Qoc based optimization of end to end m health data delivery services
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QoC-based Optimization of End-to-End M-Health Data Delivery Services. Ing Widya (UoT), Bert-Jan van Beijnum (UoT), Alfons Salden (TI). Outline: introduction mobile-healthcare case context flow graph computational model freshness, availability, costs QoC computational example

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Qoc based optimization of end to end m health data delivery services
QoC-based Optimization of End-to-EndM-Health Data Delivery Services

Ing Widya (UoT),

Bert-Jan van Beijnum (UoT),

Alfons Salden (TI)


Outline:

  • introduction

    • mobile-healthcare case

  • context flow graph

  • computational model

    • freshness, availability, costs QoC

  • computational example

  • conclusions


Introduction

ADSL

Front-End

modem

si

Zigbee

ISP

Back-End

WiFi

MBU

Internet

Backbone

BlueTooth

mHP

UMTS

Front-End

si

Zigbee

PNO

GPRS

m-Health Portal

Body Area Network (BAN)

Internet Access

Introduction

  • M-Health Application

  • resource configuration & alternatives


Context flow graph cfg

S1

BTooth1

GW-processing

NFE12

NMBU11

NGW1

NGW2

wired links

NFE11

S2

FE1-

processing

WiFi

Zigbee1

S3

ADSL

GPRS

NBE2

NMBU3

NBE1

UMTS

S4

BE-

processing

WiFi

BTooth2

NFE22

NMBU22

wired link

NFE21

S5

FE2-

processing

Zigbee2

= context generatornode

= pre-selectnode

= aggregating node

Context Flow Graph (CFG)

  • optimal path to bring health-data to professional ?


Cfg qoc and qos

QoS

QoCat_B

QoCat_A

Context Information

Context Information

resource (processing/communication)

node A

node B

CFG, QoC and QoS

  • QoC based selection

    • Quality of Context (information)

    • QoC freshness(/up-to-dateness), availability, “costs”;

  • QoC impeded by QoS


Computational model
Computational Model

  • min-plus algebra

    • additive operation:

    • multiplicative operation:

arithmetic domain

  • max-plus algebra:

    • arithmetic maximum (instead minimum)

  • properties: commutative, associative, …


Computational model1
Computational Model (..)

  • aggregation & concatenation elements

    • algebraic expression

d1

S1

NFE11

d2

S2

  • QoC arithmetic expression


Computational model2

BTooth1

NFE12

Zigbee1

Computational Model (..)

  • concatenation & pre-select element

    • algebraic expression

NMBU11

  • QoC arithmetic expression


Computational model3
Computational Model (..)

  • End-to-End Freshness algebraic expression


Computational model4
Computational Model (..)

  • (1,1) element

S1

NFE12

NMBU11

NGW1

NGW2

NFE11

wired links

S2

FE1-

processing

Zigbee1

S3

GPRS

NBE2

NMBU3

NBE1

S4

BE-

processing

NFE22

NMBU22

wired link

NFE21

S5

FE2-

processing

Zigbee2

  • Availability & costs: independently & similarly


Computational example
Computational Example

  • QoS values (illustration)

  • QoC results

    • three independently calculated QoC matrices

    • 4x4 matrices of ranked alternative E2E paths

  • Weighing Metrics

    • weighted quadratic norms


Computational example1
Computational Example (..)

  • QoC for a rehabilitation training scenario

    • weights: wFr = 1, w1-Av = 150, wCo = 0.02 (not normalized)

outdoors

indoors

  • indoors: path via ZigBee1, BTooth2 & WiFi + ADSL

  • outdoors: path via ZigBee1, BTooth2 & UMTS


Conclusions
Conclusions

  • QoC based selection of an optimal E2E transfer pathfor M-Health scenarios;

  • Min-max-plus algebra for several QoC dimensions;

  • Future work:

    • dynamic case

    • use of (colored) Petri-Nets

    • other workflow operations


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