Software Development for Atom based Safe and Sustainable BSN IMPACT LAB Project Report on “Safe, Secure and Sustainable Body Area Networks using Intel Atom” funded by Intel

Impact Lab Research Goal Environmentally Aware (physical), Performance aware (cyber), Criticality Aware, Safe and Secure Cyber-Physical Systems Body-Area Sensor Networks Objectives Minimize energy consumption Minimize health risks (safety) Ensure security and privacy Allow complex applications Approach Infuse energy awareness Introduce high computation AADL modeling Taxi Cab Scheduling Objectives Compute optimal route with targets Minimize fuel consumption Evaluate solutions Approach Design proactive, spatio- temporal schedules AADL modeling Data Centers Objectives Minimize Energy Consumption Maintain Performance Approach Integrated Management Infuse Proactive Spatio- Temporal Scheduling AADL Modeling

Project Goal 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 Software Design of Computationally capable Safe and Sustainable Atom based BSN

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

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 Requirements  Response within a small time window  Fast Computation of windowed FFT and associated signal processing Security  Physiological Value based Security [3]  Combines signal processing with security algorithms Requirements Hogs up 80 % of total RAM Continuous Monitoring  Seamless 24 hrs medical monitoring [2] Requirements  Increased lifetime of the sensors  Battery less non-intrusive operation Figure explains PVS Implementation 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 4 th Intl. Conference on Body Area Networks, Apr 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 K. Venkatasubramanian et al. Plethysmogram-based secure inter-sensor communication in body area networks. Military Communications Conference, IEEE, pages 1–7, Nov.

Proposed BSN System Future 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

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

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)

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 Typical BSN Workload Ayushman PhaseRate of Execution Sensing 60 samples per second Data Transmission every 5 seconds PKA executionOnce in 24 hrs (the processor can sleep during sensing phase while it can be active during the transmission phase) Sensor CPU Utilization Time Sensing Phase Transmission Phase Security Phase Sleep Cycle Ayushman Workload Enables Sleep Scheduling Frequency Throttling during security phase

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 Management Strategies for Safety and Sustainability 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 Intelligent design is required to achieve safety and sustainability while respecting the real time requirements of the applications The strategies are closely related to the applications real time requirements.

Software Design Methodology

BSN Hardware model Base Station BSN Node 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, wireless standard  Maximum Power dissipation (58 mW [4]) 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 Wireless Charging Base Station  Atom based mobile phone

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

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

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 C6 Sleep StateRun Ayushman Turn On GMCH board Read MSR Log Temperature Data Set Operating Frequency Thermal profiling methodology

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 Power Profiling AC Mains Power Meter Intel Atom N270 on Mobile Intel Chipset 945 GSE Operating Mode (Percent throttling) Power (W) , 50, 62, Power Measurement Set up Table showing Atom power consumption for PKA execution at different operating frequencies Board Power Lead

Resource Consumption PlatformRAM Usage Power (mW) Computation Time (ms) TelosB80% Atom0.006%16441 Resource Consumption for PKA execution 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

Modeling Phase Industry Standard AADL language is used for modeling

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 -

Sustainability Analysis Duty Cycling of Atom operation during Ayushman execution  Sleep mode (C6) during Sensing Phase Power consumption = P sleep for time t s  Active mode during data transmission phase Power consumption = P active + radio power P radio for data transmission time t tx  Active mode during PKA execution Power Consumption = P active + PKA execution power P PKA for time t PKA  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 = P active + P radio for time t vault  Total energy consumption for n BSN nodes  x is the number of sleep cycles required in a day Total EnergySensing Energy Transmission Energy PKA communication Energy (Pair wise PKA) PKA Computation Energy (Pair wise PKA) Total Sleep Cycle Time Pair wise PKA Execution Time

Sustainability Analysis Results Four energy scavenging sources were considered  Body Heat, Ambulation, Respiration and Sun Light PM – Processor and radio sleep scheduling NPM – Radio sleep sche- ling NPNM – no sleep schedule Scavengin g Source Available Power (W) Scavenge Time (Hrs) Body Heat0.1 – Ambulation1.52 Respiration0.426 Sun Light0.13

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

Problems Faced Inaccuracies in Thermal Profiling  Presence of heat sink on the Atom processor can cause additional thermal effects which are not accounted for in the analysis  Reliability of thermal sensors not known Inaccuracies in Power Profiling  Available board was used to determine the power consumption of Atom  The power consumption may include several other components in the board  The sense resistors across which power can be measured were not found due to lack of documentation Require stripped down version of Atom based development boards Options to turn off components of the board has to evaluated

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