Next Century Challenges: Scalable Coordination in Sensor Networks

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. 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. 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. Applications: Environmental Analysis

5. Applications: Contaminant Flow Monitoring

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. Applications: Biological Systems

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

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

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

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

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

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

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

20. Base-line Estimation

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

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

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

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. 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. Directed Diffusion

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. 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. 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