WiNS n GloMoSim / UCLA n Opnet

Why Another Simulator? n Previous Sims: LAN-Biased –Assume Thick Layers (802.11,TCP, Telnet) –End-to-End Networking n Sensor Nets: Different Architecture –How Can We Network w/ Minimal Hardware? –Interested in Node Behavior –Adapting Other Sims is Same Job

Ongoing Work: Network Algorithms n Given Clusters, How do we Route? –Limited Route Table Storage –Traffic Often Directed –Loop-Free –Minimal Route Updates n How does Node know Location in Network? –“Identifying ID” Number

Sunrise Synchronization n Use Sunrise as Synchronization Point –Earlier Risers are More Eastern –Smooth with Cluster Values, Neighbor Clusters n Gross Estimate of East-West Dimension

Conclusions n Sensor Networks Valuable Collection Agents n Minimal Hardware, Adapt Algorithms to Match n Use Scientific Observations in Routing n SensorSim Ongoing Work for Analysis