broadband paradox and mobile cloud

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Broadband Paradox and Mobile Cloud By : Dr.Ir.Joko Suryana Laboratory of Radio Telecommunications and Microwave Reference sources: Internet

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Page 1: Broadband paradox and mobile cloud

Broadband Paradox and Mobile Cloud

By : Dr.Ir.Joko SuryanaLaboratory of Radio Telecommunications and Microwave

Reference sources: Internet

Page 2: Broadband paradox and mobile cloud

Outline

• Mobile and IP-based services :– Mobile and Internet

Subscriptions

– Device Adoption

– Global IP Traffic

– Global Mobile Traffic

• Mobile Broadband Paradox – Introduction

– The Paradoxes

– Current Findings

• Mobile Broadband Facts :– European Market

– Indonesian Market

• ‘Traditional’ Operator Strategy

• Mobile Cloud Approach– Traditional Telco vs OTT

Operator

– Telco+OTT Approah

– Mobile Cloud Business

– Softbank Study Cases

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GLOBAL IP TRAFFIC 2010-2015

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Cisco Global IP Traffic 2010-2015

• Total IP Traffic 80.5 Exabytes per month by 2015 – By 2015, annual global IP traffic will almost reach a

zettabyte• Fixed Internet 59.4 Exabytes per month by 2015

– By 2015, one million video minutes cross the network each second

• Managed IP 14.8 Exabytes per month by 2015 – Business IP video conferencing will grow six-fold from

2010-2015 • Mobile Data 6.3 Exabytes per month by 2015

– Mobile video will increase 26-fold from 2010 to 2015

Source: Cisco Visual Networking Index (VNI) Global IP Traffic Forecast, 2010–2015

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Entering Zettabyte Era

• By 2015, global IP traffic will reach an annual run rate of 966 exabytes per year

• 966 Exabytes is equal to:

– 8X more than all IP traffic generated in 2008 (121 EB)

– 28 million DVDs per hour

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Global Device Number : By 2015 there will be 1.5 B Device

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Global Device Adoption 2011

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Smartphone OS Market Share 2011

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Global Device Number : Generated Traffic by Device

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Global IP Traffic 2010 – 2015 : Regional Contribution

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Global IP Traffic Drivers 2010-2015

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Global Mobile Traffic 2012

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INDONESIA INTERNET PROFILE

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Global Internet Users 2011

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Global Mobile Users 2011

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Profile of Indonesian Internet Users 2011

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Indonesian Mobile Broadband: Subscriber Subscription

• Total number of cellular subscribers in Indonesia, has reached 225 million in 2010 with an average 1.33 SIM cards used per person, it is estimated that there are approximately 168 million mobile phones in Indonesia.

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Indonesian Mobile Operator ProfilesBB Infrastructure 2011-2012

FY 2011 Q1 2012

Telkomsel XL Indosat Telkomsel XL Indosat

Internet BW 20 Gbps 5 Gbps 8.36 Gbps 20 Gbps 5 Gbps 8.36 Gbps

BW of Blackberry (RIM) 5 Gbps 3 Gbps 2.7 Gbps 5 Gbps 3 Gbps 2.7 Gbps

Mobile Internet Subscribers 45 millions 25.5 millions 20 millions 48 millions 29 millions 22 millions

Mobile Broadband Subscribers 6.7 millions 3.7 millions 3 millions 8.6 millions 7 millions 5 millions

Blackberry Subscribers 3.6 millions 1.8 millions 1.7 millions 4.4 millions 2.5 millions 2 millions

Traffic per day 115 TByte 66 TByte 36 Tbyte 115 TByte 66 TByte 36 Tbyte

Node-B BTS 9500 4910 3400 10000 5000 3500

FY 2012 Outlook

Telkomsel XL Indosat

Internet BW 35 Gbps 10 Gbps 10 Gbps

BW of Blackberry (RIM) 10 Gbps 8 Gbps 5 Gbps

Mobile Internet Subscribers 56 millions 36 millions 28 millions

Mobile Broadband Subscribers 15 millions 14 millions 8 millions

Blackberry Subscribers 6.5 millions 3.5 millions 3 millions

Traffic per day 200 Tbyte 120 Tbyte 80 Tbyte

Node-B BTS 11000 8000 5000

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Mobile Broadband Market Size 2012 The Big Three : TSEL, XL, ISAT

• Data ARPU and Infrastructure Profile :– Data ARPU ( blended )

• Rp 100.000 per month (Q1 2012)• Rp 70.000 per month (Q4 2012)

– Total BTS Networks :• 24.000 Node Bs

• Bandwidth Estimation Profile :– Internet BW

• 60 Gbps

– RIM Bandwidth : • 23 Gbps

• Data Business 2012 Profile :– Total data subscribers

• 37 million user• 12 x Rp 70.000 x 37 million

• Rp 31 trillions

Providers Data PlanBenefit

(Price – Volume – Speed)

Telkomsel Flash UnlimitedIDR 100,000 – 1 GB – max 1 Mbps

IDR 200,000 – 2.5 GB – max 2 Mbps

Indosat Paket Browser Bulanan IDR 100,000 – 1 GB – max 1 Mbps

XL Hotrod 3GIDR 99,000 – 2.5 GB – max 3.6 Mbps

IDR 199,000 – 6 GB – max 3.6 Mbps

AxisBulanan Premium

Bulanan Ultimate

IDR 79,000 – 1 GB – unknown

IDR 200,000 – 2.5 GB – unknown

3 Paket Internet 3

IDR 50,000 – 1 GB – unknown

IDR 75,000 – 2 GB – unknown

IDR 125,000 – 5 GB – unknown

BakrieSuper Giga

Ultimate

IDR 100,000 – 2 GB – max 3.1 Mbps

IDR 500,000 – 35 GB – max 3.1 Mbps

Smart Paket Data

IDR 50,000 – 2 GB – max 3.1 Mbps

IDR 100,000 – 6 GB – max 3.1 Mbps

IDR 150,000 – 12 GB – max 14.7 Mbps

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Indonesia International BW 2010-2015

Fixed BB 2011: 100 GbpsFixed BB 2012 :120 Gbps

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MOBILE BROADBAND PARADOX

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Mobile Broadband Paradox : Definition

• Mobile broadband is increasing rapidly both when it comes to traffic and number of subscriptions. – The swift growth of the demand

will require substantial capacity expansions.

• Operators are challenged by the fact that :– Revenues from mobile

broadband are limited, just a few per cent of ARPU, and thus not compensating for declining voice revenues , creating a so called :

“Broadband Paradox”

Traffic Increases rapidlyRevenue grows at low level

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Broadband Paradox : Mobile Data Traffic Behavior

The data services are dominating type of traffic in the networks

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Broadband Paradox : Mobile Data Revenue Behavior

But the data services revenue contribution is at a low level

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Broadband Paradox #1 : Revenue

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Broadband Paradox #2 : Service

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Broadband Paradox #3 : Network

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Broadband Paradox #4 : Investment• Mobile operator problem :

– Data traffic and the need for additional network capacity ( investments) are increasing substantially

– While revenues are growing at a very low level

Scalability of cellular systems :• For a specified amount of spectrum and

for the same type of Radio Access Technology :

– deployment of N times morecapacity will imply N times higher network costs.

• The cost is proportional to the number of users, the demand per user, the service area and also a function of quality

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MOBILE BROADBAND CURRENT FINDINGS

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Findings From Current Development

A. Mobile broadband unable to drive revenues• The data points underscores that operators are highly

dependent upon the revenue stream from the voice business.

• It requires limited network capacity as voice customers only generates 10 MB of traffic per month, while mobile broadband users in average consumes 130 times more traffic, paying only 1% of the price per MB compared to voice.

• This asymmetry is unsustainable, although low utilization rates in the UMTS networks initially can handle the increased load factors.

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Findings From Current Development

B. Operators forced to look for new revenue streams

• This forces operators to launch new value added services to compensate for a deteriorating voice business.

• But this has so far been unsuccessful, illustrated by the limited interest users have showed for mobile videoconference, mobile-TV, and gaming.

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Findings From Current DevelopmentC.Lower free cash flow restricts capex• The financial crisis has placed the focus on debt making

operators more cautious on capex in order to have the ability to service debt, pay dividends and strengthen their balance sheets.

• But the operators’ ambition to expand aggressively onmobile broadband requires capex upgrades.

• Given that mobile broadband generates no cash flow it weakens operators financially in a time when investors and banks are favoring financial stability.

• This forces operators to make strategic prioritizations and subsequently alter business models for mobile broadband.

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MOBILE BROADBAND FACTS : EUROPEAN MARKET

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Broadband Paradox : Traffic Facts(European Mobile Operators)

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Broadband Paradox : Revenue Facts(European Mobile Operators)

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Broadband Paradox : Revenue Facts(European Mobile Operators)

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MOBILE BROADBAND FACTS : INDONESIAN MARKET

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Indonesian Mobile Broadband : Voice Traffic and Revenue

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Indonesian Mobile Broadband : SMS Traffic and Revenue

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Indonesian Mobile Broadband: Data Growth is Picking Up

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Indonesian Mobile Broadband: 3G NodeB Investments

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Indonesian Mobile Broadband : The Lowest Usage in the Region

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Indonesian Mobile Broadband : Capex Still High in the Region

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Telkomsel Mobile Broadband : Data Revenue vs 3G CAPEX

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XL Mobile Broadband : Data Revenue vs 3G CAPEX

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Indosat Mobile Broadband: Data Revenue vs 3G CAPEX

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TYPICAL OPTIONS FOR OPERATOR STRATEGIES

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Operator OptionsStrategy to bridge the revenue gap :1. Network sharing : all forms of operator

cooperation where sites or parts of the radio access networks are shared.

2. Spectrum refarming : replace or mix radio access technologies in specific frequency bands.

3. Offloading heavy data traffic : to local networksor indoor systems.

4. Pricing strategies and service differentiation5. New types of services and revenues : M2M, NFC

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1. Network sharing

• Network sharing includes all forms of operator cooperation where sites or parts of the radio access networks are shared. This is a form of long term cooperation.

• In Sweden all 3G operators are involved in different types of joint ventures, and a new constellation has been announced regarding the deployment of LTE.

• The cost savings can be in the range 20-40% depending on the level of sharing :– The potential for saving is obvious when you consider coverage

and macro base station deployment where the site costs are large

– For capacity expansion in urban areas the potential savings with shared networks would presumably be much lower.

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2.Spectrum Refarming

• Another way to exploit current networks and re-use existing sites is to replace or mix radio access technologies in specific frequency bands. – One example is the 900 MHz band where WCDMA, HSPA or LTE can replace

GSM/EDGE resulting in increased capacity per site and MHz of spectrum. WCDMA in the 900 MHz band implies that 3G coverage can be achieved with a lower number of sites than in the 2.1 GHz band. Hence, these benefits would be most valuable for wide area coverage.

– On the other hand the present usage of the 900 MHz band is for GSM and EDGE. So when calculating the benefits the costs for the whole WCDMA implementation has to be included. These costs have to be covered by the additional revenues resulting from WCDMA.

• Nokia Siemens Networks claims that the total savings in capex and opexcan be up to 60%, i.e. total cost of ownership (TCO) is reduced to 40% compared to deployment in the 2.1 GHz band.– For indoor coverage the benefits of the above mentioned type of spectrum

refarming is more difficult to exploit than for wide area coverage. – In urban areas high capacity is already achieved by dense deployment of

macro or micro sites using WCDMA or HSPA operating at 2.1 GHz.

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2.Spectrum Refarming: Indonesia Context

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3. Offloading Heavy Data Traffic

• Instead of deploying a large number of outdoor base stations for mobile broadband the heavy data traffic can be offloaded to local networks or operators using indoor systems .

• In addition to the potential of substantially lowered network costs a number of other motivations can be identified:– the data traffic is mostly (~90% ) generated indoors– the users are stationary or nomadic– the users are ”known” (at the office or at home)– no need to deal with wall attenuation

• Compared to capacity expansion using macro or micro base stations the use of cellular femtocells or WLAN systems indicate cost savings in the range 20 times .

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3. Offloading Heavy Data Traffic

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4.Pricing Strategies and Service Differentiation

• Currently the flat rate subscriptions area associated with some type of restrictions, e.g. maximum amount of data per month (1GB, 5GB) and maximum data rate (384 kbps, 3,8Mbps, 7Mbps). – Operator “3” in the UK offers

subscriptions with different maximum amount of data per month, e.g. 1 GB for £10, 5 GB for £15, and 15 GB for £30.

– Heavy data users have to pay more. – This kind of pricing scheme is a way

to handle the “waste” problem associated with flat rate.

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4.Pricing Strategies and Service Differentiation ( Continue )

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5.New types of Services and Revenues

• M2M Services

• NFC-based Services

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MOBILE CLOUD BUSINESS MODEL

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Traditional Telco Business Model :Current Service delivery positioning

• Telcos are becoming dumb pipes for service providers

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Traditional Telco is a Dumb Pipe

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Traditional Telco Business Model :Approach doesn’t work

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Telco 1.0 vs Telco 2.0

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Two Sided Model : Google

• Google is a ‘two-sided’ business model master

• Telco Business should consider the Google business model

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Google vs Vodafone = 2-sided vs 1-sided

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Two Sided Model :Open up more markets for Telco platform

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Two Sided Model : Cloud Service Provider by Telco

Three Major Tasks :

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Mobile Cloud Service : Architecture

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Cloud Service Center

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New Business Model : : OTT+Telco

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Telco and OTT Worlds

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Telco+OTT World

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Telco+OTT World

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Value Chain of Mobile Cloud

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Sample of Mobile Cloud Services

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Leading Mobile Operator : Mobile Cloud Operator

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Mobile Internet Evolution

• Mobile Internet 1.0 : – The first wave of mobile data connectivity was very rudimentary with

technologies such as CDPD, GPRS, and messaging (SMS).

• Mobile Internet 2.0 : – The next wave brought in better devices, faster networks and the

consumers started migrating their tasks, content creation and consumption behavior to the mobile platform

• Mobile Internet 3.0 : Mobile Cloud Operator– Is defined by the cloud-enabled, software driven, IP-centric, high-

speed 4G+ networks; the consumers using multiple connected devices; the flattened value-chains; and the operators relying on mobile data services for majority of their revenues

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Cloud Computing Evolution

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Mobile Cloud :Service and Application Areas

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Mobile Cloud :Service and Application Areas

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Mobile Cloud :Service and Application Areas

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Mobile Cloud :Service and Application Areas

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Mobile Cloud :Service and Application Areas

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SUCCESS STORY : SOFTBANK

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History

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Group Sinergy

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Group Network

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Softbank Performance

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Softbank vs Competitor

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Top Brand

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ARPU and Subscribers

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Winning Formula

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Traditional Mobile Services

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New Mobile Services

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Cooperation Network Technologies

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Increase Capacity

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Content and Applications : Softbank

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Thank You