1 / 62

Sensor Networks

Sensor Networks. OUTLINE. Introduction Applications Communication Architecture Protocol Stack Research Issues Another Challenges Conclusion. Introduction - Definition. Sensor Network Wireless network consisting of low cost, densely deployed (may be mobile) sensor nodes.

trapper
Download Presentation

Sensor Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Sensor Networks

  2. OUTLINE • Introduction • Applications • Communication Architecture • Protocol Stack • Research Issues • Another Challenges • Conclusion

  3. Introduction - Definition • Sensor Network • Wireless network consisting of low cost, densely deployed (may be mobile) sensor nodes. • Distribution is done in an ad hoc fashion. • Close to event to be monitored. • Usually have a limited amount of energy. • Sensor Nodes • Battery Power source, low power wireless communication. • Match Box size form factor and power aware CPU. • Small embedded OS (TinyOS) and program & data memory is few KB. • MEMS sensors (measures light, temp, seismic, acoustics, stress). http://www.ensc.sfu.ca/~ljilja/cnl/presentations/shameem/project816.pdf

  4. Introduction - Advantages • Improved Signal-to-Noise Ration (SNR) • combine sources with different spatial perspectives. • Greater fault tolerance through redundancy • Coverage of large area • Multiple sensor types can improve performance • Sensors close to object/phenomena of interest can overcome environmental noise effects • Can be deployed in regions where infrastructure for replenishing energy is not available http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  5. Introduction - Difference What makes a wireless sensor network unique? • Cellular networks, ad-hoc networks are designed to • Optimize QoS & Provide high bandwidth • Provide good throughput/delay characteristics under medium/high mobility conditions • Energy consumption of secondary importance • Sensor networks • Many nodes, autonomous operation • Generally stationary devices (or low mobility) • Traffic periodic or intermittent, low data rate, frequently uni-directional • Energy management is critical • Sensing application cannot be ignored ! http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  6. Introduction - Uniqueness • Data-centric networks • Identity/address of a sensor node is not critical – its data is the important aspect • Application specific • Intermediate nodes can perform data aggregation or in-network processing • Network operation driven by global objectives; not by individual data transfers. • Resource constraints call for more tightly integrated layers http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  7. Sensors and Wireless Radio Types of sensors: -Pressure, -Temperature -Light -Biological -Chemical -Strain, fatigue -Tilt Sensors • Capable of surviving harsh environments (heat, humidity, corrosion, pollution, radiation, etc). • Could be deployed in large numbers. Wireless Radio From CDMChttp://www.ececs.uc.edu/~dpa

  8. Applications • Medical monitoring (e.g., heart rate, glucose level) and localized drug delivery • Monitoring structural integrity in buildings • Tracking vehicles, people, chemical agents, pollution, weather phenomena • Seismic monitoring, contaminant/pollution monitoring • Precision agriculture The movie “Twister” is an example of sensor network. http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  9. Ecophysiological Modeling Using Sensor Array Data • Spatially and temporally dense microclimate data will allow • significant advancements in modeling plant production http://cens.ucla.edu/Estrin/

  10. NIMS: mobile ground and canopy climate sensors, data mules, and robotic samplers Dense micro-climate sensor networks Extensible Sensor System (ESS) Cavity nest micro-climate, remote observation, bioacoustic sensing Habitat and Environmental Sensing UC James Reserve Habitat Sensing Testbed Soil microclimate and chemical sensors, root/fungi imaging systems (mini-rhizotron) James Reserve and Hall Canyon Research Natural Area http://cens.ucla.edu/Estrin/

  11. Error Resilient Contaminant Monitoring Sensor network error resiliency in complex media (air-water-soil) • Working in the context of a real problem in Palmdale, CA • partnering with LA County Sanitation District • Working in concert with Sensor Group on broadly applicable sensors, scalable sensors nitrate and other ionic species • microsensors matching COTS perfomance • Real-time analysis instead of “logging” • model calibration, forecasting http://cens.ucla.edu/Estrin/

  12. Larger scale, multimedia problems Linking remote and in situ sensing over multiple scales Management, visualization, exploration of massive, heterogeneous data streams NSF CLEANER Initiative Challenges: Multimedia, Multiscale problems (time and space) Multidisciplinary Management, visualization, exploration of massive, heterogeneous data streams Contaminant Transport Futures http://cens.ucla.edu/Estrin/

  13. Seismic Applications • Multi-Hopped Radio Linked Array features • Time synchronization • Network event detect • Sequenced event transmission • Deployments planned for UCLA campus and the San Andreas Fault (100m-10 km) • Easily reconfigurable • Worldwide application • Factor Building site • 72 channels of 24-bit data • 500 samples per second continuous data recording • Internet accessible real time data monitoring • Observation of 4 strong earthquakes, including Alaska & Japan Fiberoptic link Radio link http://cens.ucla.edu/Estrin/

  14. Science Application Systems • Biology/Biocomplexity • Microclimate monitoring • Triggered image capture • Marine microorganisms • Detection of a harmful alga • Experimental testbed w/autonously adapting sensor location Ecosystems, Biocomplexity Marine Microorganisms http://cens.ucla.edu/Estrin/

  15. Architectural Decisions • Small size, rugged design, energy-efficient operation and low cost • Limited transmission range -> multi-hop network • Communication is energy-expensive • 3 J energy to transmit 1Kb over 100m – equivalent to 300 million instructions for a 100 Mops processor • Rough energy rule: 1 bit = 1000 instructions • Local processing of information to limit amount of data that must be exchanged http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  16. Strategies • Cooperative signal processing • Collaboration enhances energy efficiency • Substantial redundancy in data from closely-spaced sensors • Exploit redundancy of hardware elements • Deploy higher density of nodes than necessary • Adjust duty cycle so neighboring nodes are not always active • Adaptive signal processing • Maintain balance between energy, accuracy and rapidity of results • Hierarchical architecture • Higher energy, more powerful devices act as cluster heads • Cluster heads control operation of a set of more limited devices http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  17. Communication Architecture Sensor nodes are usually scattered in a sensor field. Each of these scattered sensor nodes has the capabilities to collect and route data back to the sink by a multi-hop infrastructureless architecture through the sink.

  18. Communication Architecture(Cont.) • Design Factor • Fault Tolerance • Scalability • Production Costs • Hardware Constraints • Sensor Network Topology • Environment • Transmission Media • Power Consumption

  19. Communication Architecture(Cont.) • Design Factor - Fault Tolerance • The failure of sensor nodes should not affect the overall task of the sensor network where : the failure rate of sensor node k t : time period • Reference [2]

  20. Communication Architecture(Cont.) • Design Factor - Scalability • The density can range from few sensor nodes to few hundred sensor nodes in a region, which can be less than 10 m in diameter. • Reference[3]

  21. Communication Architecture(Cont.) • Design Factor - Production Costs • The cost of each sensor node has to be kept low • The state-of-the-art technology allow a Bluetooth radio system to be less than US$10. • The cost of a sensor node should be much less than US$1 in order for the sensor network to be feasible.

  22. Communication Architecture(Cont.) • Design Factor - Hardware Constraints

  23. Communication Architecture(Cont.) • Design Factor - Sensor Network Topology • Predeployment and deployment phase • Post-deployment phase • Redeployment of additional nodes phase

  24. Communication Architecture(Cont.) • Design Factor - Environment • Sensor nodes usually work unattended in remote geographic areas. • At the bottom of an ocean • In a biologically or chemically contaminated field • In a battlefield • In a home or large building

  25. Communication Architecture(Cont.) • Design Factor (Transmission Media) • RF circuit μAMPS, WINS • Infrared • Optical Smart Dust mote

  26. Communication Architecture(Cont.) • Design Factor - Power Consumption • Limited power(<0.5Ah, 1.2V) • Power Consumption • Sensing • Communication • Data processing

  27. Protocol Stack This protocol stack combines power and routing awareness, integrates data with networking protocols, communicates power efficiently through the wireless medium, and promotes cooperative efforts of sensor nodes.

  28. Protocol Stack (cont.) • Physical Layer • 915MHz (ISM) band • Ultra wideband (UWB) • Impulse radio (IR) • Open research issue • Modulation schemes • Strategies to overcome signal propagation effect • Hardware design

  29. Protocol Stack (cont.) • Data Link Layer (Medium Access Control) • Existing MAC protocols cannot be used • SMACS (Self-Organizing Medium Access Control for sensor Networks) and the EAR (Eaves-drop-And-Register) Algorithm • CSMA-Based Medium Access • Hybrid TDMA/FDMA-Based

  30. Protocol Stack (cont.) • Data Link Layer (Power Saving Modes of Operation) • Sensor nodes communicate using short data packets. The shorter the packets, the more the dominance of startup energy. • Energy-efficient only if the time spent in that mode is greater than a certain threshold. • Number of modes can be characterized by its power consumption and latency overhead.

  31. Protocol Stack (cont.) • Data Link Layer (Error Control) • FEC (Forward Error Correction) • ARQ (Automatic Repeat Quest)

  32. Protocol Stack (cont.) • Data Link Layer (Open Research Issues) • MAC for mobile sensor networks • Determination of lower bounds on the energy required for sensor network self-organization • Error control coding schemes • Power-saving modes of operation

  33. Protocol Stack (cont.) • Network Layer • Power efficiency is always an important consideration. • Sensor networks are mostly data-centric. • Data aggregation is useful only when it does not hinder the collaborative effort of the sensor nodes. • An ideal sensor network has attribute-based addressing and location awareness.

  34. Protocol Stack (cont.) • Network Layer • Maximum PA route • Minimum energy (ME) route • Minimum hop (MH) route • Maximum minimum PA node route

  35. Protocol Stack (cont.) • The power efficiency of the routes • an example of data aggregation • the SPIN protocol [15] • an example of directed diffusion [5]

  36. Protocol Stack (cont.) • Network Layer • SMECN (Small Minimum Energy Communication Network) • Flooding • Gossiping • Sensor Protocols for information via negotiation • Sequential assignment routing • Low-Energy Adaptive Clustering Hierarchy • Directed diffusion

  37. Network Layer (open research issues) Protocol Stack (cont.) An overview of the protocols proposed for sensor networks is given in above table. These protocols need to be improved or new protocols developed to address higher topology changes and higher scalability.

  38. Protocol Stack (cont.) • Transport Layer • TCP with its current transmission window mechanisms does match the extreme characteristics of the sensor network. • TCP connections are enabled at sink nodes. • Communication between the sink and sensor nodes maybe purely by UDP-type protocols, because each sensor node has limited memory

  39. Protocol Stack (cont.) • Transport Layer (open research issues) • UDP-type protocol are used in the sensor network • Traditional TCP/UDP protocols are used in the internet or satellite network

  40. Protocol Stack (cont.) • Application Layer • SMP (Sensor Management Protocol) • TADAP (Task Assignment and Data Advertisement Protocol) • SQDDP (Sensor Query and Data Dissemination Protocol)

  41. Operational Challenges • Adaptive, self-configuring systems that respond to an unpredictable environment • Data processing inside the network • Perform computation where data is measured to extract information (compress) • Important to reduce communication overhead • Distributed control and signal processing • Untethered, unattended large-scale systems • Low-duty cycle design • Preserve energy by minimizing communication http://www.ece.mcgill.ca/~coates/publications/shortcourse-part1.pdf

  42. Networking Challengesand Design Principles • Localization • Synchronization • Coverage • Device management and scheduling • Connectivity (topology) maintenance • Routing • Reliable Data Transport • Seciruty http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  43. Localization and Synchronization • Accurate localization and synchronization • Need to determine where events occur in space • Critical for fusion of sensor measurements • Important for coordination of communication • GPS provides one solution • Not always available • Can be too costly, bulky http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  44. Localization • Most techniques use recursive trilateration/multilateration • Some nodes are assumed to know their position (through GPS for instance). • These act as beacons by periodically transmitting their position • Nodes hearing these beacons use them to estimate their position • May be an iterative process http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  45. Localization (cont.) • Fine-grained (timing/signal strength) or coarsegrained (proximity) • Fine-grained • Time of flight • Signal strength • Signal pattern matching • Directionality • Coarse-grained • Centroid of beacons http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  46. Localization Challenges • How many beacons are needed? • Provide good coverage, avoid excessive interference • Where should beacons be placed? • Incremental beacon placement • Place new beacon in region of maximum (average) localization error • Controlling beacons • Scheduling operation to preserve lifetime http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  47. Synchronization • Metrics • Precision • Peer dispersion or with reference to external standard • Lifetime • Ranging from persistent to instantaneous • Scope and Availability • Geographic span and completeness of coverage • Efficiency • Time and energy expenditure • Cost and form factor http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  48. Sensor Network Synchronization • Fine-grained, persistent timing is important in sensor networks • Data fusion • detect/estimate the same event • Local data processing • Eliminate duplicates through timestamping • Existing network timing protocols inadequate • Often conservative in use of bandwidth (e.g., NTP) but neglect cost of listening • Heterogeneity of hardware • Multiple methods of synchronization should be available • Algorithms should be tunable (precision vs. energy) http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  49. Coverage • Measures of coverage • Area coverage : fraction of area covered by sensors • Detectability : probability sensors detect event • Node coverage: fraction of sensors covered by other sensors • Maximal breach path : intruder is maximum distance from sensors over entire path • Maximum exposure path : minimum distance from sensors over entire path • K-coverage : entire sensing region must be within distance K of a sensor http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

  50. Coverage - Maintenance • Where to position sensors initially? • Where to add new sensors? • Where to move sensors? • When to schedule sensors? (overlapping sensors should not operate at same time) • Locate coverage holes, breach areas, best areas. http://www.ece.mcgill.ca/~coates/publications/shortcourse-part4.pdf

More Related