Fault Tolerant Sensor Network Routing for Patient Monitoring

1. Fault Tolerant Sensor Network Routing for Patient Monitoring Shanshan Jiang, Annarita Giani, Allen Yang, Yuan Xue, and Ruzena Bajcsy Vanderbilt University University of California at Berkeley TRUST Autumn 2008 Conference November 11th, 2008

2. Outline • Motivation • System and Network Architecture • System Prototype and Implementation • Network and Routing Model of the Backbone Network • Optimization-based Routing Restoration of the Backbone Network • Performance Evaluation

3. Motivation • Aging population • According to the U.S. Census Bureau, the number of people over the age of 65 is expected to hit 70 million by 2030, having doubled since 2000. • Health care expenditures • Health care expenditures in the United States are projected to rise to 15.9% of the GDP ($2.6 trillion) by 2010. • The cost of health care for the nation’s aging population has become a national concern.

4. Motivation • Wireless Sensor Networks • Deploy wearable sensors on the bodies of patients in a residential setting • Continuously monitor physiological signals (such as ECG, blood oxygen levels) and other health related information (such as physical activity) • Advantages • Shift from a clinic-oriented, centralized healthcare system to a patient-oriented, distributed healthcare system • Reduce healthcare expenses through more efficient use of clinical resources and earlier detection of medical conditions • Challenges • Performance, Reliability, Scalability, QoS, Privacy, Security … • More prone to failures, caused by power exhaustion, software and hardware faults, natural disasters, malicious attacks, and human errors etc. • Provide fault-tolerant wireless communication that can satisfy • both the performance and reliability requirements

5. Outline • Motivation • System and Network Architecture • System Prototype and Implementation • Network and Routing Model of the Backbone Network • Optimization-based Routing Restoration of the Backbone Network • Performance Evaluation

6. System and Network Architecture

7. System and Network Architecture Lower Tier: Body Sensor Network Upper Tier: Multi-hop Wireless Backbone Network

8. Outline • Motivation • System and Network Architecture • System Prototype and Implementation • Network and Routing Model of the Backbone Network • Optimization-based Routing Restoration of the Backbone Network • Performance Evaluation

9. System Prototype and Implementation • Hardware Devices • Software Design

10. System Prototype Experiment

11. Outline • Motivation • System and Network Architecture • System Prototype and Implementation • Network and Routing Model of the Backbone Network • Optimization-based Routing Restoration of the Backbone Network • Performance Evaluation

12. Network Model of the Backbone Network • Backbone Network Performs Sensor Data Routing and Forwarding • Network and Interference Model • Topology: G=(V, E) • All nodes have a uniform transmission range and interference range • Two edges interfere with each other if they have two nodes within the interference range of each other • Traffic Demand Model • df is the traffic demand of flow f, which is an aggregation amount of all the sensor data received at the sender of flow f • Be routed over multiple paths • xf(e) denotes the amount of flow f’s traffic being routed on link e Backbone Network

13. Routing Model of the Backbone Network • Metric for routing performance • Minimum Flow Throughput Scaling Factor • The minimum, over all flows, of the actual flow throughput being routed divided by its throughput demand • Optimal Routing Formulation amount of traffic received at the destination node rf wireless channel constraint (necessary scheduling condition) flow conservation conditions

14. Outline • Motivation • System and Network Architecture • System Prototype and Implementation • Network and Routing Model of the Backbone Network • Optimization-based Routing Restoration of the Backbone Network • Performance Evaluation

15. Optimization-based Routing Restoration • Discover Alternate Paths Bypassing the Failed Nodes • Reactive Restoration • Not reserve any network resource • Deal with failures only when they occur through network resource reallocation • Application • Resource-limited System that allows performance degradation upon failures • Proactive Restoration • Reserve additional resources a priori • Provide certain performance assurance for the rerouted flows with a shorter restoration time • Application • Life-critical System • Admission Control • Result in a lower network utilization before failure occurs • Need to know the worst-case node failure situations

16. Optimization-based Routing Restoration Increase Increase • Global Restoration • All flows will be rerouted in order to get an optimal utilization of the network • All flows have to be notified with the failure information • End-to-end Restoration • The flows from the failed path will be diverted to a number of paths from its source to the destination • Failure information has to be propagated to the source nodes of the disrupted flows • Local Restoration • Uses a set of bypaths to route around the failed node locally • The restoration is locally activated Repairing Time During Restoration Network Performance after Restoration

17. Optimization-based Routing Restoration • Global Restoration • End-to-end Restoration: (1) Calculate Unaffected Flow Truncations (2) Optimal Flow Augmentation Restoration Formulation • Local Restoration: (1) Calculate Bypass Flows (2) Optimal Bypass Restoration Formulation

18. Outline • Motivation • System and Network Architecture • System Prototype and Implementation • Network and Routing Model of the Backbone Network • Optimization-based Routing Restoration of the Backbone Network • Performance Evaluation

19. Performance Evaluation Simulated Backbone Network

20. Conclusion • Three-Phase System Architecture • Two-Tier Data Collection Network • Routing Restoration of the Backbone Network • Based on optimization theory and linear programming approach • Reserve network resource or not • Proactive Restoration • Reactive Restoration • Restoration scale • Global Restoration • End-to-end Restoration • Local Restoration