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1 Mobility Aware Server Selection for Mobile Streaming Multimedia CDN Muhammad Mukarram Bin Tariq , Ravi Jain, Toshiro Kawahara {tariq , jain, kawahara}@docomolabs-usa.com DoCoMo USA Labs. September 29, 2003

Mobility Aware Server Selection for Mobile Streaming Multimedia CDN

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Mobility Aware Server Selection for Mobile Streaming Multimedia CDN. Muhammad Mukarram Bin Tariq , Ravi Jain, Toshiro Kawahara {tariq , jain, kawahara}@docomolabs-usa.com DoCoMo USA Labs. September 29, 2003. Summary. - PowerPoint PPT Presentation

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1

Mobility Aware Server Selection for Mobile Streaming Multimedia CDN

Muhammad Mukarram Bin Tariq, Ravi Jain, Toshiro Kawahara{tariq, jain, kawahara}@docomolabs-usa.com

DoCoMo USA Labs.September 29, 2003

2

Summary• We present a mobility-aware server selection scheme for content

distribution networks. • Our target is CDN with high density of servers, each server having a small

coverage area. Mobile users can move out of such service areas in the duration of streaming media sessions, resulting potentially degraded QoS.

• Server Handoff can be performed to revive QoS, but it is expensive.

• We use user’s mobility along with traditional criteria such as proximity, server load etc., and assigns a server such that the probability of user moving out of coverage area of the assigned server is reduced, while meeting QoS criteria.

• Simulation results show up to 18 % reduction in number of server handoffs.

3

Outline• Summary• Introduction

– Overview– Problem Statement

• Mobility Aware Server Selection– Assumed CDN topology– Gathering user mobility information and estimating residence time

with servers.– Server Selection.

• Simulation– Mobility, Server Selection, Content Distribution.

• Results• Conclusions

4

Introduction

• Multimedia has increasing share in overall traffic

• Fixed broadband has not harnessed Multimedia, how will mobile broadband?– Mobile phones are there all the time.

– Usage scenarios: movies, songs, news, playing video games etc, while traveling

• CDN must meet the challenge of mobility, wireless and streaming media trio.– Our focus is the (Mobility + Streaming).

Expected Future mobile communication market [Yumiba01]

2005 2010Year

Mar

ket S

ize

(tra

ffic

)

Voice20-30%

Multimedia70-80%

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Streaming Media In Mobile Networks

• In previous work [Tariq02] we showed that server handoff is helpful for streaming content to mobile users.

• Localizes traffic, reduces delay, jitter, and load on the network.

R

R

Subnets in a Mobile Network

R R R

RR

R

Logically Non Adjacent Subnets,

(hot spots)

R

Server Server

R

Server Handoff

Server Handoff

Server

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Naïve server handoff scheme has problems

• If the users move too fast, there would be too many server handoffs, which are expensive for the network. – Signaling, Content Placement

• Our mobility-aware server selection assigns right users to right servers, reducing the need for handoffs.– Reduce Number of Handoffs while meeting QoS

criteria.

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CDN Topology

• Allows:– Maximization of traffic localization– Obtain desired QoS ↔ Number of Handoffs

tradeoff by choosing appropriate server tier.

Access Network Subnets

Tier 1 Server Coverage Areaaka. server-zoneEach has a RR

Tier 2 Server Coverage Area

Tier 3 Server Coverage Area Servers

More Coverage

Area

Better QoS

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Server Selection Process

Server Tiers

RR

Server Capacity Information

Move to higher tier if

1) Server Capacity Available

2) User is Moving Fast

3) QoS Diff is maintained

Move to lower tier if

1) Server Capacity Available

2) Won’t increase handoffs

3) QoS Diff is maintained

Mobility Information

We introduce a Lazy Mode where we do not move users to lower tiers unless higher tiers are saturated!!!

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Mobility Informationiririr

( )n n ki

t tr

k

Residence Time

Trajectory of the clientA subnet

1nt nt1( )n nt t Client i

Client maintains its average subnet residence time over k

recent moves

1

n

ii

r

nr

Mean residence time of all

n clients in RR’s server-zone

tR

, ( )ii t t

rE R

r

Mean Server Residence-time

for each tier tRR uses the information to estimate a future residence time of client i with tier t

We can make a high granularity estimate using subnet specific information, at cost of higher overhead. , ,( )i

i t t ss

rE R

r

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Simulation

• Simulate realistic user movement in a large geographical area, collect movement events – we wrote a custom simulator for this.

• Simulate different server selection algorithms– Baseline, clients always assigned to default tier

– Eager mode with both Low and High Granularity Mobility Information

– Lazy Mode with both Low and High Granularity Mobility Information.

• See how we did in terms of delay and jitter experience by the users.

Mobility Simulation

Server Selection Simulation

Content Distribution Simulation

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Mobility Simulation

• Custom simulator to simulate realistic urban area user movement. – Cars, Trains, Streets,

Freeways, Public Transport, Congestion, etc.

– San Francisco Bay area, 3575 sq. miles.

– Over laid with 189 base-stations, 59 subnets

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Simulation Parameters• CDN topology

– 34 servers arranged in 3 tiers, 21, 8 and 4 in tiers 1, 2, and 3 respectively.– The 3 tiers at 80ms, 160ms and 240ms respectively, from the edge.– Server Capacity, variable {50, 75, 100, 200, 300} simultaneous sessions

• Users– 2500 users with three QoS class, {1, 2, 3}, users distributed across the

three QoS classes proportionately to the number of servers at corresponding tier.

– Session Durations, variable {50, 100, 200, 1000, 1500} seconds– Data rate per user: 64kbps, 20pps

• Selection Criteria– Desired QoS Separation between adjacent classes: 20 ms.– Server Overload threshold for Lazy mode. 10% of the maximum reported

load allowance.

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Reduction in number of handoffs

-4-202468

101214161820

50 100 200 500 1000 1500

Session Duration (seconds)

Per

cent

Red

ucti

on in

N

umbe

r of

Han

doff

sSimulation Results (1/2)

Eager Mode

Lazy Mode

Low Granularity

High Granularity

Results for server capacity = 300

Results for server capacity = 100

More results in the paper…

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Simulation Results (2/2)

• Desired Separation is maintained in all scenarios

• Eager mode is achievesbetter convergence and at lower overall value.

• Higher server capacityallows us to do more.

• Accuracy of estimationhas little impact.

Impact on QoS

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0.22

0.24

0.26

100 200 300

Server Capacity (number of sessions)

E2E

Del

ay (

seco

nd

s)

Eager Mode

QoS Class 1 QoS Class 2 QoS Class 3Lazy Mode

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Conclusions• We have presented a mobility aware server selection scheme.

– Up to 18% reduction in number of server handoffs. – Simple, Largely stateless– Relies on simple and manageable information – much of which is

already available in the network.• If you are eager, you better be sure – with eager mode, higher

accuracy is crucial.• Has applications beyond streaming media.

– Anywhere that you want to make tradeoff with mobility by switching to wider-area systems.

• Open issues: – Improving while maintaining simplicity.– Manageability.– Bundling with other technologies.

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Algorithm Details

Task: Assign server to a client i of QoS class q and current/default server tier tselectedTier := t

Find load allowance of next higher tier Lt+1

If the client is in fastest Lt+1

– true if is less than Lt+1 here Uj number of sessions of a client j

If the delay separation will be maintained – true if . similarly for q,q-1

Assign Server Tier t+1.End-If

Else-If Eager Mode or (Lazy Mode with Lt+1 too low) – checking to see if we can move it to lower tier instead

Make sure client won’t increase the number of handoffs i.e., Assign Server Tier t-1.

End-If

: j i

C

jj r r

U

1 , 1q q q qD D

, 1i t tE R

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IWCW 2003Conference Report

Muhammad Mukarram Bin TariqDoCoMo USA Labs.

October 8, 2003