Bit-Rate” and “Application · PDF file“Bit-Rate” and...

“Bit-Rate” and “Application Performance” in Ultra BroadBand Networks

4ºFocus: Gianfranco

Ciccarella - Telecom

Gianfranco Ciccarella - Telecom Italia Vice President Global Advisory Services

10 º Fiberness – Pieve Santo Stefano (Ar) – Giugno 2014

Telecom Italia

Index

► QoE platforms: the reason why

► How to improve Quality of Experience

► New business models

Gianfranco Ciccarella – Telecom Italia – VP Global Advisory Services


cv

cv

cv

IP traffic growth

247

46 23 72 80

865

134

62

259

320

World Western Europe LATAM North America APAC

2012 2017

x 3,5

x 2,9 x 2,7

x 3,6 x 4,0

Peak Internet Traffic – Total Bandwidth (Terabit/s)

Internet Video Traffic (% of total consumer traffic)

57% 51%

57%

66%

55%

69% 71% 76%

73%

66%

World WesternEurope

LATAM North America APAC

2012 2017

Source: Cisco VNI; Analysys Mason

1,2 1,3

3,2

4

2

9

Italy Argentina Brazil

2012 2017

x 3,4 x 1,5

x 2,8

Average Internet – Total Bandwidth (Terabit/s)

Data traffic «volumes» and «bandwidth» are growing…

… and most of the IP traffic is Video

3



Main performance requirements

Business requirements on Download time

Strangeloop – content delivery summit 2012

Examples of service throughput requirements

2 CH

b’cast

Key performance Drivers:

• Downstream Application

throughput

• Download time

4



“Application Throughput” and “Bit-Rate”

Central

Office User

Premises

Broadband

Line

Transmission Bit-Rate

Max TCP-IP data

transfer Bit-Rate

WEB FTP Application

Throughput

16 Mbps*

* Measures at my home, Italy, feb 2014

13 Mbps*

7 Mbps* e.g. Large File

Download (with

a browser)

e.g. PC-web site

speed test Tool

e.g. ADSL BB-

line monitor

• Application Throughput is

lower than Bit Rate (in some

case much lower!)

• High Application Throughput

requires low delay and low

packet loss

• QoS functionalities cannot

improve Throughput

• QoE Platforms (Application &

Content Delivery, WEB Acceleration,

Protocol Optimizations…) are needed

to improve best-effort IP

network performance and to

reduce network TCO

Application Throughput is the most important KPI affecting end-user Quality of Experience (QoE)

Web site

5



Application Throughput is lower than connection Bit Rate

Throughput/Bit-rate= 74%

6

Akamai average connection

speed ( throughput)

= 5,2 Mbps (4Q 2013)

The Average Connection Speed (a throughput proxy) metric represents an average of the measured connection speeds across all of the unique IP addresses seen by Akamai for a particular geography

Akamai Status of the Internet 4Q13 Report

Ookla SpeedTest ( bit rate)

= 6,98 Mbps (4Q 2013)

Download Speed Test (a bit rate proxy) uses up to four HTTP threads to saturate the user connection; several measure samples are analyzed to estimate the maximum connection speed.

Apr Jul Oct 2010 Apr Jul Oct 2011 Apr Jul Oct 2012 Apr Jul Oct 2013 2014



Application Throughput is lower than Connection Bit Rate… …and it gets worse for higher Bit Rates (1/2)

(*) Ookla SpeedTest data ( Bit Rate) - (3Q13) (#) Akamai connection speed ( Throughput ) - (3Q13)

For growing bit-rate: • the ratio Throughput / BitRate decreases • the “bit rate capacity waste” is more severe

7



Application Throughput is lower than Connection Bit Rate… …and it gets worse for higher Bit Rates (2/2)

(*) Ookla SpeedTest data ( Bit Rate) - (4Q13) (#) Akamai connection speed ( Throughput ) - (3Q13)

For growing bit-rate: • the ratio Throughput / BitRate decreases • the “bit rate capacity waste” is more severe

(4Q13)

8



Th

rou

gh

pu

t a

nd

Bit

Rate

[ M

bps ]

MAX TCP Throughput

Bit Rate and Throughput vs RTT and Packet Loss

(*) NetIndex/Ookla SpeedTest (4Q13) EU Commission report (oct.2013) shows that in EU:

P.Loss = 0,2% - 0,5% “Latency” = 19ms - 36ms

Rif: ● M.Mathis et Al. , “Macroscopic Behavior of TCP Congestion Avoidance Algorithm, July 1997

● Basso, et Al. Packet Loss Rate in the Access Through Application-Level Measurements, ACM SIGCOMM Helsinki, Aug 2012

TCP throughput over

xDSL/FTTx access

50 20 80 100

20

7

(**) Akamai State of the Internet 4Q13

Average DS

Throughput EU (**)

Average DS

Throughput Italy (**)

Average DS

BitRate EU (#)

(#) EU Commission report “Quality of BB in EU” (oct. 2013)

Long-term target

9

Average DS

BitRate Italy (*)

Telecom Italia

Index






Content & Application Delivery networks, caching…

Reduce latency for better performance

WEB acceleration, Front End Optimization…

How to improve Quality of Experience

Network protocols optimization…

Multiple copies of contents

QoS functionalities cannot improve throughput nor reduce WEB page download time Telcos can leverage on both QoE platforms & QoS functionalities … and QoE platforms enable network TCO saving

Reduce user-server distance…

Quality of Experience (QoE)

• Subjective measure, from the user’s perspective, of the overall quality of the service provided.

• Usually expressed as “MOS, Mean Opinion Score”, ranging from 1 to 5.

• QoE is improved by platforms such as content & application delivery, caching, protocol optimization, front-end optimization, compression, adaptive bitrate.

Quality of Service (Network Level)

• QoS functionalities are always used in IP networks and provide traffic management mechanisms (e.g. IETF Diffserv: Differentiated Services, ...) based on different priorities. QoS is also needed in case of network congestion

Improve application

throughput

Reduce web page

download time

QoE

platforms

11



CDN/TC Platforms improve best effort network performance

Mobile Access

Fixed Access

All-IP Domestic Network

International

Network Core Metro Regional

UBB access

Network QoE Platforms. Policy Control.

Content nearer to users better performance (higher throughput)

Akamai 2012, «Empirical Network Analysis» 12



Throughput improvement by “protocol enhancer”…

From 2 to 5 times higher

throughput for many

traffic types (e.g. FTP,

HTTP, video HD…)

13



Web page download time improvement …

Keep Alive & Compression

Add a CDN Full optimization

1 2

3 4

QoE can be improved with a mix of technologies and solutions

Strangeloopnet “ WEB performance Automation” http://www.youtube.com/watch?v=IPn0T1UacIA

No web acceleration

sec

14



OTT are looking to “enter” in the Telco Networks

1

2

3

4

• QoE platforms managed

by OTTs

• Options 3 & 4 require IP

EDGE distribution

PoP

PoP

PoP

PoP

15



Network transformation guidelines

APP Server/ QoE Platf.

IP EDGE

MPLS

IP - Ethernet

ROADM WDM

MPLS

ROADM

IP - Ethernet

IP - Ethernet

Tx Network: ROADM in Core and Metro, WDM in Aggregation

End-to-end IP/MPLS on WDM for IP EDGE, Application Servers and QoE platforms distribution

QoE Platform deployment: Content Delivery Network Transparent caching Application Delivery Network Web Acceleration … …


AS-IS TO-BE

IP EDGE


IP EDGE


Key Points

16



20 ms < RTT < 25 ms (95%)

30 ms < RTT < 35 ms (95%)

RTT > 35 ms

Cache in the Net (1/2): RTT reduction

On Net

Caching in the Core

core sites

Off Net

Caching

Out of Telco ISP domain sites

On Net

Caching in the Metro

CO/metro sites

Internet

Interconnection

Point

Last Mile

BB-UBB access

areas

User’s

premises

17

Simulation Results RTT normalized distribution with

Caches deployed:

• at the interconnection point

(Off Net)

• in Core sites (On Net)

• in Metro sites (On Net)



On Net Caching in the Core core sites

Off Net Caching Out of Telco ISP domain sites

On Net Caching in the Metro CO/metro sites

Last Mile BB-UBB access

areas

User’s

premises

Cache in the Net (2/2): TCP throughput

18

Simulation Results Max TCP throughput distribution

with Caches deployed:

• at the interconnection point

(Off Net)

• in Core sites (On Net)

• in Metro sites (On Net)

PLR: 0,01%

PLR: 0,1%



Costs Saving due to Caches deployed in the network

19

Network Costs Saving (%) as a function of “Cx” (*)

(*) Cx =

“Upstream network “ cost = cost from the cache insertion point to the Big Internet interconnection

EC (Cache efficiency or HitRatio) = average % of traffic delivered by the cache

“Cache Fan Out” = traffic delivered by the cache (given by: EC * Traffic delivered to End Users

“downstream” the cache insertion point)

Unitary “upstream network” Cost [K€/Gbps]

Unitary Cache Cost [K€/Gbps] referred to “cache fan-out”



Costs saving due to distributed IP Edge & Caching Case Study

• IP services edge

• Peer caches

• Access aggregation

20 Tier 1 COs

99 Tier 2 COs

C = centralized architecture

D = distributed architecture

Network transport costs reduced 47%

A Bell Labs case study compared the TCO of a

centralized IP edge to a distributed IP edge with CDN

content caches over the five-year period. Network model

was based on a large Tier 1 service provider in NA

Source: ALU WP - VIDEO SHAKES UP THE IP EDGE; 2012

20

Telecom Italia

Index






New business models

End-user

TELCO OTT Internet Access fees + premium services

CDN, ADN, ...

€ €

€ Services fees

Two–sides Business Model

Incremental revenues from OTT/CP: “Two-sides business model”

Telco Premium services offered to end users

To complement best effort IP traffic termination, Telcos are deploying QoE platforms and are offering differentiated quality for IP delivery to end-users and OTT/CP Examples of OTT/CP and Telcos agreements: Comcast/Netflix, Verizon/Google, Orange/Cogent, several Akamai agreements (including Akamai/Telefonica…)

Best-effort is not sufficient to meet requirements for Application/Content/Services in the ALL-IP scenario QoE platforms in the Domestic Network are needed

22



UBB+QoE = ACCESS MONETIZATION…

QoE enables Telco Premium services

QoE improvement enables incremental revenues from NGAN & LTE

Average UBB price uplift

Western EU

DSL Cable FTTx

To get a Premium Access Fee from UBB access:

• access bit-rate improvement is not sufficient

• higher application throughput and lower download time are needed

23



• Comcast must terminate Netflix traffic, to avoid end-users complaint & churn (~30% of Comcast customers are also Netflix customers)

• Comcast gets a “traffic termination“ revenue from Netflix, additional to the “access revenue” from end-users, in a two-sides business model. The Telco revenue is related to the “value” of the Application/Content that OTT/CP offers to end-users. In the Netflix case, the “value” is relatively small (“US $7.99 all you can watch”); in other cases, the “traffic value” is higher (e.g. Amazon services)

• Comcast goal is to handle Netflix traffic efficiently (…a huge traffic, e.g. 3Tbps, that will further grow)

• The agreement with Netflix facilitates Comcast use of more effective&efficient solutions to handle Netflix traffic (QoE platforms) enabling network cost saving

Netflix-Comcast case

24

NO deal • Payback Time = never

• Additional Revenues from OTT/CP • Payback Time estimate > 25 years

Deal, but no use

of QoE platforms

• Additional Revenues from OTT/CP • Capex saving = 25%-40% • Payback Time estimate = 10-15 years

Deal, and use of

QoE platforms

3 options



Internet Best Effort QoE capable network

Dumb Pipe

OTT

CP

Є

Є Access fee ADV

Є Differentiated quality

for IP delivery

OTT

CP

Є

Є

ADV

Є

Access fee

BestEffort Є

Content, Services

Content, Services

Є

Business models transformation guidelines

: Router/Server/Cache OTT: Over The Top; CP: Content Provider; ADV: Advertising

Premium Access Fee

Content, Services

New IP Interconnection Policy

Regulatory issues on Net Neutrality

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