1. Introduction to Sensor Networks Rabie A. Ramadan, PhD Cairo University http://rabieramadan.org rabie@rabieramadan.org 1

2. WebSite Website: http://rabieramadan.org/classes/2013/sensor/ 2

3. Class Format Presentations by myself Assignments Survey on one of the following topics : Topics Survey Format 3

4. Textbooks Some other materials will be provided 4

5. 5 Introduction and Basic Concepts 5

6. Wireless Networks Most of the traditional wireless networks occur over fixed infrastructure Access points Many wireless protocols (heterogeneity problem) Bluetooth, WiFi, WiMax We need Seamless network Connects everyone from their home to work,.. Disasters may be a drive force for such networks 6 Katrina hurricane, 2006

7. General Types of Wireless Networks Wireless Cellular Networks First, Second, 2.5, third, and 4 th generations Wireless Ad Hoc Networks Nodes function as host and router Dynamic topology Nodes may departure Requires efficient routing protocols Mobile Ad Hoc Networks (MANET) Wireless Sensor Networks (WSN) 7

8. Wireless Sensor Networks 8

9. Definitions and Background Sensing: Is a technique used to gather information about a physical object or process, including the occurrence of events (i.e., changes in state such as a drop in temperature or pressure). Sensor: An object performing such a sensing task Converts energy of the physical worlds into electrical signal. Sometimes named “Transducer”  converts energy from one form to another. 9

10. Definitions and Background Examples on remote sensors: eyes: capture optical information (light) ears: capture acoustic information (sound) nose: captures olfactory information (smell) skin: captures tactile information (shape, texture) 10

11. Sensing Task 11 e.g. amplification, filtering,..etc

12. An example of a sensor: Passive infrared PIR is a differential sensor: detects target as it crosses the “beams” produced by the optic

13. PIR signal: Amplitude Human 3 mph @ 10m Car 20-25 mph @ 25m

14. Communication Unit Sensing Unit Sensors ADC Processing Unit Processor Storage Power Unit Mobility Support Unit Location Finding Unit What is a Smart Sensor Node?

15. Node’s Responsibilities Data Collection In-Network Analysis Data Fusion Decision Making 15

16. Sensors Classification 16 TypeExamples TemperatureThermistors, thermocouples PressurePressure gauges, barometers, ionization gauges OpticalPhotodiodes, phototransistors, infrared sensors, CCD sensors AcousticPiezoelectric resonators, microphones MechanicalStrain gauges, tactile sensors, capacitive diaphragms, piezoresistive cells Motion, vibrationAccelerometers, mass air flow sensors PositionGPS, ultrasound-based sensors, infrared-based sensors, inclinometers ElectromagneticHall-effect sensors, magnetometers ChemicalpH sensors, electrochemical sensors, infrared gas sensors HumidityCapacitive and resistive sensors, hygrometers, MEMS-based humidity sensors RadiationIonization detectors, Geiger-Mueller counters Physical property to be monitored determines type of required sensor

17. Other Classifications Power supply: Power supply: active sensors require external power, i.e., they emit energy (microwaves, light, sound) to trigger response or detect change in energy of transmitted signal (e.g., electromagnetic proximity sensor) passive sensors detect energy in the environment and derive their power from this energy input (e.g., passive infrared sensor) Electrical phenomenon: Electrical phenomenon: resistive sensors use changes in electrical resistivity (ρ) based on physical properties such as temperature (resistance R = ρ*l/A) capacitive sensors use changes in capacitor dimensions or permittivity (ε) based on physical properties (capacitance C = ε*A/d) inductive sensors rely on the principle of inductance (electromagnetic force is induced by fluctuating current) piezoelectric sensors rely on materials (crystals, ceramics) that generate a displacement of charges in response to mechanical deformation

18. 18 What is a sensor Network? Sink Node Internet Monitored field

19. Wireless Sensor Network (WSN) Multiple sensors (often hundreds or thousands) form a network to cooperatively monitor large or complex physical environments Acquired information is wirelessly communicated to a base station (BS), which propagates the information to remote devices for storage, analysis, and processing

20. History of WSN 20

21. History of Wireless Sensor Networks DARPA: Distributed Sensor Nets Workshop (1978) Distributed Sensor Networks (DSN) program (early 1980s) Sensor Information Technology (SensIT) program UCLA and Rockwell Science Center Wireless Integrated Network Sensors (WINS) Low Power Wireless Integrated Microsensor (LWIM) (1996) UC-Berkeley Smart Dust project (1999) concept of “motes”: extremely small sensor nodes Berkeley Wireless Research Center (BWRC) PicoRadio project (2000) MIT μAMPS (micro-Adaptive Multidomain Power-aware Sensors) (2005)

22. Sample Sensor Hardware: Berkeley motes 22

23. 23

24. Commercial Effort Crossbow (www.xbow.com), Sensoria (www.sensoria.com), Worldsens (http://worldsens.citi.insa- lyon.fr),http://worldsens.citi.insa- lyon.fr Dust Networks (http://www.dustnetworks.com ), andhttp://www.dustnetworks.com Ember Corporation (http://www.ember.com ).http://www.ember.com 24

25. Challenges and Constraints Energy Sensors powered through batteries  sometimes impossible to do. Mission time may depend on the type of application (e.g. battlefield monitoring – hours or days) Node’s layers must be designed carefully. 25

26. Wireless Range Controls the Network Topology 26 Routing in multihop network is a challenge Relay node may aggregate the data

27. Medium Access Control layer (MAC) Responsible for providing sensor nodes with access to the wireless channel. Responsible of Contention free Transmission. MAC protocols have to be contention free as well as energy efficient. Contention free requires listening to the wireless channel all the time Energy efficient requires turning off the radio 27

28. Network Layer Responsible for finding routes from a sensor node to the base station Route characteristics such as length (e.g., in terms of number of hops), required transmission power, and available energy on relay nodes Determine the energy overheads of multi-hop communication and try to avoid it. 28

29. Operating System Energy affects the O.S. design : Small memory footprint, Efficient switching between tasks security mechanisms 29

30. Challenges and Constraints Self-Management Sensors usually deployed in harsh environment. There is no pre-infrastructure setup. Once deployed, must operate without human intervention Sensor nodes must be self-managing in that They configure themselves, Operate and collaborate with other nodes, Adapt to failures, changes in the environment, 30

31. A self-managing Network Self-organization A network’s ability to adapt configuration parameters based on system and Environmental state. Self-optimization A device’s ability to monitor and optimize the use of its own system resources Self-protection Allows a device to recognize and protect itself from intrusions and attacks Self-healing Allows sensor nodes to discover, identify, and react to network disruptions. 31

32. Ad Hoc Deployment Deterministic Vs. Ad Hoc Deployment 32

33. Challenges and Constraints Wireless Networking Transmission Media Sensors use wireless medium Suffer from the same problems that wireless networks suffer from Fading High error rate 33

34. Challenges and Constraints Wireless Networking Communication range Communication ranges are always short It is required for the network to be highly connected Routing paths will be long What about critical applications where delay is not acceptable ? QoS will be an issue 34

35. Challenges and Constraints Wireless Networking Sensing Range Very small Nodes might be close to each other Data Redundancy Coverage Problem 35

36. Challenges and Constraints Decentralized Management Requires Distributed Algorithms Overhead might be imposed Security Exposed to malicious intrusions and attacks due to unattendance characteristics. denial-of-service jamming attack 36

37. In Network Processing 37

38. Enable Data Base Like Operations 38

39. Network Characteristics Dense Node Deployment Battery-Powered Sensors Sever Energy, Computation, and Storage Constraints Self Configurable Application Specific Unreliable Sensor Nodes Frequent Topology Change No Global Identifications Many-to-One Traffic pattern ( multiple sources to a single Sink node) Data Redundancy 39

40. Design Issues Fault Tolerance Large number of nodes already deployed or Nodes do the same job. If one fails, the network still working because its neighbor monitors the same phenomenon. Mobility Helps nodes to reorganize themselves in case of a failure of any of the nodes Attribute-Based Addressing Addresses are composed of group of attribute-value pairs Ex. 35, location = area A>

41. Design issues Location Awareness Nodes’ data reporting is associated with location Priority Based Reporting Nodes should adapt to the drastic changes in the environment Query Handling The sink node / user should be able to query the network The response should be routed to the originator We might have multiple sinks in the network

42. Traditional networks Vs. wireless sensor networks 42 Traditional NetworksWireless Sensor Networks General-purpose design; serving many applicationsSingle-purpose design; serving one specific application Typical primary design concerns are network performance and latencies; energy is not a primary concern Energy is the main constraint in the design of all node and network components Networks are designed and engineered according to plansDeployment, network structure, and resource use are often ad-hoc (without planning) Devices and networks operate in controlled and mild environments Sensor networks often operate in environments with harsh conditions Maintenance and repair are common and networks are typically easy to access Physical access to sensor nodes is often difficult or even impossible Component failure is addressed through maintenance and repair Component failure is expected and addressed in the design of the network Obtaining global network knowledge is typically feasible and centralized management is possible Most decisions are made localized without the support of a central manager