tinyos concurrent execution and power control n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
TinyOS: Concurrent Execution, and Power control PowerPoint Presentation
Download Presentation
TinyOS: Concurrent Execution, and Power control

Loading in 2 Seconds...

play fullscreen
1 / 53

TinyOS: Concurrent Execution, and Power control - PowerPoint PPT Presentation


  • 83 Views
  • Uploaded on

TinyOS: Concurrent Execution, and Power control. Class 9. Announcements. Sign up for the weeken d classes Review phase 1 requirements Each group update TA on your progress with TinyOS installation . Agenda. TinyOS multi-threading Radio duty cycling Power management in sensors.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'TinyOS: Concurrent Execution, and Power control' - vesna


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
announcements
Announcements

Sign up for the weekend classes

Review phase 1 requirements

Each group update TA on your progress with TinyOS installation

agenda
Agenda

TinyOS multi-threading

Radio duty cycling

Power management in sensors

tinyos multi threading
TinyOS multi-threading

TinyOS is a single application OS

It supports multi-threading for the application

Several threads can be posted in parallel which get scheduled in a FIFO queue

Tasks and events are primarily used for doing computation

Tasks are for long running computations

Events are used for very short computation and for posting long running computations in the FIFO queue

slide5

Concurrent execution

  • uint16_t Samples[SAMPLES];
  • Uint16_t i = 0;
  • event void ReadStream.readDone(error_t ok, uint32_t SensedVal) {
  • if (ok == SUCCESS){
  • i++;
  • Samples[i] = Val;
  • if(i == SAMPLES-1){
  • i = 0;
  • post calculateAvg();
  • }
  • }
  • }
  • task void calculateAvg() {
  • uint16_t i, avg, var;
  • for (avg = 0, i = 0; i < SAMPLES; i++)
  • avg += Samples[i];
  • avg /= SAMPLES;
  • for (var = 0, i = 0; i < SAMPLES; i++)
  • {
  • int16_t diff = Samples[i] - avg;
  • var += diff * diff;
  • }
  • }

In readDone, we need to compute the variance of the sample. We defer this “computationally-intensive” operation to a separate task, using post.

We then compute the variance

exercise to understand concurrency
Exercise to understand concurrency

Lets have a loop in a task

Increment a counter

Have a timer fired event where at each fired event we send the counter value to the base station

What values do we see at the base station ?

code flow diagram
Code Flow Diagram

Booted

Boot

Start Radio

StartDone

Call Timer

Only the first task gets done

FIFO scheduler gives preference to events

TimerFired

Call Sensor

Task gets pushed back in the queue

ReadDone

Post 10 tasks

code from last class
Code from last class

How to efficiently duty cycle radio ?

  • Event based radio turn off
    • Not duty cycling
  • Duty cycling: Having a fixed schedule of radio off and on states
  • Depends on several factors:
    • Application communication and computation patterns
    • Emergency communication requirements
    • In case of networks, base station might sleep when a sensor sends a packet
      • Leads to packet loss
lets go step by step
Lets go step by step
  • Consider 3 sensors
    • One base station A
    • Two sensor nodes B and C
    • C communicates its data to B and B forwards it to A
  • The sensors periodically broadcasts messages to their neighbor
  • All the sensors want to sleep
  • Design a strategy to duty cycle the radio so that no packet is lost
solution
Solution

Sleep

Sensor C

Awake

Sensor B

Sensor A

Synchronous sleep

next step
Next Step

Consider 4 sensors

A collects data from B

Adjusts it sleep according to B’s sleep schedule

D collects data from C and adjusts its sleep according to C’s sleep schedule

Design a sleep schedule so that A can send data to D

solution1
Solution

Sensor B

Sensor A

Sensor D

Sensor C

For two sensors to communicate their the sender should know the receiver’s sleep schedule

generic solution to duty cycling
Generic solution to duty cycling
  • Each sensor keeps a table of its sleep schedule
  • Each sensor then sends the table to all its immediate neighbors
  • The sensors then start their sleep schedule
  • When sensor A wants to communicate with B
    • A waits for B to wake up and then transmits
    • Once a transmission is started none of the sensors sleep until the transmission is finished
  • When finished both the sensors resume their sleep schedule
smac sensor medium access control
SMAC- Sensor Medium Access Control
  • Need an energy efficient MAC protocol
  • Design considerations –
    • Level 1 issues
      • Collision avoidance-a basic task of MAC protocols
      • Good scalability – sensors may die or new sensors maybe added
      • Energy efficiency
        • Often difficult recharge batteries or replace them
        • Prolonging the life-time is important
    • Level 2 issues
      • Latency, fairness, throughput, bandwidth
collision avoidance
Collision Avoidance
  • When more than one sensor wants to send packets to a receiver there can be collision
  • Use two flags –
    • Request To Send (RTS) – If a sensor wants to send a packet to the receiver it sends out an RTS.
    • Clear To Send (CTS) – The receiver on reception of the first RTS sends out a CTS to the sender allowing access to the channel
collision avoidance time diagram
Collision Avoidance Time Diagram

SYNC to synchronize sleep schedule

CS to sense the channel

overhearing avoidance
Overhearing Avoidance
  • Problem: Receive packets destined to others
    • In 802.11, each node keeps listening to all transmissions from its neighbors for virtual carrier sensing
    • Each node should overhear a lot of packets not destined to itself
  • Solution: Letting interfering nodes go sleep after they hear an RTS or CTS packet
  • Which nodes should sleep?
    • All immediate neighbors of sender and receiver
    • S-MAC lets interfering nodes go to sleep after they hear an RTS or CTS
      • DATA packets are normally much longer than control packets
  • How long?
    • The duration field in each packet informs other nodes the sleep interval
    • After hearing the RTS/CTS packet destined to a node, all the other immediate neighbors of both the sender and receiver should sleep until the NAV becomes zero
message passing
Message Passing
  • Problem: Sensor net in-network processing requires entire message
  • Solution: Don’t interleave different messages
    • Long message is fragmented & sent in burst
    • RTS/CTS reserve medium for entire message
    • Fragment-level error recovery — ACK

— Extend Tx time and re-transmit immediately if no ACK is received

  • Advantages
    • Reduces latency of the message
    • Reduces control overhead
  • Disadvantage
    • Node-to-node fairness is reduced, as nodes with small packets to send has to wait till the message burst is transmitted
aim to reduce energy
Aim to reduce energy

Main reason for radio sleep is to save energy

Why save energy ?

What are the different energy consumers ?

How to save energy ?

sources of power dissipation
Sources of Power Dissipation

Often more than computation

Least Power consuming

Most Power consuming

Power consumption depends on the type of processing

Sending <

Receiving

Communication energy more than 100 times greater than computation energy

Sensing + Computation + Communication

why power management
Why power management ?
  • Safety
    • Energy dissipation causes temperature rise
    • Sensors on body can cause physical harm
    • Sensors (Mean Time To Failure) MTTF decreases
  • Sustainability
    • Scarce and intermittent energy sources
      • Often energy is scavenged from the environment
    • Energy efficiency to reduce power supply needs
    • Matching power needs
power management strategies
Power management strategies
  • Sensing
    • E.g. pulse oximeter operation causes temperature rise on human skin
    • Temperature rise depends on the sensing frequency
    • Reduce the frequency to control temperature
    • Compressed sensing
power management strategies1
Power management strategies
  • Computation
    • Power consumption depends on different types of computation
    • Duty cycling of processor
      • Sleep states
      • Frequency scaling
      • Voltage scaling
    • Scheduling computation when energy is available
    • Predicting workload characteristics
      • Periodic vs asynchronous
      • Periodic workload enables efficient solutions
      • Async workload requires prediction which may fail often
    • Making energy available during peak workloads
power management strategies2
Power management strategies
  • Communication
    • Sending and receiving requires power from the energy supply
    • Communication power > 100 X computation power
    • Receiving power more than sending
  • Low power listening
  • Radio duty cycling
application dependency

EEG

Application dependency

EKG

BP

SpO2

Base

Station

Body Sensor Network

Motion

Sensor

  • Such strategies are however application dependent
    • Cannot turn off radio when the sensor needs to send
    • When an event occurs the radio has to wake up from low power state
  • Example Ayushman health monitoring system
ayushman workload
Ayushman workload

Ayushman Workload

Frequency Throttling during security phase

Sensing Phase

Enables Sleep Scheduling

Transmission Phase

Sleep Cycle

Sensor CPU Utilization

Security Phase

Time

  • Example: Ayushman health monitoring application is considered as the workload
      • 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.
    • The Security phase occurs once in a day
    • The Sensing phase and Transmission phase alternate forming a sleep cycle
effects of power management
Effects of Power Management

Power Profile (Radio-ON)

0.06

0.05

Receiver(Radio ON)

0.04

Sender(Radio ON)

0.03

0.02

0.01

1

2

3

4

5

6

7

Lagrangian

8

9

Poly Gen +

Vault Tx/Rx

FFT

Peak

+ Quant

Ackn Tx/Rx

Sensing

Add Chaff

Interpolation

Eval

Power Profile (Radio-OFF)

0.06

Receiver(Radio OFF)

0.05

Sender(Radio OFF)

0.04

Power (mW)

0.03

0.02

0.01

0

1

2

3

4

5

6

7

8

9

FFT

Peak

+ Quant

Sensing

Add Chaff

Vault Tx/Rx

Lagrangian

Poly Gen +

Ackn Tx/Rx

Interpolation

Eval

  • Periodic sensing and computation application in Ayushman
    • Sender Side: Sensing + FFT + peak detection + quantization + polynomial evaluation + random number (chaff) generation + data transmission + acknowledgement of transmission
    • Receiver Side: Sensing + FFT + peak detection + quantization + listen for packet + interpolation + transmit acknowledgement
energy savings
Energy Savings

PKA Computation Energy Consumption for Different Vault Sizes

0.7

Sender(Radio ON)

Sender(Radio OFF)

Receiver(Radio ON)

0.6

Receiver(Radio OFF)

Sensing power >> computation power

Sensing

0.5

0.4

Energy (Joules)

~100 mJ savings when radio turned off

0.3

0.2

0.1

0

1000

2000

3000

4000

5000

Vault Size (Chaff Points)

reduction of data transmission
Reduction of data transmission

Learn the characteristic of the sensed signal

Predict unusual changes

Send only when there are changes

  • To further reduce communication power we may avoid data transmission
  • Event based data transmission
    • Consider the context aware radio example in class
    • Light intensity below 10 is not interesting
    • So don’t send data
  • Another example –
    • Temperature data does not change too often
    • Quiz: What is an intelligent way to reduce transmission ?
    • Solution: Transmit only when there is a significant difference
complex signals
Complex signals
  • What happens when the signal is complex
  • Example: Electrocardiogram
  • Represents electrical activity of the heart
  • Consists of P, Q, R, S, T waves
  • The beat morphology and R-R intervals in an ECG are considered important for diagnosis
generative models
Generative Models

Actual Signal

Need to learn the parameters for a given signal

Given the parameters the model should be able to regenerate the signal

Each wave

represented by

a Gaussian function

z =

event based data transmission
Event Based data transmission

Normal

Expected Change

Unexpected Change

Morphology and inter beat features do not change

Both morphology and inter beat features change

Only inter beat features change

No communication

Use a generative model to represent ECG

Send inter beat feature updates

Send every sample

the methodology
The Methodology

Sensor matches sensed signal with model

If a match don’t send data

If model parameters vary, send only parameters

If unknown change occurs send sample by sample

At the base station use model to regenerate and align with raw signals to show the ECG

results
Results

42:1

93%

Energy and Memory Savings

Diagnostic Accuracy

Implemented using off-the-shelf sensors

Base case for comparison: Send entire ECG

demo video
Demo Video

http://www.youtube.com/watch?v=NGBq-oyPhGI&feature=channel_video_title

lessons learned
Lessons Learned
  • Communication more expensive than computation
  • Communication duty cycling is an useful tool
    • Application dependent duty cycling
  • Event based communication enables lot of energy savings
    • Can only be applied to cases where the sensed signal has a definite pattern
energy savings in computation
Energy savings in computation
  • Frequency throttling
  • Voltage scaling
  • Example BSN with Atom processors
    • Allows Advanced Configuration and Power Interface (ACPI) control for frequency and voltage
atom background
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)
strategies to address safety and sustainability challenges
Strategies to Address – Safety and Sustainability Challenges

The strategies are closely related to the applications real time requirements.

Intelligent design is required to achieve safety and sustainability

while respecting the real time requirements of the applications

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

  • 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
bsn hardware model
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

bsn node software
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
model based analysis
Model based Analysis
  • Model: An abstraction in a mathematical domain
  • Behavioral models (e.g. control system transfer function)
    • Consider the system as a black box
    • Find the relation between the inputs and the outputs
  • Formal models (e.g. finite state machines, petrinets)
    • Represent the operation of the system in terms of states and transitions between them
  • Structural models (XML specifications)
    • Represent the structure of a system in terms of the basic blocks that are present in the system
    • Does not necessarily represent operational characteristics
model based analysis1
Model based analysis
  • Model based analysis normally used to verify critical systems such as avionics.
    • no need for actual scenario generation putting lives/property at risk.
  • Formal models for abstraction of the system behavior.
  • Expected system properties depend on the requirements.
  • Formal models analyzed through model checking to verify the system properties.
  • We use model based analysis to evaluate effectiveness of crisis response processes.

System Profiling

System Requirements

Models

Expected Properties

Model

Checking

Property Verification

Requirement Verification

profiling requirements
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
Thermal Profiling

Turn On GMCH board

Set Operating

Frequency

Read MSR

C6 Sleep State

Run Ayushman

Log Temperature Data

Thermal profiling methodology

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

power profiling
Power Profiling

Power Meter

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

  • 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
resource consumption
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

safety analysis
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.

sustainability analysis
Sustainability Analysis

Total Energy

Sensing Energy

Transmission Energy

PKA Computation Energy (Pair wise PKA)

PKA communication Energy (Pair wise PKA)

Ayushman Workload

Frequency Throttling during security phase

Sensing Phase

Enables Sleep Scheduling

Transmission Phase

Total Sleep Cycle Time

Pair wise PKA Execution Time

Sleep Cycle

Sensor CPU Utilization

Security Phase

Time

  • 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
sustainability analysis results
Sustainability Analysis Results
  • Four energy scavenging sources were considered
    • Body Heat, Ambulation, Respiration and Sun Light
  • The total energy obtained from any combination of scavenging sources should provide EBSN amount of energy for n nodes