1. Next Century Challenges: Scalable Coordination in Sensor Networks Deborah Estrin, Ramesh Govindan, John Heidemann, Satish Kumar (Some images and slides adopted from Santhosh R Thampuran - CMU)

2. 2 Outline Characteristics of sensor devices. Motivating applications. Key requirements of a sensor network and differences with current networks. Localized algorithms for coordination. Directed Diffusion – a model for describing localized algorithms.

3. 3 Characteristics of Sensor Devices Ability to monitor a wide variety of ambient conditions: – temperature, – pressure, – mechanical stress level on attached objects… Will be equipped with significant processing, memory, and wireless communication capabilities.

4. 4 Applications: Environmental Analysis

5. 5 Applications: Contaminant Flow Monitoring

6. 6 Applications: Traffic Control Sensor attached to every vehicle. Capable of detecting their location, vehicle sizes, speeds and densities; road conditions… Alternate routes, estimate trip times…

7. 7 Applications: Biological Systems

8. 8 Key Requirements These futuristic scenarios bring out two key requirements of sensor networks: – support for very large numbers of unattended autonomous nodes. – adaptivity to environment and task dynamics.

9. 9 Differences with Current Networks Sensor Networks: ratio of communicating nodes to users is much greater. – extremely difficult to pay special attention to any individual node. Sensors may be inaccessible: – embedded in physical structures. – thrown into inhospitable terrain.

10. 10 Differences with Current Networks There are large scale unattended systems, today. Automated factories are deployed with very careful planning and react to very few external events.

11. 11 Differences with Current Networks Sensor networks deployed in very ad hoc manner. They will suffer substantial changes as nodes fail: battery exhaustion, accidents; new nodes are added; nodes move. User and environmental demands also contribute to dynamics.

12. 12 Overall Design of Sensor Networks – Is it sufficient to design sensor network applications using Internet technologies coupled with ad-hoc routing mechanisms? Data-Centric; Application-Specific. Sensor network coordination applications are better realized using localized algorithms: distributed as opposed to centralized. – scales with increase in network size, robust to network partitions and node failures.

13. 13 Localized Algorithms for Coordination Clustering: efficient coordination.

14. 14 Localized Clustering Algorithm For every sensor, level  radius Advertisement = {hierarchical level, parent ID, remaining energy} B A C E D wait time

15. 15 Localized Clustering Algorithm B A C E D promotion timer Start promotion timer if no parent. Promotion timer: inv prop (remaining energy, number of other sensors from whom level 0 adv was received)

16. 16 Localized Clustering Algorithm B A C E D Periodic advertisements at the level 1 radius. Advertisement = {B,C,E} level 1 sensor

17. 17 Localized Clustering Algorithm Two key design constraints: – asymmetric communication in the network. – limited energy of sensors.

18. 18 Application of Clustering Algorithm Aim: To pinpoint in an energy-efficient manner, the exact location of objects. Accuracy: widest possible measurement baseline. triangulation Energy efficiency: fewest number of sensors participating in the triangulation.

19. 19 Triangulation A Z Determine position in space. Can specify approx direction of object relative to its own location.

20. 20 Base-line Estimation

21. 21 Advantages of Cluster-based Approach Sensor algorithms only use local information. – generally lower energy consumption in comparison to global communication. Robust to link or node failures and network partitions – mechanisms for self-configuration can be simpler.

22. 22 Advantages of Cluster-based Approach Local communication and per-hop data filtering – avoid transmitting large amounts of data over long distances. – preserving node energy resources. Node energy resources are better utilized – cluster-heads adapt to changing energy levels.

23. 23 Disadvantage of Cluster-based Approach Non-optimal under certain terrain conditions.

24. 24 Several Sensors Electing Themselves Obstacle Allow a cluster-head to switch on some number of child sensors in its cluster to do object location.

25. 25 Adaptive Fidelity Algorithms A Y Z quality of the answer can be traded against battery lifetime, network bandwidth, or number of active sensors.

26. 26 Tradeoffs Localized algorithms exhibit good robustness and scaling properties. May sacrifice resource utilization or sensing fidelity, responsiveness, or immunity to cascading failures.

27. 27 Directed Diffusion A novel data-centric, data disemmination paradigm for sensor networks. Data generated by sensor node is named using attribute-value pairs. A sensing task is disseminated throughout the sensor network as an interest for named data.

28. 28 Directed Diffusion This dissemination sets up gradients within the network designed to "draw" data matching the interest. Events start flowing towards the originators of interests along multiple paths. The sensor network reinforces one, or a small number of these paths.

29. 29 Directed Diffusion

30. 30 Directed Diffusion Allows intermediate nodes to cache or locally transform data. –leverages the application-specificity that is possible in sensor networks. The diffusion model’s data naming and local data transformation features capture the data-centricity and application- specificity inherent in sensor networks.

31. 31 Related Work Ad-hoc Networks –Proactive vs. reactive routing protocols Energy-efficiency issues Distributed Robotics –Robots cooperate to discover entire map Internet Multicast and web caching –Lightweight session

32. 32 Current Developments Smartdust project: –cubic millimeter sensors –Sensors float in air like dust WINS (wireless integrated wireless Sensors) WSN (Wireless Sensing Network) Odyssey Habitat monitoring The Cricket Indoor Location System