Energy Neutral Systems CSE 591 – Green Computing

Randomness in Available Energy Intermittent energy supply Depends on the environment Solar cells produce energy only in the day time Cloudy weather hampers energy production Statistical variance in available power The scavenging sources put a cap on the instantaneous power and not on energy Principal difference from the batteries, which put a cap on the energy.

Shift in Design Consideration Energy efficiency alone is not enough Optimized power profile is more important System design under an energy constraint is no longer valid The energy constraint itself varies over time, given the randomness in the energy source More relevant design objective – Perpetual energy neutrality – Maximize the performance of a system without depleting the battery ever

System Model Battery Scavenging Source Scavenging Source Computing Scavenging source generates energy The computing system uses the energy from the scavenging source to perform computational tasks Scavenging source generates energy The energy is used to charge a battery The computing system uses the energy from the battery to perform computational tasks Computing System Computing System

Scavenging Source Metrics Design considerations – Conversion Efficiency – Percentage of energy available from the source that can be used as electrical energy for powering systems Cost constraints Form factor constraints Technology constraints E.g. Solar cells have a conversion efficiency of 5% Reliability – Failure to supply power, uncontrolled power supply E.g. scavenging from ambulation has low reliability

I-V characteristics Battery Scavenging Sources Voltage sources Limit on the current drawn (Irating) Current depends on the load across the battery Current sources Limit on the voltage supplied The operating point, both voltage and current depends on the load Highest Instantaneous power Voltage (V) Current (A) Voltage (V) Aim – Operate in the Maximal Power Point (MPP) Harvesting Aware Power Management for Sensor Networks by Aman Kansal, Jason Hsu, Mani B Srivastava, and Vijay Raghunathan

Techniques for using harvested energy Adjust the load on the scavenging source. Use a current switch in the circuit Essentially a voltage regulator or a transformer. Allow the scavenging source to operate in the MPP The voltage or current is then scaled according to the load using the switch Inefficiencies – The switching circuit itself draws power Leakage current of the transformer will cause wastage of power. Storage of scavenged energy Use fuel cells or ultracapacitors Round trip efficiency – Percentage of energy lost in storing in the capacitor or battery and then transferring for use. Main cause is the leakage of energy Depth of Discharge (DoD) – The residual battery capacity just before it is recharged The lifetime of a battery increases exponentially with increasing depth of discharge System level workload scheduling Schedule workload to match the available power profile from the sources.

Harvesting theory Energy Neutrality – A system is energy neutral, for a given time t, if the energy stored in the battery after the system operation for time t is greater than or equal to the previous. Mathematically, if is the battery energy at time t = 0 and is the battery energy after time t. If then the system is energy neutral If then the system is perpetually energy neutral

Modeling of harvesting system is the power obtained from a scavenging source is the efficiency of the storage (fraction of usable electrical energy ) is the leakage power is the power consumed by the computing unit For a given time t, if , then the storage unit stores energy Else the storage unit gets depleted of the energy From the stored energy only a fraction can be used to power computing units

Energy Neutrality Criteria Amount of energy stored from scavenging sources Amount of energy depleted from storage units due to lack of scavenged energy Amount of energy depleted from storage units due to leakage Previously stored energy Harvesting Aware Power Management for Sensor Networks by Aman Kansal, Jason Hsu, Mani B Srivastava, and Vijay Raghunathan

Scavenging Source Definition of scavenging source (ρ1,σ1,σ2) tuple defines a scavenging source ρ1 is the constant power supply model σ1 is the upper limit σ2 is the lower limit If Ps(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 Aman Kansal, Dunny Potter and Mani B Srivastava

Power source consumer Definition of variable power source consumer Consumer (ρ2 ,σ3 ) has a power consumption which satisfies the following equation for any given time T

Theorem – Energy Neutral Operation The sufficient conditions for a system to be energy neutral are – Here Bmax is the storage capacity while B0 is the initially stored energy

System Performance Characterization Utility – A function of duty cycling Example - speed tracking sensors

Performance maximization objective Maximize average utility Constraints – Energy consumption model Energy neutrality constraint Performance constraint

Prediction of available power The optimization assumes that the available power is known before hand However, scavenged power depends on several environmental factors along with diurnal variations Exponentially weighted predictive function where is a historically weighted function for the energy available from solar source and x(i) is the current amount of available energy

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 Ayushman Phase Rate of Execution Sensing 60 samples per second Data Transmission every 5 seconds PKA execution Once in 24 hrs (the processor can sleep during sensing phase while it can be active during the transmission phase) This slide is there to show how the strategies mentioned in the previous slide can be used in Ayushman application to reduce the energy consumption The workload timeline provided in the figure can be used to explain the opprtunity to schedule sleeping cycles of the processor. Due to loose real time requirements on the PKA execution the frequency of the Atom processor can be throttled. Sensor CPU Utilization Time Sensing Phase Transmission Phase Security Phase Sleep Cycle Ayushman Workload Enables Sleep Scheduling Frequency Throttling during security phase

Sustainability Analysis of Atom 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

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. Scavenging Source Available Power (W) Scavenge Time (Hrs) Body Heat 0.1 – 0.15 24 Ambulation 1.5 2 Respiration 0.42 6 Sun Light 0.1 3

Sustainability Results

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