Network-Assisted Offloading for Mobile Cloud Applications · IEEE ICC 2015 Network-Assisted...

IEEE ICC 2015

Network-Assisted Offloading for MobileCloud Applications

Claudio Fiandrino

Dzmitry Kliazovich

Pascal Bouvry

University of Luxembourg

Albert Y. Zomaya University of Sydney

June 9, 2015

Motivation

I 4.4 billion people will use mobile cloud applications by 2017I $ 45 billion marketI Mobile cloud applications: 90% of all mobile data traffic by 2019

2014 2015 2016 2017 2018 20190

50%

100%19% 17% 15% 14% 12% 10%

81% 83% 85% 86% 88% 90%

Non-CloudCloud

Source: Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2014-2019

Claudio Fiandrino | IEEE ICC 2015 | Network-Assisted Offloading for Mobile Cloud Applications 1 of 11

Mobile data traffic

1 EB

30 EB

24.3 EB

Global Internet2000

Mobile Networks2014

Mobile Networks2019 (per month)

Source: Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2014-2019


Techniques

Increasing capacity

I Deploying more base stations(Micro, Pico, Femto)

3 Improve coverage

7 Cost of installation and mainte-nance

Traffic Offloading

I Offload traffic to other networks(WiFi, opportunistic)

3 Use of existing infrastructure

7 Use of different technologiesthan cellular


Traffic Offloading

Bear in mind:I Performance of applications

I Bandwidth, latencyI User profiles

I Mobility, behaviour


The scenario

I Network-assisted offloading over WiFi networks

Mobile Operator Network

CloudInternetP-GWS-GW

MCOHMME

HSS PCRFeNodeB

IP Network

WiFi APUEs

Mobile Cloud Offloading Helper

I Software module with high computing capabilities

I Offloading balancing application requirementsuser behaviour

and network resources


Offloading decision

UserBehavior

Mobile CloudOffloading

Helper (MCOH)

ApplicationRequirements

Availabilityof NetworkResources

MobilityData Plan

Channel QualityRate

Latency

Channel QualityRate

Latency


Evaluation

I NS-3 SimulationsI Scenario:

I 4 users equipped with both LTE and WiFiI Average mobility speed: [1.4,10] m/sI Available data plan: [0,1] GbI VOIP application (64 Kbit/s)

Avg. Speed: 7.54 m/sAv. Data: 0.48 GB





Amount of offloaded traffic





0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0

0.5

1

1.5

2

2.5

3

3.5

·104

1− γ

Offl

oade

dtr

affic

[Byt

es]


Mobility

0 0.2 0.4 0.6 0.8 1

0

0.2

0.4

0.6

0.8

1

Mobility factor

Traf

ficra

tio

Theoretical Experimental

I Velocity is a highly dynamic parameter


Data plan

0 0.2 0.4 0.6 0.8 1

0

0.2

0.4

0.6

0.8

1

Data plan factor

Traf

ficra

tio

Theoretical Experimental

I Amount of available data is not dynamic


Conclusion

Summary

I Software module to take offloading decisionsI Use information already present in operator networks

Take home message

I Network- and application-awareness crucial for offloadingdecisions


Thank You!Thank You!Claudio Fiandrino

<[email protected]>

Network-Assisted Offloading for Mobile Cloud Applications · IEEE ICC 2015 Network-Assisted...

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