MiLAN: Middleware to Support Sensor Network Applications

Jonghak Kim, Da Huo, Hyungik Oh

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One Line Comment

• MiLAN is a middleware which goal is 1)maximizing application lifetime while 2)providing application QoS by controlling and optimizing network as well as sensors

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Motivation

High respiratory rate

Normal Heart Rate

Low blood pressureRespiratory

Rate

Blood O2

BloodPressure

Blood O2

HeartRate

0.8

0.7

High Heart Rate

ECGDiagram

BloodPressure

BloodO2

HeartRate

0.3

0.8

0.3

0.8

0.3

1.0

0.3

• Personal Health Monitor Application– The QoS of the different variables of interest at each different states of patient– The state-based Variable Requirement graph

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Motivation• Personal Health Monitor Application

– The QoS of the different variables depends on which sensors provide data to the application

– The Sensor QoS Graph

Bloodpressure

Heartrate

Bloodpulse

Bloodpress

Bloodflow

Pulseoxy

ECGBloodpress

Bloodflow

Pulseoxy

0.7 1.0 0.8 0.7 1.0 0.70.7 0.8

1.0

Virtual sensor

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Motivation

• The characteristics of sensor network

2. Dynamic Availability

Either mobility through space, addition of new sensors, or loss of existing sensors causes the set of available sensors to change over time

3. Resource Limitation

Both network bandwidth and sensor energy are constrained. This is especially true when considering battery-powered sensors and wireless networks

1. Inherent Distribution

The sensors are distributed throughout a physical space and primarily connected wirelessly

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Goal of MiLAN

ProvideApplication

QoS

Maximize Application

Lifetime

Control the network as well as the sensors

• Goal– To satisfy the given application QoS specification and

provide data to application as long as possible, MiLAN control sensor network as well as the sensors

ApplicationQoS

Requirement

NetworkMonitoring

State Of Monitored

Objects

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MiLAN Components

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MiLAN Overview

App.Feasible

Set

NetworkFeasible

Set

Sensor Network Configuration

Sensor Network

ApplicationQoS Requirement

Sensed ObjectStates

NetworkInformation

OverallSet

Application Logic

Sensor Reading

Doctor

Application Middleware - MiLAN

Trade-off computation

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A High-level overview of MiLAN operation and Partial MiLAN API

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Application Feasible Set FA

Set # Sensors

1 Blood flow, Respiratory rate

2 Blood flow, ECG (3 leads)

3 Pulse oxymeter, Blood pressure,

ECG(1 lead), Respiratory rate

4 Pulse oxymeter, Blood pressure, ECG(3 leads)

5 Oxygen Measurement, Blood pressure, ECG(1 lead), Respiratory rate

6 Oxygen measurement, Blood pressure, ECG(3 leads)

• Multiple set of sensors, which can provide application QoS at a given state, can be derived from the state-based variable requirement graph and the sensor QoS graph

• A patient state– medium stress– high heart rate, normal respiratory rate, and low blood pressure

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Network Feasible Set FN

• Network Feasible Set– Network plugin’s job– The subsets of nodes that can be supported by

the network• Suppose that the sensors and processors communicate

using an IEEE 802.11a network• It can support overall throughput of nearly 11Mb/s• However, if multiple applications are running

simultaneously on the network and the personal health monitor application can only utilize 100kb/s of the throughput, the network would not be able to support the transmission of data from the ECG sensor with either 3, 5, or 12 leads

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Overall Set F

• F = FA ∩ FN

• Example of Overall set F– Suppose network can’t support ECG 3, 5 12 leads, since other applications are running

simultaneously

Set # Sensors

1 Blood flow, Respiratory rate

2 Blood flow, ECG (3 leads)

3 Pulse oxymeter, Blood pressure,

ECG(1 lead), Respiratory rate

4 Pulse oxymeter, Blood pressure,

ECG(3 leads)

5 Oxygen Measurement, Blood pressure, ECG(1 lead), Respiratory rate

6 Oxygen measurement, Blood pressure, ECG(3 leads)

Set # Sensors

1 Blood flow, Respiratory rate

3 Pulse oxymeter, Blood pressure,

ECG(1 lead), Respiratory rate

5 Oxygen Measurement, Blood pressure, ECG(1 lead), Respiratory rate

Application Feasible Set FA

Overall Set F

FA ∩ FN

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Trade-off Computation

• Goal– Among the elements in overall set F, MiLAN choose an element f

that represents the best performance/cost trade-off

• For getting more information about trade-off computation, refer to the paper named “Providing Application QoS through Intelligent Sensor Management” published in Elsevier Ad Hoc Network Journal, vol. 1, no. 2-3, 2003– Mathematically formulate the problem– Interpret the problem as a Generalized Maximum Flow Problem– None of the algorithms that are commonly used to solve

generalized maximum flow problem in polynomial time can be used for the sensor scheduling problem

– They use simple linear programming approach

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The END

Thank you