white paper signalling storm
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SS7TRANSCRIPT
Overview
Mobile data consumption is increasing exponentially
because of sophisticated smartphones that drive
consumer demand for downloading, streaming,
browsing, and sharing content. While new types
of applications and feature-rich functionality
are proving extremely popular, they also pose
a significant challenge for operators given the
impact they have on network performance and
the customer experience. Many of these apps
are “chatty” in nature, signalling the mobile
network for hundreds and even thousands
of updates every hour.
Managing this mobile environment is made
more challenging because the ecosystem is in conflict.
Device manufacturers want improved battery life,
the app development community want the
“killer app”, while operators want increased
data usage with a good experience at a
lower cost to the network. This has to be
achieved using an infrastructure where
radio resources are limited and where the
volatile nature of today’s traffic is producing
wide, non-correlated variations in traffic volume, airtime
usage and radio signalling.
This excess signalling has a significant impact on network
resources, leading to poor customer experience and in
some case network outages. In Japan, NTT Docomo
recently suffered an outage that left 2.5 million customers
without a service for four and half hours. The operator was
already in the process of upgrading its network to cope with
increased signalling traffic from smartphones, a process
that has been ramped up significantly at considerable cost.
Continuous investment to increase capacity of the RAN
(Radio Access Network) is not economically viable.
Operators must seek alternative solutions to help them
stay ahead of the data curve. This must be achieved in
Managing the Signalling Storm
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a manner that addresses the most immediate need to
control signalling volume growth and extend smartphone
battery life without impacting on the customer’s Quality of
Experience (QoE ).
The Operator Dilemma
Smartphone success
Smart devices are growing at
an explosive rate, driven by the
demand for accessing feature-
rich content on the move.
According to Informa, smart
device shipments are expected
to reach over 500 million units in
2016. In tandem with this, the
growth of mobile applications
continues at pace with forecasts
predicting that the total number
of downloads will reach 185 billion
by 2014. This increase is driving
the adoption of Over The Top
(OTT) services, including a new
wave of Instant Messaging (IM) apps from third parties that
threaten operators with lost revenue and disengagement
with customers.
Existing operator business models are already being eroded
as the mobile Internet and open device platforms combine
to create new ecosystems for third-party application
developers. The mobile development community has
momentum and will continue to deliver applications across
multiple platforms and channels, offering more creative and
innovative messaging experiences.
Smartphone traffic patterns – bursty behaviour
While operator’s initial concerns were around the exponential
growth in data volume due to the widespread and growing
popularity of smartphones, issues relating to signalling
capacity have presented the operator with an even greater
challenge. The most popular smartphone applications –
including push email, social networking, online gaming and
news reports – combined with in-application advertising,
are “chatty” by nature and require regular connections to
the network for updates. These chatty apps send small
amounts of data (packet bursts) at very regular intervals
over separate short-lived connections. The requirement
characteristics of such apps cause a bi-directional ping-
pong of messages between the smartphone device and
application servers in the Content Delivery Network (CDN).
This frequent communication is known as transactional
behaviour and leads to a disproportionate increase in radio
signalling load relative to data transmitted.
As networks become congested with mobile data traffic
and the underlying signalling overhead associated with
devices constantly connecting and disconnecting from
the network, the customer experience can degrade to
unacceptable levels. Slow network response times, poor
battery performance, low data rates and dropped calls are
just some of the undesirable characteristics of a network
that is strained to its limits. Even with such overheads
placed on operators, they are still expected to deliver an
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INFORMA TELECOMS & MEDIA FORECAST ON SMART DEVICES BY OS : 2010-2016
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optimal quality of experience to their customers thereby
exacerbating the problem.
Application developers have little or no visibility into the
resource-constrained mobile execution environment
resulting in smartphone applications that are typically not
mobile friendly. However, the recent publication of the
‘Smarter Apps for Smarter Phones’ by the GSMA presents
a set of guidelines to encourage application developers
to write “better behaved” software. By following these
recommendations, developers will be better equipped
to create fit-for-purpose apps; mobile operators will
see a reduced strain on network overload, and users
will experience more responsive and reliable apps and
improved battery life.
Operators need to take their place profitably within the
value chain to mitigate risks and deliver the right value
and blend to their customers. They need to innovate their
business model to work more closely with all members of
the ecosystem and encourage adoption of frameworks
such as those outlined above. As a result, mobile operators
are forming a symbiotic relationship with application
developers and device manufacturers to ensure valuable
network resources and the customer experience are not
undermined.
Taking proactive measures – Intelligent network monitoring
It is essential operators have early visibility into the growth
and impact of chatty applications in order to ascertain the
potential impact on the radio network and to identify the
most appropriate strategy to alleviate the problem.
When reviewing this issue, the mobile operator cannot
test a single element in isolation. Instead, they must focus
on all contributing factors. The same application running
on different devices and OS versions may have a vastly
different effect on the network.
By using intelligent network monitoring systems, the
operator can glean insights into which applications,
devices, OS versions and combinations of each are
contributing most to increased signalling load on their RAN.
Using a signalling load or aggressiveness score against
each of these dimensions enables operators to address the
issue early.
Armed with this actionable intelligence through real time
reporting, the operator can set about implementing a
strategy to ensure an optimum performance balance for
handsets, their batteries, applications, networks, and most
importantly the end user.
Operators need to take their place profitably within the value chain to mitigate risks and deliver the right value and blend to their customers.
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Measuring the impact of application signalling
Actionable insights into network traffic offer a unique and
pre-emptive approach to the problem because they identify
potential issues before the full force of the signalling affects
the customer experience. Armed with the right intelligence,
operators can avoid costly network upgrades that are an
expedient response to excess signalling that undermines
the customer experience.
To measure signalling impact, operators need to capture
detailed profiles of mobile applications in addition to
undertaking proactive modelling. Being able to measure
the bursty behaviour of apps, coupled with the ability to
identify apps before they go viral, are valuable weapons for
operators as they look to control the impact of application
signalling.
a. Profiling mobile applications
In order to accurately assess how efficiently an application
(or device/user/operating system) is utilising radio signalling
resources to transmit and receive data, the application
traffic is characterised in terms of packet bursts. By
using bursts to analyse the traffic, it is possible to extract
information about activity and inactivity periods during a
data session.
Consider a typical smartphone user with multiple
applications running in parallel (e.g. Gmail, WhatsApp,
Facebook, Google maps). Each application exhibits a
different traffic pattern and will send packets into the
network over separate data streams. Small amounts of
data are sent at irregular intervals causing the user’s device
to wake up, send some data and go back to sleep.
The latency between application bursts causes the device
to transmit between Idle and Connected mode
each time a connection is required to send
data. This causes a massive surge in radio
signalling due to the high number of RRC
state promotions and demotions involved
(~26 RRC messages round trip per connection
setup). Based on these insights, sessions with
anomalous traffic burst patterns are obtained
and the cumulated impact of applications and
devices on radio signalling capacity is exposed.
b. Proactive modelling
By extracting properties of traffic that exhibit
inefficient bursty behaviour, it is possible
to proactively identify new threats to RAN
resources if certain combinations
of applications and devices with
inefficient behaviour increase in
popularity.
For example, an application
might be very bursty but not very
popular, thereby having little impact
on signalling capacity. However,
if that application goes viral and its
popularity increases exponentially in
a short period of time, the cumulative
impact of bursty behaviour across a high
number of devices will significantly increase
the signalling involved and pose a real threat
to the normal functioning of the RAN.
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SMARTPHONE SALES FORECASTS 2012 - 2016 (MILLIONS OF UNITS)
REGION 2012 2014 2016
NORTH AMERICA 105.51 118.92 127.4
LATIN AMERICA 34 59.43 94.15
ASIA PACIFIC 178.63 249.04 344.24
EUROPE 162.79 192.94 221.24
MEA 39.06 59.66 82.98
TOTAL 520 680 870.02
Conclusion
Signalling volume growth poses a significant
challenge for mobile operators that will only get worse.
Mobile data services are a hotbed of innovation and a
commercial opportunity that app developers and third-
party providers will continue to explore, putting more
strain on the network, creating greater challenges
for operators as they try to ensure the best possible
customer experience for their customers.
Investing in network capacity, building ecosystem
partnerships and attempting to optimise assets and
devices may offer a short-term fix, but long-term,
operators need to become more proactive and assume
the driving seat.
With intelligent network monitoring and by measuring the
precise impact of signalling by device, application and
service, the operator is in a much better position to deal
with the challenges and manage the storm.
About The Now Factory
The Now Factory provides operators with rich insights
around the use of mobile data services, helping optimise
the customer experience and drive greater profitability.
By providing tools and solutions to quickly detect and
measure the effects of emerging applications on the
network, The Now Factory enables operators to be proactive
and plan against the impact of excessive signalling, rather
than respond with expedient measures that are short-term
and expensive.
The Now Factory empowers operators to mitigate the risk
of network degradation and poor customer experience, all
the time driving increased cost-efficiencies.
Copyright © The Now Factory 2012. All Rights Reserved. All data contained in this white paper is for information purposes only and is subject to change without notice.
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