Autonomic Wireless Sensor Networks: Intelligent Ubiquitous Sensing

1. Autonomic Wireless Sensor Networks: Intelligent Ubiquitous Sensing G.M.P. O’Hare, M.J. O’Grady, A. Ruzzelli, R. Tynan Adaptive Information Cluster (AIC) Group, University College Dublin, Ireland.

2. Summary • Wireless Sensor networks (WSNs) • Generality • Prototypes • Applications • Requirements • Autonomic computing • Properties • Autonomic WSNs • Agent technology in WSNs • Autonomic network management • Intelligent power management • Intelligent communication and routing • Intelligent network coverage • Conclusion

3. Energy-Efficient Wireless Sensor Networks (WSNs) • A large number of tiny wireless devices to sense the environment: • Sensor nodes • Few more powerful devices to collect the data: • Gateways (or sinks) PDA, laptop, PC etc.

4. Some WSN applications environmental data collection: temperature light, humidity, pressure, solar radiation. Wind Response Of Golden Gate Bridge • Remote area monitoring • Object location • Industry machinery monitoring • Disaster prevention • Wireless medical systems

5. Wireless sensor characteristics WSN manager • Sensors are of : • Low cost • Low processing capability •  System strength based on sensor collaboration • Large scale networks • Multihop communication • Sensors are battery operated for long unattended period: •  Saving energy is a primary objective

6. WSN issues • Large number of nodes Scalability issues • High dynamic condition (number and position of nodes might change) Network Reactivity and Self-organization • Power management The network need to be connected as long as possible • System reliability • The wireless signal might be subjected to interference • Robustness • Subject to environmental variability • Complex interoperability of network devices

7. Sensor node prototypes Mica2 mote Tyndall sensor Eyes node prototype Philips sand nodes

8. General wireless sensor network architecture: Sensing devices Application Data interpolation Sensing coverage Localization Cross layer interaction Routing MAC Physical Antenna • Any layer try to achieve the task using the smallest amount of energy possible

9. Autonomic WSNs: • Origin of autonomic computing by IBM Relieve human of the burden of managing large scale computer systems • Autonomic WSNs properties: • Self healing • Self protection • Self configuration • Self optimization • Self managing

10. Agent technology for autonomic WSNs • Agent properties: • Sense-deliberate-act cycle • Sensing data is used as input for the decision making process • Mobility • Useful characteristic of agents that well map onto WSNs • Agent can migrate from one node to another processing data as it goes • Fault tolerance • Agents can still take decision if some data are missing

11. An example: Network anomaly intervention Possible solution Multiple Notification messages (High energy consuming) Proposed solution: Migrating agent (Moderate energy consuming)

12. Contribution of autonomic computing to WSNs • Self configuring nodes (1) can set up a network; (2) might not be well positioned but still work; (3) can evaluate network gaps; (4) can decide communication schedule. • Self protection attribute • Migrating agents check channel condition and battery level before migrating • Self healing • Repair network damage due to hash work condition • Negotiating new routes; • Activating redundant nodes; • Ask for replacement of damaged nodes. • Self optimization • Quality of service • Network efficiency • Delay control and data prioritization

13. Intelligence-aided sensor network • Opportunistic power management • Intelligent coverage • Intelligent routing

14. Opportunistic power management (1) • Increase network longevity by deactivating redundant nodes: node hibernation • Sensing Coverage: • All points within the sensed area need to be covered by at least 1 sensor. Traditionally, a point is covered if it is within the sensing range of a given sensor. Gateway Redundant based on sensor coverage

15. Intelligent sensing coverage • It deals with the quality of sensory data provided to the application which is using it; • Data sampling frequency at the node and surrounding nodes should be enough to have a certain detail of the phenomena of interest; • Migrating agents control: • Sensor sampling rate by tuning it; • Might request an increase of node density in an area

16. Intelligent routing • By interacting with different layers the agent can check several parameters • A look-up table with neighbouring nodes parameters (RSSI, battery level, location) is provided • Even with incomplete data an agent can figure out the best neighbours to which to forward the data to Routing table Route managing Agent MAC Physical Antenna

17. Conclusion • A methodology for the automation of the sensor network technogy has been presented; • WSNs offer significant potential in numerous application domains • Given the diverse nature of such domain, robustness and reliability is essential; • The method outlined exploits the integration of autonomic principles into design and operation of WSNs • Autonomic WSN can effectively both enhance the network reliability and extend the network lifespan.

18. Thank you! www.csi.ucd.ie/research(Prism LAB web site) www.adaptiveinformation.ie (project)