Data-Driven Dependability Analysis Using AADL for

Wireless Sensor Networks

Ting Yan, Hui Cao, Sujit R. Das, and Luis Pereira

Innovation Center, Eaton CorporationJanuary 25th, 2006

Dependability

Dependability = Ability to deliver a trusted service

DependabilityDependability

ThreatsThreats AttributesAttributes

SurvivabilitySurvivability

IntegrityIntegrity

ConfidentialityConfidentiality

SafetySafety

MaintainabilityMaintainability

AvailabilityAvailability

ReliabilityReliability

FailuresFailures

ErrorsErrors

FaultsFaults

Dependability metrics for WSN

Average Packet Success Rate Average LatencyAverage System Life

Reliability AvailabilityAvailability, Maintainability

Note: Those values are averaged across all the nodes and over a period of time

AADL Dependability Analysis Tool Design

GUI Input

Power consumption

data

Link Quality data

Hardware failure data

Packet latency data

Topology Formation

Routing

Latency Analysis PSR AnalysisSystem Life Analysis

Time Series Data Analysis

DeploymentComponents Environment Radio Feature

AADL WSN Model Generation

Model InstantiationData Access

System to model and analyzeSensor Network

Base station

•Chip: ATmega128L•Radio: CC2420•Battery: 2AA-1800MAH•# of nodes: 8•Location of nodes: node1(0,10), node2(10,15)…..•Environment: humdity 85%…•MAC: 802.15.4•Routing: AODV•Application: data aggregation

AADL Model

Average PSR

0%

20%

40%

60%

80%

100%

0 20% 30% 40% 50% 60% 70%

Humidity

0.96

0.94

0.780.89

0.900.69

0.32

0.95

R(t) = 0.97

0.98

0.79

0.680.76

0.91

0.84 0.980.88

0.93

Hardware Data

Communication Link Data

Data driven Dependability Analysis

AADLArchitecture Design

Power consumption

data

Link PSR data

Dependability Analysis

Dependability MetricsPacket Success RateSystem Latency System Life

Hardwarefailure data

Packet latency data

Why Data driven?Low fidelity of wireless channel model

Huge Environment impact on link quality

and node reliability

Real data from

deployment

Time Varying Dependability Analysis

Time(days)

…

Time(days)

Node Reliability

Battery Level: B (t) =

1800mAh

100

100

200

200

1

Link Quality: retrieved from Link Data

R (t) = e -λt

λ: Failure rate for Node

tDCBtotal **−C: power consumption per dayD: duty cycle

Modeling a Sensornet

Power UnitBattery

Processing UnitCPU

Transceiver UnitRadio

Sensing UnitHardware

Physical Layer

MAC Layer

Network Layer

Transport Layer

Sensor Layer

Sensor Application Layer

Wireless Channel Sensor Channel

NETWORK STACKSENSOR STACK

AADL Constructs:

Software categoryProcessSubprogramDataThreadThread group

Platform categoryProcessorMemoryDeviceBus

CompositeSystem

Mapping

Layers: ThreadsWireless Channel: BusSensor Channel: BusProcessing Unit: ProcessorSensing Unit: Device

Transceiver Unit: DevicePower Unit: DeviceSensor Measurements: DataMessages Exchanged: Data,

Event Ports

AADL Model - Network

NetworkSets of NodesRouting policy:

Neighbor TableZigBee AODV routing policy

Radio ChannelChannel No.

Data SourceLink QualityHardware Reliability

system implementation WSN.NLAsubcomponents

NODE0: system NODE.NODE0;NODE1: system NODE.NODE1;NODE2: system NODE.NODE2;NODE3: system NODE.NODE3;NODE4: system NODE.NODE4;NODE5: system NODE.NODE5;NODE6: system NODE.NODE6;NODE7: system NODE.NODE7;

propertiesNetworkProp::network_channel => 13;NetworkProp::network_LinkData=>“\c\dev\psr1.txt”;

end WSN.NLA;

•Chip: ATmega128L•Radio: CC2420•Battery: 2AA-1800MAH•# of nodes: 8•Location of nodes: node1(0,10), node2(10,15)…..•Environment: humdity 85%…•MAC: 802.15.4•Routing: AODV•Application: data aggregation

AADL Model

AADL Model - NodeNode

Node Type: RFD, FFDLocation (x,y)Hardware Components

CPUMemory

EnvironmentsTemperature

Operating ProfilesDuty Cycle

Power Unit:Battery CapacityPower consumption

Radio ChannelTx Power level

system implementation NODE.NODE0properties--Location PropertiesNodeProp::node_id => 0;NodeProp::node_x => 0.0;NodeProp::node_y => 0.0;--Hardware Components PropertiesNodeProp::node_memory => 1000.0;NodeProp::node_cpu_speed => 1000.0;--Environments PropertiesNodeProp::op_temperature => 30.0;NodeProp::dormrant_temperature => 40.0;--Operating Profiles PropertiesNodeProp::humidity => 20.0;NodeProp::vibration_level => 0.0;NodeProp::case_ID => 0;--Battery PropertiesNodeProp::isBattery => 0; NodeProp::node_battery_energy => 2100.0; --Node state

NodeProp::node_time => 0.0;end NODE.NODE0;

Dependability Analysis: Mains-Powered

Method: Monte Carlo Simulation

Base station

Sensor Node 1

Step 1: Update Node reliability

Step 2: Decide whether Node is alive or not

Step 3: Update Link Quality

Step 4: AODV routing policy1

8

7

6

2

4

5

0.78

0.90 0.42

0.79

0.680.76

0.91

0.88

0.67

ZigBee routing policy

AODV Link Cost:

Reliability of node 1:

Latency of node 1:

402412 LLL ++

402412 RRR ∗∗

Dependability Analysis: Battery-Powered

Node battery life: Node can work properly until certain voltage levelOnly for RFD or end devices

18

7

6

23

4

5

0.96

0.94

0.890.95

0.97

0.98

0.910.84

0.999

17

6

24

5

0.78

0.90 0.420.680.76

0.91

0.881

76

24

5

0.78

0.90 0.42 0.680.76

0.91

0.88

18

7

6

24

53

9%

19%23% Base station

Mains Node 1

Battery Node 7

Results – System PSRAverage Packet Success Rate (PSR)

Channel has impact on reliability of WSN

Transmission power level also affects reliability

00.10.20.30.40.50.60.70.80.9

1

1 2 3 4 5 6 7 8 9 10

year

End-

to-E

nd R

elia

bilit

y

channel 13channel 17channel 21channel 25

0.65

0.7

0.75

0.8

0.85

0.9

0 -5 -10 -15

Tx Power Level(dBm)

End-

to-E

nd R

elia

bilit

y

Note: Average over 10 year

Results – System Life

System life:Measured by percentage of disconnected nodes

0

0.1

0.2

0.30.4

0.5

0.6

0.7

0.8

1 2 3 4 5 6 7 8 9 10

year

Perc

enta

ge o

f Dis

conn

ecte

d Nod

es

-40F30F85F At higher temperature, more

nodes are disconnected

0.182

0.183

0.184

0.185

0.186

0.187

0.188

13 17 21 25

Channel No.

Perc

enta

ge o

f Dis

conn

ecte

d no

des Channel affects the system

life also

Note: Average over 10 year

Lessons learnedAADL is the choice for modeling WSN architecture:

Flexibility in language extensions

OSATE plug-in support

Node or link level dependability ≠ WSN dependability

Needed more AADL support for WSN:

Represent large scale WSN topologies

Import empirical/experimental data into the system model

Represent time-variant properties

Represent node-level state machines

Proposed Publications

AADL tutorial for Embedded System Design magazineWSN modeling approach using AADL –ConferenceAADL for ZigBee – ZigBee conference

Issues for WSN Modeling

What features are not there for effectively modeling wireless sensor networks in the current version of AADL?

Effective and flexible means to represent large scale WSN topologiesto import empirical/experimental data into the system model to represent time-variant propertiesto represent node-level state machines

WSN Topology Specification

It is painful to specify each individual node location and link manually for a large scale WSNVarious ways to manage the issue

Fixed topologies – need means to read topology from filesTopologies with patterns – grids, uniformly random, …

Specify with patterns and parameters, such as Grid with grid size 10 meters, and have the plug-ins automatically generate the topologies

Specification of Links

Number of links exceeds that of nodes, therefore it is not realistic to have them entered manually for a system with > 100 nodesAutomatically generate links based on simple models with plug-ins

Given the node topologies, base the on/off of links on a circular model with random fluctuations

Gather link information with experiments, and then import the experimental data into the system

Specify Time-Variant Properties

Some properties are time-variant, e.g., RSSI and LQI, which cannot be specified with the syntax/semantics of the current version of AADLSpecify time-variant properties

Model based specificationImport empirical data from experiments

Specify Node-Level State Machines

State machines on each WSN node are necessary to describe system behavior, which is missing in the current version of AADL

For example, the communication sub-system of a single node may have states such as SENDING, RECEIVING, WAITING_FOR_ACK, …Need notions of state, transition, …

Two Patterns

Need to import data from separate filesNode locations, link qualities, …

Need various levels of details – for example: First level – Grid deployment with density of 1/100m^2Second level – Locations (0m, 0m), (10m, 0m), (20m, 0m), (0m, 10m) …Use plug-ins to automatically generate the second level model from the first level model