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ENVIRONMENTAL MONITORING: FROM SENSORS TO DATABASE Jerry Yang
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Overview Design Requirement System Framework Wireless Sensor Networks Communications Protocols Data Interpolating Energy Harvesting Over-the-Air Programming Telecommunication system Single Board Computer GPRS modem Networking sensors, data loggers and data servers Database and Client Interfaces Database Data Visualization Conclusion and Future Work
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Project Object Design and implement a fully functional environmental monitoring system Collect and report temporal and spatial soil moisture data with required accuracy Provide near-real-time data about monitored variables to the public Monolithic weather stations Wired Sensors (Data loggers) limited Spatial Coverage Field Study Data is acquired every month
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Go Wireless Wireless Sensors could fulfill this mission Unprecedented temporal and spatial granularities Near-real-time data is accessible via the Internet Besides… Robust and accurate through dense deployment Minimize disturbance to the monitored site Cover larger area (Multihop) Low installation cost Ease of deployment and relocation
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System Architecture Database Server Internet Client Data Browsing and Processing Data loggers In the Field: Download Data In the Lab: Upload Data
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System Architecture Database Server Internet Client Data Browsing and Processing Base Station Node Wireless Sensor Nodes GPRS Modem Gateway (Single Board Computer) GPRS Link Data loggers
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An introduction to WSNs A wireless sensor mote is a battery-operated embedded system including various hardware and software components. For MicaZ motes: Processing Unit 7.37MHz micro-controller 4KB RAM 512KB Flash Sensors 16-bit ADC with MDA 300 Data Acquisition Board EC-5 Soil Moisture Sensors Transceiver 2.4 GHz, IEEE 802.15.4 compliant, 250 kbps Powered by 2 AA batteries
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Constraints of Sensor Motes Limited processing, storage and communication capabilities 100 nodes @250bps = 25kbps (data sampled every second) WILL be solved in the near future year Streaming Data to/from the Physical World
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Fundamental Problem Sensor network is un-tethered, and will be operating for a long time. Replacing batteries is difficult and expensive if not impossible For MicaZ, typical current drawing is 30mA. Powered by 2.4V 3000mAh Batteries, a MicaZ mote could run for 100 hours continuously. Communicating 1 bit data over the wireless medium consumes far more energy than processing it. Operating Current (mA)MicaZ ATMega128L, full operation12 (7.37 MHz) ATMega128L, sleep0.010 Radio, receive19.7 Radio, transmit (0dBm)17 Radio, sleep0.001
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Software Support TinyOS and NesC An open-source operating system designed for wireless embedded sensor networks Component-based architecture which enables rapid innovation and implementation while minimizing code size Event-driven execution model
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Communication Protocols Design requirement Energy Efficient Radio communication is the most expensive operation in terms of energy usage Robust, scalable and adaptive Dynamic topology changes due to unstable links, node failures and network disconnections Unique characteristics of our project Long-term operation with very low data rate A single sink node At most of the time, data flow is uni-directional Layered Architecture Physical/Link Layer Medium Access Control Routing
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Physical/Link Layer Radio Propagation Path Loss - signal strength attenuates as distance to a constant exponent However, radio connectivity is not a simple disk Shadowing (due to obstructions) and Multipath Fading Wireless Channel Characteristics Great spatial variability Non-isotropic propagation Asymmetric links are common due to hardware calibration
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Link Quality Over Space Packet reception over distance has a heavy tail. There is a non-zero probability of receiving packets at distances much greater than the average cell range 169 motes, 13x13 grid, 2 ft spacing, open area, RFM radio, simple CSMA
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Medium Access Control MAC protocol decides when and how nodes access the shared wireless channel Collision avoidance Duty-cycle control MAC layer protocols directly controls radio activities, significantly affect the overall node lifetime MAC in Wireless Networks Contention-based protocols CSMA/CA – node compete for a single channel On-demand allocation provides more flexibility and adaptivity Scheduled protocols C/T/FDMA – divide wireless channel into different sub-channels Collision-free and energy-efficient
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MAC for Sensors Sources of energy waste in radio communication Idle listening Costs as much power as transmitting or receiving dominant factor of energy consumption especially in low data rate systems Collision – retransmit when packets collide Build on CSMA but also adopt TDMA-like sleep/wakeup duty cycle S-MAC, T-MAC, B-MAC, Z-MAC Reduce idle listen and minimize collision Improve power efficiency while retaining flexibility Sacrifice throughput, increase latency
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MAC Protocol Design Parent…SyncSleepRcv 1Rcv2SleepTransmitSleep Child 1…SyncSleepTransmitSleep Child 2…SyncSleepTransmitSleep We implement a tree-structure data report hierarchy, rooted at the sink node A global clock is also maintained by time synchronization All nodes begin with a Sync slot Synchronize time, manage neighbor list, select parent Parent nodes then allocate time slots for their children All nodes are awake, but only broadcasting very short control packets A node will report its latest readings to its parent in transmit slot, while the parent node will become active and listen to the channel Nodes sleep for the rest of time
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Network Layer - Routing Establishing and maintain the multi-hop routing hierarchy Link Quality Estimation Neighbor Management Discover, update, remove neighboring nodes Parent selection Shortest Path, Minimal Transmission, Geo-Routing, Energy-Aware routing
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Link Quality Versus Distance
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Time Synchronization Why do we need network-wise clock? Time stamp data samples Set up radio schedule TOA, TDOA in Localization Pair-wise Synchronization Estimate communication delays Send time, access time, propagation time, receive time, etc. Estimate clock skew Perform linear regression on past local/global time pairs Multihop Synchronization Minimize control overhead
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Application Layer Energy Efficient Map Interpolation for Sensor Fields using Kriging (E2K) an energy efficient and error bounded framework for interpolating maps from sensor fields Environmental dynamics, such as temperature and soil moisture, are continuous Should be represented as a continuous surface over the sensor fields through interpolating Spatial and temporal autocorrelation could be utilized to reduce sample points
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Data Interpolating
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Localization Knowing the exact location where information was collected is critical A reading is represented by vectors (x,y,t,v) Self-localization vs Tracking Ranging Methods Radio, acoustic/ultrasound, laser, etc. RSS, TOA, TDOA Lateration and Triangulation
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Solar Harvesting Sub-System Energy Storage Module Ultra Capacitors and Rechargeable Batteries Choosing Batteries NiMH, NiCd, Li-ion Solar Harvesting Module Solar Cells Regulators and Switches Circuit Design Smart Battery Monitoring Energy-Aware Protocol and Considerations
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Over-the-Air Programming Loading a new application or upgrading an existing application on a sensor node via a serial port or some physical connections to the node Reprogram nodes one by one However, physical access to nodes is in many cases extremely limited following deployment Even when access were possible, manually updating hundreds or thousands of nodes would be a tedious task indeed Network reprogramming protocols have recently emerged as a way to distribute application updates without requiring physical access to sensor nodes.
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Multi-hop Over-the-Air Programming MOAP divides a program image into packets, and these packets are distributed through the network. Once received, packets are placed in stable storage until the entire update has been completed. In MOAP, sources advertise updated code images to their neighbors. A node having received a full image become publishers and propagate the image to other nodes out of range of the original source. This process is applied iteratively until the update has propagated across the network. Packet loss and retransmission Receiver uses a sliding window to keep track of lost packets. When a missing packet is detected, the receiver sends a uni-cast retransmission request. If the source does not respond within a certain amount of time, the receiver broadcasts a retransmission request to which all nodes within range reply. This allows the receiver to choose a new source in case the original source fails. Duplicate requests arriving at a source within a given time period are suppressed.
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Cross Layer Protocol Design No standard protocol for sensor nets Sensor protocol design is task-specific Resource constraints even demand cross-layer integration While some protocols can achieve very high performance in terms of the metrics related to each of the individual layer, they are not jointly optimized in order to maximize the overall network performance and minimize energy expenditure When designing communication schemes, we can not simply pick the best protocol in each layer and pile them up.
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Tele-Communication System The needs for telemetry Provides near-real-time data feeding Enables remote control of sensor nets and data loggers Change monitoring parameters Update sensor motes/data logger programs after deployment Single Board Computer (SBC) 200Mhz ARM processor, 64MB RAM, 1GB SD Card Linux support Bridge between sensors and Internet Local Database Server GPRS modem PPP and PPP Daemon a data link protocol commonly used to establish a direct connection between two nodes over serial cable, phone line, cellular phone, or dial-up network to get access to the Internet
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Conclusion Data flows from sensors to remote database System Architecture Research areas Energy-Aware Design Cross Layer Protocol Design Over the air programming Localization Questions?
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