Sustainability – A Body Sensor Network Example

1. Sustainability – A Body Sensor Network Example IMPACT LAB Excerpt of a Project Report on “Safe, Secure and Sustainable Body Area Networks using Intel Atom” funded by Intel

2. Sustainability • Sustainability can be defined from two perspectives • Energy perspective • Percentage of energy obtained from green sources for operating the computing systems. • Number of computing units completely powered by green sources. • Equipment recycle perspective • Reusability and longevity of the computing units

3. Considerations for energy perspective • Energy Efficiency • Developing low power computing systems • Using strategies to distribute workload for achieving energy efficiency • Power management of non-computing systems • Green Energy • Harvesting of energy from green sources such as solar power • Energy Storage • Store the harvested energy for just in time use

4. Energy Sustainability • Power consumption and energy availability problem

5. Storage and replenishment • Energy storage and replenishment

6. Challenges • Efficiency of energy extraction from scavenging sources. • Low cost extraction of energy • Storage inefficiency • Energy is stored in ultracapacitors • Leakage in capacitors causes energy wastage • Storage limit • Energy Reuse • Extract energy from the heat dissipated as side effect of computing

7. Approach • Model based engineering for sustainability • Definition of scavenging source • (ρ,σ1,σ2) tuple defines a scavenging source • ρ is the constant power supply model • σ1 is the lower limit • σ2 is the upper limit • If P(t) is the power obtained from the scavenging souce at any time then we have, Average case – σ1 and σ2 are zero. Performance Aware Tasking for Environmentally Powered Sensor Networks by AmanKansal, Dunny Potter and Mani B Srivastava

8. Theorem 1 • Sustainable performance at eternity (constant power operation) • If a device is supplied by a power source (ρ,σ1,σ2) • Operates at constant power ρ • Has a storage capacity of σ1 + σ2 • Then • The energy source is utilized fully • Device can operate with that energy source uninterruptedly for eternity

9. Theorem 2 • Definition of variable power source consumer • Consumer (ρ’,σ) has a power consumption which satisfies the following equation for any value of T • Theorem 2 – If • a consumer (ρ’,σ) is supplied by a source (ρ, σ 1σ2) • Has a storage capacity of (σ + σ1 + σ2) and • ρ’ < ρ • Then the device can operate forever.

10. Energy Flow Data & Control Flow Design & Verification Flow Holistic Model Based Design Sustainability Verification CPS Resource Management Computing Power Management Computing Workload Management Physical Entity Management Model- based Analysis CPS Power Profile CPS Behavior Analysis Computing Component Power Profile Physical Component Power Profile Interdependency Profile of Computing and Physical Component Power Simulation/Experimental Evaluation Modeling CPS Behavior Cyber-Physical Interactions Physical Components Computing Components Cyber-Physical System (CPS) Energy Sources Physical Environment External Physical Components Research Directions in Energy-Sustainable Cyber-Physical Systems by Sandeep K. S. Gupta, Tridib Mukherjee, GeorgiosVarsamopoulos, and Ayan Banerjee, http://impact.asu.edu/publication/EnergySustainable.pdf Workload

11. Example – Body Sensor Networks • Body Sensor Networks (BSNs) – network of medical devices on human body are small scale cyber-physical system • Critical infrastructures – used in medical applications • Require to support life saving applications • Involvement of human users require BSNs to be safe (reduce medical hazards) and sustainable (provide seamless operation) • Complex application requirements (especially security protocols) demand powerful processors in BSN nodes • Atom is used as the BSN node processor to provide required computational capabilities • However, higher power dissipation of Atom, hampers the safe and sustainable operation of BSN nodes Design of Computationally capable Safe and Sustainable Atom based BSN

12. Traditional Body Sensor Network • Salient Features • Computationally incapable set of nodes • Heterogeneous hardware and software configuration • Constrained in energy – battery operated • No energy scavenging Present

13. Application requirements • Monitoring and Feedback • Online detection of freezing of gait [1] in Parkinson’s patients from on-body sensors • Feedback through on-body actuators • Continuous Monitoring • Seamless 24 hrs medical monitoring [2] • Requirements • Response within a small time window • Fast Computation of windowed FFT and associated signal processing • Requirements • Increased lifetime of the sensors • Battery less non-intrusive operation • Requirements • Security • Physiological Value based Security [3] • Combines signal processing with security algorithms Highest power consumption References 1. M. B¨achlin et al. Online Detection of Freezing of Gait in Parkinson’s Disease Patients: A Performance Characterization. In Proc. of the 4th Intl. Conference on Body Area Networks, Apr. 2009 2. K. Venkatasubramanian et al. Ayushman: A Wireless Sensor Network Based Health Monitoring Infrastructure and Testbed. In Distributed Computing in Sensor Systems, pages 406–407, July 2005 3. K. Venkatasubramanian et al. Plethysmogram-based secure inter-sensor communication in body area networks. Military Communications Conference, 2008. IEEE, pages 1–7, Nov. Figure explains PVS Implementation

14. Proposed BSN System • Computationally capable sensors • Use Intel Atom as the sensor processor • Addresses the computational requirements of the present day applications • Homogeneous hardware and software platform • Sensors running intel atom can have stripped down versions of the same OS kernel • Resolves software compatibility issues • Energy Scavenging • Incorporate energy scavenging hardware in the network to sustain operation of the sensors • Supplement battery power • Makes the BSN system greener Future

15. Challenges of Atom based BSN Atom can provide a uniform platform with highly capable BSN processors Challenges with Atom - sustainability • Energy Efficiency • Relatively higher power footprint of Atom • Thermal Safety • Possible high thermal footprint of Atom • Lifetime • How long can energy scavenged from human sources sustain Atom operation ?

16. Sustainable design of BSN Design & Verification Flow Data & Control Flow Energy Flow Sustainability Verification BAN Resource Management • Schedule sensing • Schedule communication • Schedule key agreement • Strategy for allocation of scavenged energy to sensor nodes • Strategy to reduce operating temperature • Radio sleep • Processor duty cycling • Processor frequency control Model-based Analysis BAN Power Profile Power consumption of Sensor Nodes Human body thermal properties Heat transfer process Simulate power consumption and available power from scavenging sources Analysis of temperature of human skin Scavenging sources power profile Average available power Thermal Model of BAN Heat Energy Transfer Sensor Nodes Human Body Scavenged Energy Energy Scavenging Sources Network of Sensors on Human Body Ayushman Workload Peizoelectric devices on Shoe soles

17. Atom background • Ultra low power processor for embedded applications • However, order of magnitude higher power dissipation than the state-of-art BSN node • IA-32 microarchitecture helps in easy application development • Can use high level programming languages to develop applications • Six low power sleep states with ultra low power deep sleep state • Sleep scheduling can be employed to reduce power consumption • Intel Speed Step technology enables seven different operating frequency levels • Clock frequency control to reduce operating power • Sleep state and frequency control performed through easy ACPI support (through Model Specific Register (MSR) accesses)

18. Typical BSN Workload • Ayushman [2] health monitoring application is considered as the workload • Ayushman has three phases of operation – • Sensing Phase – Sensing of physiological values (Plethysmogram signals) from the sensors and storing it in the local memory • Transmission Phase – Send the stored data to the base station in a single burst • Security Phase – Perform network wide key agreement for secure inter-sensor communication using Physiological value based Key Agreement Scheme (PKA) [3]. • The Security phase occurs once in a day • The Sensing phase and Transmission phase alternate forming a sleep cycle • (the processor can sleep during sensing phase while it can be active during the transmission phase) Ayushman Workload Frequency Throttling during security phase Sensing Phase Enables Sleep Scheduling Transmission Phase Sleep Cycle Sensor CPU Utilization Security Phase Time

19. PPG Values PPG Values cfi,di SENSOR 2 SENSOR 1 PKA Algorithm Radio Off Sensing Sensing Time Time FFT Values FFT Values Radio On FFT FFT Index Index Peak Values Peak Values Peak Detection Peak Detection Index Index Quantize Quantize Fs = [fs1 fs2 …….. fsn] Fr = [fr1 fr2 …….. frn] p(fs1) Polynomial Generation and evaluation p(fs2) p(fsn) fs1 fsn fs2 Adding Chaff R Receive Vault Transmit Vault p(x) Lagrangian Interpolation Receive Acknowledgement Transmit Acknowledgement

20. Strategies to Address – Safety and Sustainability Challenges • Challenge - Atom’s high TDP (2.2 W) with respect to present day sensor nodes (~ 80 mW [4]) • Remedy – Power budgeting through sleep scheduling and clock frequency control • Road Blocks – • In a sleep mode the processor cannot compute • Decrease in clock frequency increases computation time • Challenge - Increase lifetime of operation • Remedy – include scavenging nodes in the BSN that will charge the Atom nodes wirelessly and supplement battery • Road Blocks – • The operation of scavenging sources are intermittent depending on the stochastic behavior of the host • Often the scavenging nodes fail to provide appropriate power levels to the nodes The strategies are closely related to the applications real time requirements. 4. K. Venkatasubramanian et al. Green and sustainable cyber-physical security solutions for body area networks. In BSN ’09: Proc. of the Sixth Intl. Workshop on Wearable and Implantable Body Sensor Networks, pages 240–245, Washington, DC, USA Intelligent design is required to achieve safety and sustainability while respecting the real time requirements of the applications

21. BSN Hardware model • BSN node • Intel N270 single core processor • 1.6 GHz clock frequency, 1 GB RAM • Intel SpeedStep frequency control technology – useful for power management • 6 sleep states including one ultra low power sleep state (C6) – sleep scheduling • Chipcon 2420 radio • 2.45 GHz, 802.15.4 wireless standard • Maximum Power dissipation (58 mW [4]) BSN Node Base Station • Base Station • Atom based mobile phone Wireless Charging • Scavenging Sources • Body Heat, Ambulation, Respiration and Sun Light • Wireless charging of BSN nodes from scavenging sources is assumed • Each source has a specified range upto which it can charge nodes Scavenging Sources

22. BSN node Software • The power consumption of Atom processor depends on the Operating System used • Mobile Intel 945 GMCH board power consumption • Open Suse Linux = 11.7 W • Moblin OS = 10.4 W • ACPI support required for accessing Intel SpeedStep frequency control and sleep states • Moblin provides ACPI through which one can write to or read appropriate MSR registers to – • Control clock frequency • Sleep States • Measure core temperature • The BSN workload considered is the Ayushman application

23. Profiling Requirements • Thermal Safety – The maximum temperature of the skin in contact with the node should not exceed 39 ºC for 24 Hrs of operation • Thermal behavior of Atom under the given workload has to be evaluated • Sustainability – The available power from the scavenging sources should be able to meet the power demands of Atom node under the given workload • Power profiling of Atom processors during execution of Ayushman

24. Thermal Profiling • Requires core temperature measurements for different operating points of the Atom processor • The Mobile Intel 945 GSE development platform (GMCH) provided by Intel has digital thermal sensors • The board thermal sensors were read from Model Specific Registers • The maximum core temperature (43 ºC) was observed during PKA execution Turn On GMCH board Set Operating Frequency Read MSR C6 Sleep State Run Ayushman Log Temperature Data Thermal profiling methodology

25. Power Profiling Power Meter • PKA is the most power consuming computation in Ayushman [3] • The difference between idle power and power during PKA execution was measured using the GMCH board • Idle power of Atom N270 processor was added to it to obtain PKA power consumption Board Power Lead Intel Atom N270 on Mobile Intel Chipset 945 GSE AC Mains Table showing Atom power consumption for PKA execution at different operating frequencies Power Measurement Set up

26. Resource Consumption • PKA computation in Ayushman involves signal processing of physiological signals as well as execution of security algorithms • Resource footprint of PKA is evaluated in terms of – • RAM usage, Power Consumption, and Computation Time • Atom compared to TelosB provides very low RAM usage and computation time • However as expected it has around thrice the power consumption Resource Consumption for PKA execution

27. Safety Analysis • The temperature rise of human skin due to contact with Atom based BSN node has to be evaluated • The temperature rise occurs due to several physical phenomenon and is modeled using the Penne’s bioheat equation - Skin Temperature Radio Power Atom Power Consumption Atom Operating Temperature Heat accumulated Heat transfer by conduction Heat transfer by convection Heat by electromagnetic radiation Heat by power dissipation Heat by radiation Thermal damage parameter calculated according to Henrique and Moritz [5]. Maximum temperature must not exceed this. 5. F. C. J. Henriques et al. Studies of thermal injury: I. the conduction of heat to and through skin and the temperatures attained therein. A theoretical and an experimental investigation. In Am J Pathol., pages 530–549, July. 1947.

28. Sustainability Analysis • Duty Cycling of Atom operation during Ayushman execution • Sleep mode (C6) during Sensing Phase • Power consumption = Psleep for time ts • Active mode during data transmission phase • Power consumption = Pactive + radio power Pradio for data transmission time ttx • Active mode during PKA execution • Power Consumption = Pactive + PKA execution power PPKA for time tPKA • PKA involves transmission of security related information (vault) between two sensors • The Atom processor must be in active state with the radio on. Power Consumption = Pactive + Pradio for time tvault • Total energy consumption for n BSN nodes • x is the number of sleep cycles required in a day Total Energy Sensing Energy Transmission Energy PKA Computation Energy (Pair wise PKA) PKA communication Energy (Pair wise PKA) Total Sleep Cycle Time Pair wise PKA Execution Time

29. Sustainability Analysis Results • Four energy scavenging sources were considered • Body Heat, Ambulation, Respiration and Sun Light • Three energy efficient techniques used • processor level sleep scheduling and communication (radio sleep) scheduling (P-M), • no processor level sleep scheduling but with communication scheduling (NP-M), and • no processor level sleep scheduling or communication scheduling (NP-NM). • Here we consider the average case power consumption of the scavenging sources. • Variance in the power availability can be captured using the theory discussed earlier.

30. Sustainability Results

31. Conclusions • Proper Sleep scheduling and Frequency throttling can be used to bring Atom’s power consumption to safe and sustainable levels • Atom based BSNs with upto 25 nodes can be sustained using scavenged energy from body heat and respiration • A model based engineering tool has also been developed in this process • It uses industry standard AADL to model • Analysis of Model is performed through an eclipse interface by developing java based plug-ins

32. Thank You