ECE/CSC 575 – Section 1 Introduction to Wireless Networking

1. ECE/CSC 575 – Section 1 Introduction to Wireless Networking Lecture 24Dr. Xinbing Wang

2. Overview of the Course • Part 1: Wireless communication systems (Chapter 1) • Flexibility to support roaming • Limitations: Geographical coverage, transmission rate, and transmission errors • Part 2: Wireless communication technology • Radio propagation (Chapter 5) • Spread spectrum (Chapter 7) • Part 3: Current wireless systems • Cellular network architecture (Chapter 10) • Mobile IP (Chapter 12) • Wireless LAN (Chapter 11/13/14) • Part 4: Other wireless networks • Ad hoc networks (Reading materials) • Sensor networks (Reading materials) • Wireless PAN (Chapter 15) • Satellite systems (Chapter 9) • Part 5: Wireless Security Dr. Xinbing Wang

3. Factors Influencing Sensor Network Design  A. Fault Tolerance (Reliability) B. Scalability C. Production Costs D. Hardware Constraints E. Sensor Network Topology F. Operating Environment G. Transmission Media H. Power Consumption  Dr. Xinbing Wang

4. B. Scalability • The number of sensor nodes may reach millions in studying a field/application • The density of sensor nodes can range from few to several hundreds in a region (cluster) which can be less than 10m in diameter. Dr. Xinbing Wang

5. Scalability (2) • The Sensor Node Density: i.e., the number of expected nodes within the radio range R where N is the number of scattered sensor nodes in region A and R is the radio transmission range. Basically:  is the number of sensor nodes within the transmission radius of each sensor node in region A. The number of sensor nodes in a region is used to indicate the node density upon the application. Dr. Xinbing Wang

6. Scalability (3) EXAMPLE: Assume sensor nodes are evenly distributed in the sensor field, determine the node density if 200 sensor nodes are deployed in a 50x50 m2 region where each sensor node has a broadcast radius of 5 m. Use the eq. on the previous slide  (R) = (200 * * 52 )/(50*50) = 2 *  Dr. Xinbing Wang

7. Example -- Node Distribution Dr. Xinbing Wang

8. Scalability (4) -- Network Configuration dnei Expected distance to the nearest neighbor, may or may not be communicating neighbor. dhop  Expected distance to the next hop, i.e., distance to communicating neighbor. dhop>=dnei Assuming that connection establishment is equally likely with any node within the radio range R of the given node, the expectedhop distance is: Sink node dhop = 2R/3 Radio Range R e.g., R=20m  13.33m dnei dhop Sensor nodes Dr. Xinbing Wang

9. Scalability (5) -- Examples • Machine Diagnosis Application: less than 300 sensor nodes in a 5 m x 5 m region. • Vehicle Tracking Application:Around 10 sensor nodes per cluster/region. • Home Application:2 dozens or more. • Habitat Monitoring Application: Range from 25 to 100 nodes/cluster • Personal Applications:Ranges from 100s to 1000s, e.g., clothing, eye glasses, shoes, watch, jewelry. Dr. Xinbing Wang

10. Factors Influencing Sensor Network Design  A. Fault Tolerance (Reliability) B. Scalability C. Production Costs D. Hardware Constraints E. Sensor Network Topology F. Operating Environment G. Transmission Media H. Power Consumption   Dr. Xinbing Wang

11. Sink Internet, Satellite, etc Sink Task Manager Sensor Networks Topology • Several thousand nodes • Nodes are tens of feet of each other • Densities as high as 20 nodes/m3 Topology can change: • Pre-deployment and Deployment Phase • Post Deployment Phase • Re-Deployment of Additional Nodes Dr. Xinbing Wang

12. Topology -- Pre-deployment and deployment Phase • Dropping from a plane • Delivering in an artillery shell, rocket or missile • Throwing by a catapult (from a ship board, etc.) • Placing in factory • Being placed one by one by a human or a robot • Initial deployment schemes must • Reduce installation cost • Eliminate the need for any pre-organization and pre-planning • Increase the flexibility of arrangement • Promote self organization and fault tolerance. Dr. Xinbing Wang

13. Topology --Post-deployment Phase • After deployment, topology changes are due to change in sensor nodes’ • Position • Reachability (due to jamming, noise, moving obstacles, etc.) • Available energy • Malfunctioning Dr. Xinbing Wang

14. Reliable Data and Query Transfer Dr. Xinbing Wang

15. Example: Node Classification • Sink rotates the essential node set periodically. Up-to-date energy-level information is sent by sensors within event reports. Dr. Xinbing Wang

16. Factors Influencing Sensor Network Design  A. Fault Tolerance (Reliability) B. Scalability C. Production Costs D. Hardware Constraints E. Sensor Network Topology F. Operating Environment G. Transmission Media H. Power Consumption    Dr. Xinbing Wang

17. Power Consumption • A Sensor node has limited power source (~1.2V). • Sensor node LIFETIME depends on battery lifetime • Sensors can be a DATA ORIGINATOR or a DATA ROUTER • Power conservation and power management are important  POWER AWARE PROTOCOLS must be developed. Dr. Xinbing Wang

18. Power Consumptions in Sensor Networks • Power consumption in a sensor network can be divided into three domains • Communication • Data Processing • Sensing • Transmission and reception energy costs are nearly the same, (e.g., modern low power short range transceivers consume between 15 and 300 milliwatts of power when sending and receiving). • Transceiver circuitry has both active and start-up power consumption Dr. Xinbing Wang

19. Power -- Communications • A sensor expends maximum energy in data communication (both for transmission and reception). NOTE: For short range communication with low radiation power (~0 dbm), transmission and reception power costs are approximately the same. Dr. Xinbing Wang

20. Power -- Sensing Depend on Applications • Nature of sensing: Sporadic or Constant • Detection complexity • Ambient noise levels Dr. Xinbing Wang

21. Comparison of Energy Balance Two-Tiered Scheduling without Rotation Two-Tiered Scheduling with Rotation Dr. Xinbing Wang

22. Application Layer Transport Layer Task Management Plane Mobility Management Plane Network Layer Power Management Plane Data Link Layer Physical Layer Sensor Networks: Communication Architecture • Used by sink and all sensor nodes • Combines power and routing awareness • Integrates data with networking protocols • Communicates power efficiently through wireless medium, and • Promotes cooperative efforts. Dr. Xinbing Wang

23. Why can’t ad-hoc network protocols be used? • Number of sensor nodes can be several orders of magnitude higher • Sensor nodes are densely deployed and are prone to failures • The topology of a sensor network changes very frequently due to node mobility and node failure • Sensor nodes are limited in power, computational capacities, and memory • May not have global ID like IP address. • Need tight integration with sensing tasks. Dr. Xinbing Wang

24. Network Layer -- Routing/Forwarding • Sensor networks are mostly data centric • They are “data centric” networks, i.e., the interest is in “what is the data?” rather than “where is the data?”. • An ideal sensor network has attribute based addressing and location awareness • Data aggregation is useful unless it does not hinder collaborative effort • Power efficiency is always a key factor Dr. Xinbing Wang

25. Network Layer -- Routing/Forwarding (2) • In traditional wired networks each node is identified by a unique address, which is used for routing. Sensor networks, being data centric do not, in general, require routing between specific nodes. • Adjacent nodes may have similar data. So it is desirable to aggregate this data and send it. • The requirements of the network change with application, hence it is application specific. Dr. Xinbing Wang

26. Network Layer -- Routing/Forwarding (3) • Routing Algorithms Constraints Regarding Power Efficiency (Energy Efficient Routing) E (PA=1) F (PA=4) • Minimum power available (PA) route : Route along which the PA is larger than PAs of the other routes is preferred, e.g., Route 3 is the most efficient; Route 1 is the second). D (PA=3) T Sink A (PA=2) C (PA=2) B (PA=2) Route 1: Sink-A-B-T (PA=2) Route 2: Sink-A-B-C-T (PA=2) Route 3: Sink-D-T (PA=3) Route 4: Sink-E-F-T (PA=1) Dr. Xinbing Wang

27. 71 75 68 67 66 71 71 71 68 69 Network Layer -- Routing/Forwarding (4) • Data-Centric Routing • Interest dissemination is performed to assign the sensing tasks to the sensor nodes. • Either sinks broadcast the interest or sensor nodes broadcast an advertisement for the available data and wait for a request from the sinks. Sink Query: Nodes that read >70oF temperature Dr. Xinbing Wang

28. Commercial Viability of WSN Applications • XSILOGY Solutions is a company which provides wireless sensor network solutions for various commercial applications such as tank inventory management, stream distribution systems, commercial buildings, environmental monitoring, homeland defense etc. http://www.xsilogy.com/home/main/index.html • In-Q-Tel provides distributed data collection solutions with sensor network deployment. http://www.in-q-tel.com/tech/dd.html • ENSCO Inc. invests in wireless sensor networks for meteorological applications. http://www.ensco.com/products/homeland/msis/msis_rnd.htm • EMBER provides wireless sensor network solutions for industrial automation, defense, and building automation. http://www.ember.com Dr. Xinbing Wang

29. Commercial Viability of WSN Applications (2) • H900 Wireless SensorNet System(TM), the first commercially available end-to-end, low-power, bi-directional, wireless mesh networking system for commercial sensors and controls is developed by the company called Sensicast Systems. The company targets wide range of commercial applications from energy to homeland security. http://www.sensicast.com • The Sensor-based Perimeter Security product is introduced by a company called SOFLINX Corp. (a wireless sensor network software company) http://www.soflinx.com • XYZ On A Chip: Integrated Wireless Sensor Networks for the Control of the Indoor Environment In Buildings is another commercial application project currently performed by Berkeley. http://www.cbe.berkeley.edu/research/briefs-wirelessxyz.htm Dr. Xinbing Wang

30. Commercial Viability of WSN Applications (3) • Melexis produces advanced integrated semiconductors, sensor ICs, and programmable sensor IC systems. http://www.melexis.com • Dust Inc. develops the next-generation hardware and software for wireless sensor networks http://www.dust-inc.com • Integration Associates designs sensors used in medical, automotive, industrial, and military applications to cost-effective designs for handheld consumer appliances, barcode readers, and wireless computer input devices http://www.integration.com • Chipcon produces low-cost and low-power single-chip 2.4 GHz ISM band transceiver design for sensors. http://www.chipcon.com • ZigBee Alliance develops a standard for wireless low-power, low-rate devices. http://www.zigbee.com Dr. Xinbing Wang

31. Application: Remote and Intelligent Control Field of Interest Dr. Xinbing Wang

32. Final Remarks • Basic Needs • An Analytical Framework for Sensor Networks • Find a Basic Generic Architecture and Protocol • Development which can be tailored to specific applications. • More theoretical investigations of the Architecture and Protocol developments • Network Configuration and Planning • Future challenges in protocol stack • Follow the TCP/IP Stack, i.e., keep the strict Layer Approach? • Or Interleave the Layer functionalities? • Cross Layer Optimization • Standardization? Dr. Xinbing Wang