Lecture 2: Software Platforms

Lecture 2: Software Platforms

Anish Arora

CIS788.11J

Introduction to Wireless Sensor Networks

Lecture uses slides from tutorials prepared by authors of these platforms

2

Outline

• Discussion includes not only operating systems but also programming methodology Some environments focus more on one than the other

• Focus here is on node centric platforms (versus distributed system centric platforms)

• Platforms TinyOS (applies to XSMs) slides from Culler et al EmStar (applies to XSSs) slides from UCLA SOS Contiki Virtual machines (Maté) TinyCLR

3

• NesC

• The Emergence of Networking Abstractions and Techniques in TinyOS

• EmStar: An Environment for Developing Wireless Embedded Systems Software

• TinyOS webpage

• EmStar webpage

References

4

Traditional Systems

• Well established layers of abstractions

• Strict boundaries• Ample resources• Independent

applications at endpoints communicate pt-pt through routers

• Well attended

User

System

Physical LayerData LinkNetwork

TransportNetwork Stack

Threads

Address Space

Drivers

Files

Application

Application

Routers

5

Sensor Network Systems

• Highly constrained resources processing, storage, bandwidth, power, limited hardware parallelism,

relatively simple interconnect

• Applications spread over many small nodes self-organizing collectives highly integrated with changing environment and network diversity in design and usage

• Concurrency intensive in bursts streams of sensor data & network traffic

• Robust inaccessible, critical operation

• Unclear where the boundaries belong

Need a framework for:• Resource-constrained concurrency• Defining boundaries• Appl’n-specific processingallow abstractions to emerge

6

Choice of Programming Primitives

• Traditional approaches command processing loop (wait request, act, respond) monolithic event processing full thread/socket posix regime

• Alternative provide framework for concurrency and modularity never poll, never block interleaving flows, events

7

TinyOS

• Microthreaded OS (lightweight thread support) and efficient network interfaces

• Two level scheduling structure

Long running tasks that can be interrupted by hardware events

• Small, tightly integrated design that allows crossover of software components into hardware

8

Tiny OS Concepts

• Scheduler + Graph of Components constrained two-level scheduling model:

threads + events

• Component: Commands Event Handlers Frame (storage) Tasks (concurrency)

• Constrained Storage Model frame per component, shared stack, no

heap

• Very lean multithreading

• Efficient Layering

Messaging Component

init

Pow

er(m

ode)

TX_p

acke

t(buf

)

TX_p

acke

t_do

ne

(suc

cess

)R

X_p

acke

t_do

ne (b

uffe

r)

Internal State

init

pow

er(m

ode)

send

_msg

(add

r, ty

pe, d

ata)

msg

_rec

(type

, dat

a)m

sg_s

end_

done

)

internal thread

Commands Events

9

Application = Graph of Components

RFM

Radio byte

Radio Packet

UART

Serial Packet

ADC

Temp Photo

Active Messages

clockbit

byte

pack

et

Route map Router Sensor Appln

appl

icat

ion

HW

SW

Example: ad hoc, multi-hop routing of photo sensor readings

3450 B code 226 B data

Graph of cooperatingstate machines on shared stack

10

TOS Execution Model

• commands request action ack/nack at every boundary call command or post task

• events notify occurrence HW interrupt at lowest level may signal events call commands post tasks

• tasks provide logical concurrency preempted by events

RFM

Radio byte

Radio Packet

bit

byte

pack

et

event-driven bit-pump

event-driven byte-pump

event-driven packet-pump

message-event drivenactive message

application comp

encode/decode

crc

data processing

11

Event-Driven Sensor Access Pattern

• clock event handler initiates data collection• sensor signals data ready event• data event handler calls output command• device sleeps or handles other activity while waiting• conservative send/ack at component boundary

command result_t StdControl.start() { return call Timer.start(TIMER_REPEAT, 200); }event result_t Timer.fired() { return call sensor.getData(); }event result_t sensor.dataReady(uint16_t data) { display(data) return SUCCESS; }

SENSE

Timer Photo LED

12

TinyOS Commands and Events

{... status = call CmdName(args)...}

command CmdName(args) {...return status;}

{... status = signal EvtName(args)...}

event EvtName(args) {...return status;}

13

TinyOS Execution Contexts

• Events generated by interrupts preempt tasks• Tasks do not preempt tasks• Both essential process state transitions

Hardware

Interrupts

even

ts

commands

Tasks

14

Tasks

• provide concurrency internal to a component longer running operations

• are preempted by events• able to perform operations beyond event context• may call commands• may signal events• not preempted by tasks

{...post TskName();...}

task void TskName {...}

15

Typical Application Use of Tasks

• event driven data acquisition• schedule task to do computational portion

event result_t sensor.dataReady(uint16_t data) {

putdata(data);

post processData();

return SUCCESS;

}

task void processData() {

int16_t i, sum=0;

for (i=0; i ‹ maxdata; i++)

sum += (rdata[i] ›› 7);

display(sum ›› shiftdata);

}

• 128 Hz sampling rate• simple FIR filter• dynamic software tuning for centering the magnetometer signal (1208 bytes)

• digital control of analog, not DSP• ADC (196 bytes)

16

Task Scheduling

• Currently simple fifo scheduler• Bounded number of pending tasks• When idle, shuts down node except clock

• Uses non-blocking task queue data structure

• Simple event-driven structure + control over complete application/system graph

instead of complex task priorities and IPC

17

Maintaining Scheduling Agility

• Need logical concurrency at many levels of the graph• While meeting hard timing constraints

sample the radio in every bit window

Retain event-driven structure throughout application Tasks extend processing outside event window All operations are non-blocking

18

RadioTimingSecDedEncode

The Complete Application

RadioCRCPacket

UART

UARTnoCRCPacket

ADC

phototemp

AMStandard

ClockC

bit

byte

pack

et

SenseToRfm

HW

SW

IntToRfm

MicaHighSpeedRadioM

RandomLFSRSPIByteFIFO

SlavePin

noCRCPacket

Timer photo

ChannelMon

generic comm

CRCfilter

19

Programming Syntax

• TinyOS 2.0 is written in an extension of C, called nesC

• Applications are too just additional components composed with OS components

• Provides syntax for TinyOS concurrency and storage model commands, events, tasks local frame variable

• Compositional support separation of definition and linkage robustness through narrow interfaces and reuse interpositioning

• Whole system analysis and optimization

20

Components

• A component specifies a set of interfaces by which it is connected to other components

provides a set of interfaces to others uses a set of interfaces provided by others

• Interfaces are bidirectional include commands and events

• Interface methods are the external namespace of the component

Timer Component

StdControl Timer

Clock

provides

uses

provides interface StdControl; interface Timer:uses

interface Clock

21

Component Interface

• logically related set of commands and events

StdControl.nc

interface StdControl { command result_t init(); command result_t start(); command result_t stop();}

Clock.nc

interface Clock {

command result_t setRate(char interval, char scale);

event result_t fire();

}

22

Component Types

• Configurations link together components to compose new component configurations can be nested complete “main” application is always a configuration

• Modules provides code that implements one or more interfaces and

internal behavior

23

Example of Top Level Configuration

configuration SenseToRfm {// this module does not provide any interface}implementation{ components Main, SenseToInt, IntToRfm, ClockC, Photo as Sensor;

Main.StdControl -> SenseToInt; Main.StdControl -> IntToRfm;

SenseToInt.Clock -> ClockC; SenseToInt.ADC -> Sensor; SenseToInt.ADCControl -> Sensor; SenseToInt.IntOutput -> IntToRfm;}

SenseToInt

ClockC Photo

Main

StdControl

ADCControl IntOutputClock ADC

IntToRfm

24

Nested Configuration

includes IntMsg;configuration IntToRfm{ provides { interface IntOutput; interface StdControl; }}implementation{ components IntToRfmM, GenericComm as Comm;

IntOutput = IntToRfmM; StdControl = IntToRfmM;

IntToRfmM.Send -> Comm.SendMsg[AM_INTMSG]; IntToRfmM.SubControl -> Comm;}

IntToRfmM

GenericComm

StdControl IntOutput

SubControl SendMsg[AM_INTMSG];

25

IntToRfm Module

includes IntMsg;

module IntToRfmM { uses { interface StdControl as SubControl; interface SendMsg as Send; } provides { interface IntOutput; interface StdControl; }}implementation{ bool pending; struct TOS_Msg data;

command result_t StdControl.init() { pending = FALSE; return call SubControl.init(); }

command result_t StdControl.start()

{ return call SubControl.start(); }

command result_t StdControl.stop()

{ return call SubControl.stop(); }

command result_t IntOutput.output(uint16_t value)

{

...

if (call Send.send(TOS_BCAST_ADDR,sizeof(IntMsg), &data)

return SUCCESS;

...

}

event result_t Send.sendDone(TOS_MsgPtr msg, result_t success)

{

...

}

}

26

Atomicity Support in nesC

• Split phase operations require care to deal with pending operations

• Race conditions may occur when shared state is accessed by premptible executions, e.g. when an event accesses a shared state, or when a task updates state (premptible by an event which then uses that state)

• nesC supports atomic block implemented by turning of interrupts for efficiency, no calls are allowed in block access to shared variable outside atomic block is not allowed

27

Supporting HW Evolution

• Distribution broken into apps: top-level applications tos:

lib: shared application components system: hardware independent system components platform: hardware dependent system components

o includes HPLs and hardware.h interfaces

tools: development support tools contrib beta

• Component design so HW and SW look the same example: temp component

may abstract particular channel of ADC on the microcontroller may be a SW I2C protocol to a sensor board with digital sensor or ADC

• HW/SW boundary can move up and down with minimal changes

28

Example: Radio Byte Operation

• Pipelines transmission: transmits byte while encoding next byte• Trades 1 byte of buffering for easy deadline• Encoding task must complete before byte transmission completes• Separates high level latencies from low level real-time rqmts• Decode must complete before next byte arrives

Encode Task

Bit transmission Byte 1

Byte 2

RFM Bits

Byte 2

Byte 1 Byte 3

Byte 3

Byte 4

start …

29

Dynamics of Events and Threads

bit event filtered at byte layer

bit event => end of byte =>

end of packet => end of msg send

thread posted to start

send next message

radio takes clock events to detect recv

30

Sending a Message

bool pending;struct TOS_Msg data;command result_t IntOutput.output(uint16_t value) {

IntMsg *message = (IntMsg *)data.data;if (!pending) {

pending = TRUE;message->val = value;message->src = TOS_LOCAL_ADDRESS;if (call Send.send(TOS_BCAST_ADDR, sizeof(IntMsg), &data))

return SUCCESS; pending = FALSE;

} return FAIL;}

destination length

• Refuses to accept command if buffer is still full or network refuses to accept send command• User component provide structured msg storage

31

Send done Event

• Send done event fans out to all potential senders• Originator determined by match

free buffer on success, retry or fail on failure• Others use the event to schedule pending communication

event result_t IntOutput.sendDone(TOS_MsgPtr msg, result_t success)

{ if (pending && msg == &data) {

pending = FALSE;signal IntOutput.outputComplete(success);

} return SUCCESS; }}

32

Receive Event

• Active message automatically dispatched to associated handler knows format, no run-time parsing performs action on message event

• Must return free buffer to the system typically the incoming buffer if processing complete

event TOS_MsgPtr ReceiveIntMsg.receive(TOS_MsgPtr m) { IntMsg *message = (IntMsg *)m->data; call IntOutput.output(message->val); return m;}

33

Tiny Active Messages

• Sending declare buffer storage in a frame request transmission name a handler handle completion signal

• Receiving declare a handler firing a handler: automatic

• Buffer management strict ownership exchange tx: send done event reuse rx: must return a buffer

34

Tasks in Low-level Operation

• transmit packet send command schedules task to calculate CRC task initiates byte-level data pump events keep the pump flowing

• receive packet receive event schedules task to check CRC task signals packet ready if OK

• byte-level tx/rx task scheduled to encode/decode each complete byte must take less time that byte data transfer

35

TinyOS tools

• TOSSIM: a simulator for tinyos programs

• ListenRaw, SerialForwarder: java tools to receive raw packets on PC from base node

• Oscilloscope: java tool to visualize (sensor) data in real time

• Memory usage: breaks down memory usage per component (in contrib)

• Peacekeeper: detect RAM corruption due to stack overflows (in lib)

• Stopwatch: tool to measure execution time of code block by timestamping at entry and exit (in osu CVS server)

• Makedoc and graphviz: generate and visualize component hierarchy

• Surge, Deluge, SNMS, TinyDB

36

Scalable Simulation Environment

• target platform: TOSSIM whole application compiled for host native instruction set event-driven execution mapped into event-driven simulator

machinery storage model mapped to thousands of virtual nodes

• radio model and environmental model plugged in

bit-level fidelity

• Sockets = basestation

• Complete application including GUI

37

Simulation Scaling

38

TinyOS Limitations

• Static allocation allows for compile-time analysis, but can make programming harder

• No support for heterogeneity Support for other platforms (e.g. stargate) Support for high data rate apps (e.g. acoustic beamforming) Interoperability with other software frameworks and languages

• Limited visibility Debugging Intra-node fault tolerance

• Robustness solved in the details of implementation nesC offers only some types of checking

39

Em*

• Software environment for sensor networks built from Linux-class devices

• Claimed features: Simulation and emulation tools Modular, but not strictly layered architecture Robust, autonomous, remote operation Fault tolerance within node and between nodes Reactivity to dynamics in environment and task High visibility into system: interactive access to all services

40

Contrasting Emstar and TinyOS

• Similar design choices programming framework

Component-based design “Wiring together” modules into an application

event-driven reactive to “sudden” sensor events or triggers

robustness Nodes/system components can fail

• Differences

hardware platform-dependent constraints Emstar: Develop without optimization TinyOS: Develop under severe resource-constraints

operating system and language choices Emstar: easy to use C language, tightly coupled to linux (devfs) TinyOS: an extended C-compiler (nesC), not wedded to any OS

41

Em* Transparently Trades-off Scale vs. Reality

Em* code runs transparently at many degrees of “reality”: high visibility debugging before low-visibility deployment

Reality

Scal

e

Pure Simulation

Data Replay

Portable Array

Deployment

Ceiling Array

42

Em* Modularity

• Dependency DAG

• Each module (service) Manages a resource & resolves

contention Has a well defined interface Has a well scoped task Encapsulates mechanism Exposes control of policy Minimizes work done by client

library

• Application has same structure as “services”

Hardware Radio

Topology Discovery

Collaborative SensorProcessing Application

NeighborDiscovery

ReliableUnicast

Sensors

LeaderElection

3d Multi-Lateration

Audio

TimeSync

AcousticRanging

StateSync

43

Em* Robustness

• Fault isolation via multiple processes

• Active process management (EmRun)

• Auto-reconnect built into libraries “Crashproofing” prevents cascading failure

• Soft state design style Services periodically refresh clients Avoid “diff protocols”

motor_x motor_y

scheduling

path_plandepth map

camera

EmRun

44

Em* Reactivity

• Event-driven software structure React to asynchronous notification e.g. reaction to change in neighbor list

• Notification through the layers Events percolate up Domain-specific filtering at every level e.g.

neighbor list membership hysteresis time synchronization linear fit and outlier rejection

motor_y

scheduling

path_plannotifyfilter

45

• Tools EmRun EmProxy/EmView

• Standard IPC FUSD Device patterns

• Common Services NeighborDiscovery TimeSync Routing

EmStar Components

46

EmView/EmProxy: Visualization

emviewEmulator

nodeNnodeNnodeN

Mote Mote … Mote

motenic

linkstat

neighbor

emproxy

…

47

EmSim/EmCee

• Em* supports a variety of types of simulation and emulation, from simulated radio channel and sensors to emulated radio and sensor channels (ceiling array)

• In all cases, the code is identical

• Multiple emulated nodes run in their own spaces, on the same physical machine

48

EmRun: Manages Services

• Designed to start, stop, and monitor services

• EmRun config file specifies service dependencies

• Starting and stopping the system Starts up services in correct order Can detect and restart unresponsive services Respawns services that die Notifies services before shutdown, enabling graceful

shutdown and persistent state

• Error/Debug Logging Per-process logging to in-memory ring buffers Configurable log levels, at run time

49

IPC : FUSD

• Inter-module IPC: FUSD Creates device file interfaces

Text/Binary on same file

Standard interface Language independent No client library required

Client Server

kfusd.o

/dev/fusd/dev/servicename

Kernel

User

50

Device Patterns

• FUSD can support virtually any semantics What happens when client calls read()?

• But many interfaces fall into certain patterns

• Device Patterns encapsulate specific semantics take the form of a library:

objects, with method calls and callback functions priority: ease of use

51

Status Device

• Designed to report current state no queuing: clients not guaranteed to see

every intermediate state

• Supports multiple clients

• Interactive and programmatic interface ASCII output via “cat” binary output to programs

• Supports client notification notification via select()

• Client configurable client can write command string server parses it to enable per-client

behavior

Status Device

Server

O I

Client1 Client2 Client3

ConfigHandler

State RequestHandler

52

Packet Device

• Designed for message streams

• Supports multiple clients

• Supports queuing Round-robin service of output

queues Delivery of messages to all/

specific clients

• Client-configurable: Input and output queue lengths Input filters Optional loopback of outputs to

other clients (for snooping)

Packet Device

Server

Client1

I O

F

Client2

I O

F

Client3

I O

F

O I

53

Device Files vs Regular Files

• Regular files: Require locking semantics to prevent race conditions between readers

and writers Support “status” semantics but not queuing No support for notification, polling only

• Device files: Leverage kernel for serialization: no locking needed Arbitrary control of semantics:

queuing, text/binary, per client configuration Immediate action, like an function call:

system call on device triggers immediate response from service, rather than setting a request and waiting for service to poll

54

Interacting With em*

• Text/Binary on same device file Text mode enables interaction from

shell and scripts Binary mode enables easy

programmatic access to data as C structures, etc.

• EmStar device patterns support multiple concurrent clients IPC channels used internally can be

viewed concurrently for debugging “Live” state can be viewed in the shell

(“echocat –w”) or using emview