Transcript Building the Mobile Internet

Building the Mobile Internet
Introduction to Mobility
Mobility Market
Growth in Mobile versus Fixed Broadband Subscribers
Wi-Fi-Enabled Handsets (Millions)
Millions
600
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300
200
100
0
2006
2007
2008
2009
2010
2011
2012
Growth in Wi-Fi-Enabled Handsets
2013
2014
2015
Factors Driving Multiple Device
ownership (1)
• Desktop PCs: Growth will be driven by
gaming as well as by watching and editing
high-definition and three-dimensional
video and graphics i.e. activities and
processes not suited to relatively lowerpowered devices like tablets, Phablets,
and Smartphones
Factors Driving Multiple Device
ownership (2)
• Tablets: Growth driven by their ease of
media-consumption, in addition to email
access, web-browser-based services, and
office productivity support.
Factors Driving Multiple Device
ownership (3)
• Phablets: Growth driven by high-quality
architectures with secure data access and
Enterprise Productivity support:
• Also Entertainment and Games
applications designed for maximum impact
on these and Smartphones.
Other Growth Drivers
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Pervasive Software Apps
Context-Aware System Architectures
Cloud Service Architectures?
? Think of other possibilities ?
The Future of Mobile Markets
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Device Divergence
Network Convergence?
IP Everywhere
Fixed and Cellular (Mobile) Networks: IP
is the ‘fundamental Building Block’
• All data Transmission is Packet-Switched?
• Three scenarios are illustrated in the next
slide:-
Early Indication of Data Consumption Trends
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$0
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Voice
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Data
Average Revenue per US Mobile Subscriber
PBytes/Month
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2014
Monthly Mobile Internet Traffic in Petabytes (Cisco VNI Forecast)
What, Where and When?
We have looked at where consumers consume mobile Internet services,
And also at what type of services are likely to be consumed using mobile
Devices, in future.
We must also consider When users access mobile services.
The next slide is an representation of the traffic load in a commercial cellula
network offering mobile Internet services over a 24-hour period.
The figure clearly illustrates the diurnal variation of traffic load within the
network, showing how the ‘data-busy’ hour is between 8.00 and 9.00 in the
evening. (20:00 -21:00 hours)
Global Mobile Data Traffic, 2014 to 2019
Overall mobile data traffic is expected to grow to 24.3
exabytes per month by 2019, nearly a tenfold increase over
2014.
Mobile data traffic will grow at a CAGR of 57 percent from
2014 to 2019
Source: Cisco VNI Mobile, 2015
Towards an ‘Always-On’ scenario:
Current cellular network standards allow mobile data-enabled devices to
Be attached to a cellular network without allocating them an IP address.
Legacy cellular networks are typically configured to automatically de-allocate a
device’s IP address after a period of inactivity.
The new generation of cellular standards are designed only to support alwayson behaviour, and so, for example, when a device attaches to an all-IP LTE
network, it must, by default, receive an IP address and be automatically enabled
to send and receive IP packets.
mi100209
Mobile Challenges
Cisco Virtual Network Forecast:
Read this Cisco White Paper:
http://www.cisco.com/c/en/us/solutions/
collateral/service-provider/visualnetworking-index-vni/white_paper_c11520862.html
Take time to study this in detail…
Cisco Forecast in 2014:
Cisco Forecast in 2015
What does this mean?
• 15.9 Exabytes of Mobile Data Traffic:
• 24.3 Exabytes of Mobile Data Traffic:
Bytes ??? (Disk Storage)
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Kilobyte = 1000 bytes
Megabyte = 1000 KBytes
Gigabyte = = 1000 MBytes
Terabyte = 1000 GBytes
Petabyte = 1000 TBytes
Exabyte = 1000 Pbytes = ?? Bytes
Bytes (Virtual Storage) ???
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Kilobyte = 210 bytes = 1024 bytes
Megabyte = 220 bytes 1048576 bytes
Gigabyte = 230 bytes = 1073741824 bytes
Terabyte = 240 bytes = ?
Petabyte = 250 bytes = ??
Exabyte = 260 bytes ≈ 1.1529 x 1018 bytes
Mobile Consumer Trends
• http://www.cisco.com/c/en/us/solutions/ser
vice-provider/vni-service-adoptionforecast/index.html
Cellular Network Capacity:
Key Limiters
There are three key cellular
characteristics:
• Spectrum
• Spectral Efficiency
• Frequency reuse
The speed at which data can travel to and from a mobile
device can be affected in two places:
the infrastructure speed capability outside the device, and
the connectivity speed from the network capability inside the
device (Figure 22).
These speeds are actual and modeled end-user speeds and
not theoretical speeds that the devices, connection, or
technology is capable of providing.
Several variables affect the performance of a mobile
connection:
•Rollout of 2G/3G/4G in various countries and regions,
•technology used by the cell towers,
•spectrum availability,
•terrain,
•signal strength, and
•number of devices sharing a cell tower.
•The type of application being used by the end user is also an
important factor. Download speed, upload speed, and latency
characteristics vary widely depending on the type of
application, be it video, radio, or instant messaging.
Mobile Challenges
The massive increase in forecast
consumption of mobile services
imposes serious challenges to the
current Internet, its structure and
in particular, to its protocols
Lets look at this in a little detail…
Spectrum
• Spectrum is a scarce resource.
• Higher speed transmission
needs sufficient bandwidth and
enough energy for wide signal
propagation
• Governments auction the
spectrum for vast sums of
money.
• We can’t make new spectrum
• The laws of physics apply!
Spectral Efficiency (1)
• Efficiency of use is critical
• Shannon’s Law determines the
maximum data transmission
rate possible in ‘noisy’
transmission channels: i.e. the
maximum amount of
information that can be
transmitted.
• The most advanced signalprocessing techniques are at or
near this limit.
Spectral Efficiency (2)
• Shannon’s Law
• C = B log2(1+S/N)
• Shannon’s limit is sometimes
referred to as ‘theoretical’
• It is, however, a factual law of
physics.
• Andrew Tanenbaum states:
‘Counter-examples should be
placed in the same category as
Perpetual-motion machines’…!
Frequency Re-use
• Spectrum is scarce and mobile
systems must re-use their
allocated radio frequencies
across any given cell network;
• Increasing capacity by re-use
means smaller cells and more
cell ‘tower’ transmitters.
Future Capacity
• Forecasts suggest a 39-Fold
increase in demand for mobile
Internet traffic:
(over approximately 5-years
2013 - 2018)
• Better use of the spectrum
offers, at best, a four-fold
increase in capacity in the
same period.
Future Capacity (2)
• Increased use of smaller cells is
the only option if the forecast
demand is to be met.
• If the demand estimates are
correct then the number of cells
in any given cellular network
will need to increase 10-fold to
achieve the required capacity.
The Future Mobile Internet
• Scalable adoption of small-cell
technologies: IEEE 802.11and
‘Home-Cells’
• Massive numbers of always-on
devices with singlesubscription-multiple-device
being the norm:
• Ubiquitous access from
anywhere, indoors or outdoors:
• Seamless service access to
Video, Web, Peer-to-Peer, VoIP
and Games (and more…)
The Future Mobile Internet
The Key problems and Challenges:
• Spectrum Limitation is clearly a
major problem:
• A second problem, just as
challenging is the inherent
design of the Internet and its
primary protocols
The Internet is not Mobile..!
• Unfortunately the Internet does
not support ‘native-mobility’
• The TCP/IP stack was not
designed with mobility in mind.
• Much has been achieved, but
the approach has been by the
development of ‘Tunneling
Protocols’
The Internet is not Mobile..!
• Tunneling means essentially
using existing IP packets as
‘wrappers’, and running
everything over the existing
structure.
The Internet is not Mobile..!
• However, we shall see that
seamless, real-time mobility
requires that ‘sessions stay
alive’ when devices move
between different types of
access networks and across
networks belonging to different
operators.
The Internet is not Mobile..!
• What is required is the
capability to implement what
has become known as
‘Session-mobility’.
• This is a a very tough
challenge;
• However, if it can be achieved,
the potential benefits for
communications is enormous.
The Internet is not Mobile..!
• To understand the problem we
need a detailed understanding
of the way that the Internet
works.
• We need to appreciate the
limitations of current Mobility
‘solutions’;
• Then we can begin to consider
new approaches to building a
truly ‘Mobile Internet’
Fixed-Cellular Convergence: Three Scenarios:
Wireless Residential
Gateway
(Access Point)
WiFi
Enabled
Tablet
DSLAM
Broadband
Network
Gateway
IP/Ethernet
Transport
Network
Home
ENB
Cellular
Smartphone
Macro
ENB
Internet
Packet Data
Network/
Serving
Gateway
Correspondent
Node
References
Texts:
 Building the Mobile Internet
• Grayson et. al.
 Computer Networking: A top-Down Approach
6th ed.

Kurose and Ross
Other Reading

Computer Networks 5th ed.
 Andrew Tanenbaum
 Claude E. Shannon

Shannon’s Law (See next slide)
The Ultimate Limit:
Shannon’s Law
Shannon’s law is simple and elegant: It states that
C = B log2(1 + S/N)
where
C is the capacity of the channel in bits per second
B is the channel bandwidth in Hertz
S is the average received signal power over the bandwidth
N is the average noise or interference power over the bandwidth, measured in watts (or
volts squared); and
S/N is the Signal-to-Noise ratio (SNR)
So, for example, if we have a communications channel with a signal-noise ratio of, say
30db, then the signal is 1000 times stronger than the noise and the S/N = 1000
If the available bandwidth is 100 MHz, (100,000,000 Hz), then the channel can transmit
996,722,625 bits per second. i.e. 996 Mbps. Almost 1Gbps.
Note that an S/N of 1000 is very high and very difficult to achieve.
In a wireless network S/N varies widely. Work out the bandwidth needed to provide a 1Gbps
bit rate on a Wi Fi network if the S/N ratio is 100
The Ultimate Limit:
Shannon’s Law
Exercise:
Work out the bandwidth needed to provide a 1Gbps bit rate on a Wi Fi network if the S/N
ratio is 10
Then, In a wireless network S/N varies widely. Work out the bandwidth needed to provide a
1Gbps bit rate on a Wi Fi network if the S/N ratio is 2