Introduction to Sensor Networks

1. Introduction to Sensor Networks Rabie A. Ramadan, PhD Cairo University http://rabieramadan.org rabie@rabieramadan.org 2

2. Do not think how hard the problem you are solving Just, “keep your eyes on the prize”

3. Hardware Platforms • Augmented General Purpose PCs • Embedded PCs (PC104), PDAs, etc.. • Usually have O.S like Linux and wireless device such as Bluetooth. • Dedicated Sensor Nodes • Commercially off the shelf components (e.g. Berkeley Motes) • System-on-chip Sensor • Platform like Smart dust, PicoNode

4. Software Platforms • Operating Systems and Language Platforms • Typical Platforms are: • TinyOS, nesC, TinyGALS, and Mote’ • TinyOS • Event Driven O.S. • Requires 178 bytes of memory • Supports Multitasking and code Modularity • Has no file system – only static memory allocation • Simple task scheduler • nesC – extension of C language for TinyOS- set of language constructs • TinyGALS -language for TinyOS for event triggered concurrent execution . • Mote’ - Virtual machine for Berkeley Mote

5. Wireless Sensor Network Standards • IEEE 802.15.4 Standard • Specifies the physical and MAC Layers for low-rate WPANs • Data rates of 250 kbps, 40 kbps, and 20 kbps. • Two addressing modes: 16 - bit short and 64 - bit IEEE addressing. • Support for critical latency devices, for example, joysticks. • The CSMA - CA channel access. • Fully handshaking protocol for transfer reliability. • Power management to ensure low - power consumption.

6. CSMA-CA Protocol How it works?

7. Wireless Sensor Network Standards • IEEE 802.15.4 Standard • The physical layer is compatible with current wireless standards such as Bluetooth • MAC layer implements synchronization , time slot management , and basic security mechanisms.

8. Wireless Sensor Network Standards IEEE 802.15.4 & ZigBee In Context Application Customer • “the software” • Network, Security & Application layers • Brand management • IEEE 802.15.4 • “the hardware” • Physical & Media Access Control layers API Security 32- / 64- / 128-bit encryption ZigBee Alliance Network Star / Mesh / Cluster-Tree MAC IEEE 802.15.4 PHY 868MHz / 915MHz / 2.4GHz Stack Silicon App

9. ZigBee Utilization BUILDING AUTOMATION CONSUMER ELECTRONICS security HVAC lighting control accesscontrol TV VCR DVD/CD remote PC & PERIPHERALS patient monitoring fitness monitoring PERSONAL HEALTH CARE ZigBee Wireless Control that Simply Works mouse keyboard joystick INDUSTRIAL CONTROL RESIDENTIAL/ LIGHT COMMERCIAL CONTROL asset mgt process control environmental energy mgt security HVAC lighting control access control lawn & garden irrigation

10. Applications Example

11. Project ExScal: Concept of operation Put tripwires anywhere—in deserts, other areas where physical terrain does not constrain troop or vehicle movement—to detect, classify & track intruders[Computer Networks 2004, ALineInTheSand webpage, ExScal webpage]

12. ExScal scenarios Border Monitoring: • Detect movement where none should exist , • Decide target classes, e.g., foot traffic to tanks • Ideal when combined with towers, tethered balloons, or UAVs

13. WSN Research Fields • Sensors HW and Software • Deployment • Physical , MAC, Routing, Applications • Data Aggregation and Data Mining • Artificial Intelligence and data handling • Self Healing • Web Integration • Heterogeneity • Security • Software Engineering (Simulators ) • Cloud Computing and Sensor Networks • Mobility Issues and Localization

14. Assignment 1 • Report the main security considerations of IEEE 802.15.4 ?

15. Deployment, Clustering , and and Routing in WSN

16. Deployment Constraints • Sensor characteristics • Monitored field characteristics • Monitored/probed object

17. Deployment Parameters

18. Deployment Parameters Diffraction: passing the signal through small opening and spreading it after passing the opening Scattering: scatter the coming signal Reflection : send the signal back towards the sender

19. Deployment Parameters

20. Deployment Parameters

21. Deployment Problems and Solutions • Random Deployment • Virtual force Algorithm • Deterministic Deployment • Circle Packing • Energy Mapping • Movement-Assisted Sensor Deployment • Sink Placement Problem • Single node • Multiple sink deployment • Relay Node Placement in WSN

22. Random Deployment Virtual Force Algorithm

23. Virtual Force Algorithm • Sensors are initially deployed randomly • Objective: • To maximize the Coverage • Assumptions: • Assume no prior knowledge about the monitored field • All nodes are mobile • Energy and obstacles might present in the field

24. Virtual Force Algorithm (Cont.) • Attractive and Repulsive forces • Sensors do not physically move • A sequence of virtual motion paths is determined for the randomly placed sensors. • Once the effective sensor positions are identified, a one-time movement is carried out to redeploy the sensors at these positions.

25. Virtual Force Algorithm (Semi Distributed.) • Assumptions: • Clustered network • All clustered heads are able to communicate with the sink node • The cluster head is responsible for executing the VFA and managing the one-time movement of sensors to the desired locations.

26. Virtual Force Algorithm (Cont.) • Each sensor behaves as a “Sourceof force” for all other sensors. • This force can be either positive (Attractive) or negative (Repulsive). • The closeness and wide distance between two sensors are measured using a predefined threshold.

27. Virtual Force Algorithm (Cont.) • Sensor Binary Model • Consider an n by m sensor field grid and assume that there are k sensors deployed in the random deployment stage. • Each sensor has a detection range r. Assume sensor siis deployed at point (xi , yi ). • For any point P at (x, y), we denote the Euclidean distance between si and P as d(si , P), • The coverage of a Grid Point P can be expressed by:

28. Virtual Force Algorithm (Cont.) • Virtual Forces • Attraction force  F12 • Repulsive force  F13 • Zero Force  F14 • Obstacle Force  • preferential coverage Force  Total Force on node i =

29. Virtual Force Algorithm (Cont.) • Using such forces , the cluster head runs the VFA • After stability occurs , Sensors are ordered to move to the new positions • Energy and Obstacles might be problems • Any sensor will not be able to move the required distance , the moving order is discarded • Obstacles need an obstacle avoidance algorithm

30. Think….. • If some sensors are stationary, does this affect the virtual force algorithm? • What other problems you see in the algorithm? • Coverage might not be satisfied due to the limitation in the energy since some nodes might not be able to move to the specified place. • Mobility assumption might not be the case for all WSNs

31. SENSOR REPLACEMENT BASED ENERGY MAPPING

32. The problem • A set of sensors S is deployed in a monitored field F(A)for a period of time T. • The field is divided into a grid of cells A. • Each cell is assigned a weight where represents the importance of the cell i. • The location of each sensor is assumed known; • More than one sensor could be deployed in one cell. • Sensors are assumed heterogeneous in terms of their energy and mobility.

33. Assumptions • A sensor could be in different states; • it could have its sensing off or on based on the field monitoring requirements. • Sensing off, radio off – (sleep mode) • Sensing off, radio receiving – (Receiving mode) • Sensing off, radio transmitting – (Routing mode) • Sensing on, radio receiving – (Sensing and Receiving mode) • Sensing on, radio transmitting – (Sensing and Transmitting mode) • Sensing on, radio off - (Sensing mode)

34. The main idea • Knowing the energy map of the network : • May lead to early detection to the uncovered areas. • Redeploy new sensors • Turn off some of the sensors due to their coverage redundancy • Wake up some of the nodes when needed • Move one or mobile nodes to cover the required uncovered spots

35. Redeployment based Energy map • Step 1: Energy dissipation rate prediction • Each sensor predicts its own energy rate based on its history (e.g. Markov Chain ..) • Step 2: sensors send their initial energy and the location, predicted energy dissipation rate to the sink node through a cluster head. • Sensors update their energy dissipation rate based on a specific threshold (if the new dissipation rate increased more than the given threshold , the node sends the new dissipation rate)

36. Redeployment based Energy map • Step 3: the sink node constructs the energy map based on the received dissipated energy rate from the sensors. • The sink may move one of the mobile sensors to the uncovered spot or wake up one of the sleeping sensors

37. Think ……. • What are the disadvantages of energy mapping algorithm ? • Sensor network is an event based network . Therefore , events are not frequently or based on specific pattern. Thus, the amount of messages to be transmitted to report the energy mapping will not be expected and might play a role in sensors energy dissipation. • Centralized algorithm

38. Movement-Assisted Sensor Deployment

39. The problem of sensor deployment • Given the target area, how to maximize the sensor coverage with less time, movement distance and message complexity • The importance of the problem • Distributed instead of centralized

40. Voronoi Diagram • Definition: • Every point in a given polygon is closer to the node in this polygon than to any other node.

41. Overview of the proposed algorithm • Sensors broadcast their locations and construct local Voronoi polygons • Find the coverage holes by examining Voronoi polygons • If holes exist, reduce coverage hole by moving • VOR : VORonoi-based • Pull sensors to the sparsely covered area

42. Part of Assignment 1 (on CD and a printed report) • Implement both Virtual Force algorithm and Voronoi based algorithm ? Report your experience and algorithms efficiency? • Given a set of sensors with limited amount of energy. Some of these sensors are assumed mobile and others are assumed stationary. Assume similar sensing and communication ranges for all sensors. Sensors are allowed to move from one place to another iff they have enough energy to move to the required destination. In addition , the borders of the monitored area is assumed known in terms of 2D coordinates. Borders may be found in the monitored area. Advice a suitable deterministic deployment algorithm for efficient deployment to the sensors given that the deployed sensors have to be connected and important areas in the field are covered. In addition , your algorithm must guarantee the coverage of the monitored field for certain period of time. • You may look for an already given solution or come up with a convincing one .

43. Deterministic Deployment Deployment Using Circle Packing

44. Deployment Using Circle Packing • Deployment of homogenous sensors • Full Coverage Deployment • Deployment of connected heterogeneous sensors 44

45. Deployment of homogenous sensors These results were based on the information presented at “introduction to circle packing” book 45

46. Full Coverage Deployment 46

47. Sequential Packing-based Deployment Algorithm (SPDA) • Given • Sensors Sensing Ranges • Sensors Communication Ranges • Bounded Monitored Field • Objective • Best Connected Deployment Scheme • Max. Coverage. • Min. Overlapped Areas • Benefit from the properties learned from the optimal deployment using circle packing 47

48. Sequential Packing-based Deployment Algorithm

49. Sequential Packing-based Deployment Algorithm

50. Potential Points 50