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SOS: Signalling Overload due to Smart devices WHITE PAPER Dr Konstantinos Stavropoulos IOT Product Manager, Anite FEBRUARY 2011

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  • SOS:Signalling Overloaddue to Smart devices

    WH

    ITE

    PAP

    ER

    Dr Konstantinos Stavropoulos IOT Product Manager, Anite

    FEBRUARY 2011

  • SOS: Signalling Overload due to Smart devices 1Anite 2011

    Contents

    1 ExEcUtivE SUmmARY

    2 intRoDUction

    3 thE EmERgEncE oF SmARt DEvicES

    4 EvERYthing FlowS: A moBilE StAtE oF FlUx

    5 AlwAYS (?) on

    6 nEtwoRK DiStRESS SignAlling

    7 SoS EvAlUAtion

    8 SmARt DEvicES, SmARtER intERopERABilitY

    APPendIces

  • SOS: Signalling Overload due to Smart devices 2Anite 2011

    1 EXECUTIVE SUMMARY

    An indispensable part of our daily routine, smart devices are causing many wireless networks to

    suffer, and not only due to the insatiable user demand for data. these always on, signalling-hungry

    devices do not communicate with the wireless network in a smart or efficient way. this signalling

    issue has been amongst the least publicised up to now, and is the subject of this paper Signalling

    overload due to Smart devices: SoS.

    Smart devices give the impression of being always on, whereas in reality they repeatedly wake

    up to ping the network for updates and then go back to sleep. A 3g device can be in different

    radio states, which can be simply described as high, low, Standby, and idle. in brief, the high

    state supports data throughput with the most network resources reserved and the device battery

    burden at its peak, while idle is where devices stay dormant, save power and are periodically active.

    Signalling accounts for as much as 60% of an operators network costs. Applications such as

    mobile email or social networking demand constant updates and a smartphones signalling may

    be eight times less efficient than a pc/laptop dongle, and does not bring in any extra revenue. SoS

    will become an even bigger headache as smart devices get cheaper, more user-friendly, and provide

    access to more/better content (apps).

    SoS influences user experience too. Signalling affects network connections and battery life.

    Subscribers expect a lot from smart devices and are likely to use them less or even churn if these

    do not live up to expectations. Ultimately, an operators profit can be negatively affected by SoS.

    Reactive methodologies such as real-time monitoring and field testing help to understand the

    impact of SoS. however, they are costly and have limited preventative use. in contrast, laboratory

    testing is the proactive approach that has helped accelerate the time to launch new devices in a

    cost-effective fashion. Using a network simulator in the lab, it is possible to test and compare the

    signalling behaviour of different smart devices and applications before they are launched.

    As the SoS issue is acknowledged across the industry, operators have started to look at ways

    to enhance the interoperability of smart devices with their networks by considering additional

    network resources, new technology features and/or more network intelligence. more importantly,

    operators want to get the ecosystem with manufacturers and application developers working

    effectively, in a similar fashion to the successful operator-driven acceptance programmes that have

    substantially reduced the time to market of new devices. operators can simply not afford to ignore

    this SoS.

  • SOS: Signalling Overload due to Smart devices 3Anite 2011

    2 INTRODUCTION

    many mobile industry experts have been surprised by the remarkable success that smart devices

    have enjoyed in the last few years. having become an indispensable part of our daily routine, these

    devices now dominate the news headlines on a regular basis.

    As the mass appeal of smart devices increases, issues relating to their operation and performance

    gain in significance. this document focuses on one of these issues, which has probably been

    amongst the least publicised up to now: Signalling overload due to Smart devices.

    this paper is organised as follows: first, we look at the emergence of devices classified as smart,

    then we discuss the related topic of mobile device radio states, investigate what always on

    actually means for smart devices, analyse the impact of these devices on network signalling, and

    finally describe the key methodologies used to evaluate and to address this impact.

  • SOS: Signalling Overload due to Smart devices 4Anite 2011

    3 THE EMERGENCE OF SMART DEVICES

    smartphone a mobile phone that supports more advanced (Pc-like) applications than a basic

    feature (voice-centric) mobile handset.

    smart (mobile) device a carried or worn, multi-purpose (mobile) device that acts as a mobile

    phone, a camera, a personal organiser, a games console, etc. which can operate as a portal and

    incorporate internal or typically accessed via wireless networks external applications.

    As wireless networks started to become more and more successful, there were very few handsets

    that could be called smart. in effect, these smart handsets or smartphones were seen as a niche

    market segment, which could address the needs of relatively speaking a small number of

    mobile users. the status quo has now changed dramatically, with (first) the advent of mobile email

    and (more recently) the unprecedented success of mobile applications or apps that the launch

    of the iphone spearheaded.

    Smartphones have been the mobile device success story for the last two to three years, and the

    trend is set to continue. the demand for smartphones has been driving the growth of handset

    sales, and specialised vendors such as Apple and Rim now find themselves in the top-5 mobile

    device manufacturers. in addition to mobile handsets, other smart devices appear to be quite

    successful: wireless tablets (such as the ipad) have been launched, with sales likely to exceed the

    50 million-unit threshold as early as 2011. Yet, this smart device boom, which has led to 600

    million mobile broadband subscriptions in 2009, has come at a price.1

    As one of the main drivers behind the mobile data explosion phenomenon, smart devices are

    also the reason why many wireless networks worldwide are now suffering, and not only because

    of the insatiable user demand for data. indeed, these always on, signalling-hungry devices are

    not currently communicating with the wireless network in a smart or efficient way, which is

    causing concern for many 3g network operators. the situation may actually deteriorate with

    next-generation mobile systems (such as ltE) and when wireless devices are embedded in every

    consumer machine.

    it therefore seems that, at least with regard to network signalling, smart devices may have been

    smart-looking, fashionable gadgets that have dazzled the public rather than the intelligent, efficient

    contraptions that their naming implies. But is the Signalling overload due to Smart devices an

    issue of real concern, an SoS for mobile network operators, or an exaggerated myth?

    1 For simplicity, the term smart device has been used in this document to refer to smart mobile devices, irrespective of their handset/

    tablet/other nature. the term does not include mobile network dongles or embedded pci cards.

  • SOS: Signalling Overload due to Smart devices 5Anite 2011

    4 EVERYTHING FLOWS: A MOBILE STATE OF FLUX

    Before looking in detail at the issue of signalling overload due to smart devices, it would be useful

    to consider the different radio connection states that a 3g device can be in, according to the 3gpp

    standards (holma and toskala, 2010). this is particularly important to understand why smart

    devices have an adverse impact on network signalling.2

    A 3g device can be in one of the following states in terms of Radio Resource control (RRc)

    connection strictly speaking, the idle state is not a connected state:

    1 High also described as Dch or cell Dch or hSpA in this state, the device is communicating

    with the network in a dedicated fashion, which requires the most network resources and the

    highest device power (compared with the other states).

    2 Low also described as FAch or cell FAch in this state, the device communication with the

    network requires some network resources (also supporting data throughput at low rates) and

    some device power, but has a lesser burden than the high state.

    3 Standby also described as URA, URA pch or cell pch in this state, the network is aware of

    the device, but there is no requirement for network resources to be consumed (cell pch is

    different from URA pch, but considered similar herein for simplification reasons).

    4 Idle in this state, the network is aware of the device, but the device is in sleep mode, not

    really communicating with the network and therefore requiring the least amount of network

    resources and consuming the least power (compared with the other states).

    Users of smart devices require long battery life, while networkoperators require signalling efficiency. Our testing must takesuch requirements into account.Group Leader, Research, Leading Mobile Network Equipment Vendor

    2 this document focuses on 3g, as it is wcDmA/hSpA networks that have driven the proliferation of smart devices by being able to

    support data throughput rates comparable to those of fixed-line networks.

  • SOS: Signalling Overload due to Smart devices 6Anite 2011

    Figure 1 illustrates these different states in a simplified fashion. it also depicts the high-

    level relationship of each state with the device power (battery) and data (throughput/speed)

    performance as well as the burden on network resources.

    in summary, with regard to device power, data throughput and network resources, the state of the

    mobile device can be:

    High, to achieve the highest possible data throughput (and shortest latency), with the most network resources reserved and the device battery burden at its peak

    Idle, to stay dormant and save power by only being periodically active, with data transmission not supported.

    So, a mobile device will generally switch from one state to another as depicted in Figure 1,

    depending on the use scenario. typically, transition to a more active state will be triggered by

    data packets (with the high or low state selected based on data volume), and transition to a less

    active state will be triggered by device inactivity (based on an inactivity timer). it is this state

    transitioning that causes increased signalling from smart devices, particularly when the device is in

    sleep mode and needs to wake up and move to the high state.

    the original aim of the 3gpp standard was for devices to move to the power-efficient Standby

    (pch) rather than the idle state after data transmission is over. the idle state was to be avoided as

    transitions to the high state require a packet connection setup, and hence increased latency and

    network signalling. however, the Standby state has not been deployed in many mobile networks,

    while the configured inactivity timers for Dch and FAch are relatively long. this is why fast

    dormancy, which is referred to in the next section, has been considered by some device vendors.

    DCH / HSPA

    FACH

    URA / PCH

    STANDBY LOW HIGHIDLE

    IDLE CONNECTED

    Data Rate | Network Resources

    Power

    Figure 1A simplified radio state transition diagram for mobile (3g) devices

  • SOS: Signalling Overload due to Smart devices 7Anite 2011

    5 ALWAYS (?) ON

    the emergence of smart devices has monopolised the industry headlines, mainly with regard to

    user data throughput and network capacity demands. to a large extent, this was inevitable as

    mobile networks were not designed to support the currently experienced data tsunami. much

    emphasis has also been put on the always on mode of operation of smart devices. what is often

    not appreciated though is that these devices give the impression of being always on, whereas they

    repeatedly wake up to ping the network for updates and then go back to sleep.

    the use pattern for smart devices can be summarised as follows:

    Userstendtopickuptheirsmartdeviceforashortperiodandinahighlyunpredictable manner, to make use of an application that requires manual action (e.g. to browse the internet

    for the latest news or find the nearest restaurant to go for lunch)

    Mobileapplicationsrelyonupdatesvianetworkserverpolling,oftenatuser-specifiedinternals that can be as short as a minute, while push-enabling applications (including instant

    messenger) require a tcp connection and the use of heartbeat or keep-alive messages, as

    often as every 30-60 seconds.

    it is this constant signalling need that led some device vendors to consider fast dormancy before

    the Standby state was deployed. this device-proprietary feature overrode the long (battery-

    draining) inactivity timers, by going directly from high to idle quickly after data transmission

    ended. the idea behind fast dormancy is simple: the device sends a Signalling connection Release

    indication or ScRi to simulate a signalling connection failure, release the RRc connection and move

    to the idle state, where power consumption is low.

    however, this direct transitioning proved problematic, due to the non-standardised, device-

    dependent implementation of fast dormancy3 and the fact that the simulated signalling

    connection failures could not be distinguished from actual failures. Fast dormancy increased

    signalling by increasing the amount of idle-high state switching, which requires the setup of a

    packet connection. it also made it impossible for the device to stay in the preferred (low) state.

    3 more comments on Fast Dormancy as a 3gpp-standardised feature are made later in the document.

  • SOS: Signalling Overload due to Smart devices 8Anite 2011

    the constant updates that many popular applications (such as mobile email or social networking)

    require from the network are the reason why smart devices are often described as chatty. indeed,

    each such update can generate as many as 30 signalling messages, equivalent to what a voice call

    would require. in these terms, it is easy to understand what kind of an impact a device that asks for

    updates every minute or so would have on the mobile network. more importantly for operators,

    such updates cost in terms of signalling currency, but do not bring in any extra revenue (at least,

    for the time being).

    According to mobile network operators figures, a smartphone generates more signalling messages

    per megabyte (mB) than a pc/laptop dongle. the average smartphone user consumes from 10

    to 25 times less data than the average mobile broadband user (with the introduction of ltE, this

    figure will probably be adjusted by a factor of two to three. At the same time, mobile dongles only

    connect to the network three times as often as smart devices. in other words, a smart device may

    make eight times as many connection attempts per mB as a dongle, i.e. may be eight times less

    efficient than a dongle in terms of signalling.

    Figure 2 below illustrates this in a simplified normalised fashion. in this figure, the data (in mB),

    number of connection attempts and connection attempts /data (mB) for smartphones and dongles

    are presented versus the respective normalised maximum value (this value is not the same or of

    the same unit for each depicted graph).

    operators now see signalling traffic in their networks outgrow data traffic by 30%50%. And, as

    the number of chatty smart devices increases, so will the impact on network signalling.

    of course, the effect on different networks will vary, and there may be many mobile networks

    where Signalling overload due to Smart devices (SoS) has not been noticeable, yet.

    Figure 2A simplified normalised illustration of how smartphones and dongles rate in real-life networks with regard to: data (mB) consumption; number of connection attempts; number of connection attempts per data (mB)

    DATA

    SMARTPHONE DONGLE

    CONNECTION ATTEMPTS

    SMARTPHONE DONGLE

    CONNECTION ATTEMPTS/DATA

    SMARTPHONE DONGLE

    Normalised Max Normalised Max Normalised Max

  • SOS: Signalling Overload due to Smart devices 9Anite 2011

    6 NETWORK DISTRESS SIGNALLING

    mobile network operators are concerned about the impact of chatty devices, even though their

    bandwidth requirements are modest compared with heavy data users. this impact cannot be

    concealed: mobile network/device issues have been widely publicised, especially with popular

    smart devices such as the iphone.

    Some of the publicised issues have to do with the described constant signalling between smart

    devices and the network, which places a significant burden on the network resources and can lead

    to sudden battery draining or applications working slowly on the device. the signalling burden

    may not be seen today in many networks, but as the number of smart devices increases so will the

    likelihood of network meltdown.

    operators are aware of the danger. Smart device traffic is predicted to increase by 10,000%

    in the next five years. the impact of smart devices is expected to be an even bigger headache

    as devices get cheaper, become more user-friendly, and provide access to more/better content

    (apps). Smartphone sales were expected to exceed 250 million in 2010, after 170 million were

    sold in 2009. According to analysts, smartphones will outsell pcs by 2012 and there will be

    more smartphones than pcs by 2013. And the emergence of machine-to-machine (m2m)

    communications will also exacerbate the signalling challenges.

    there are some more worrying trends for operators:

    WiththeEuropeanUnionreadytoimposeacaponroamingfees,aleadingmobileoperator recently announced a flat-rate data package for smartphone customer roaming in Europe. As

    more and more operators are likely to follow a similar strategy, the issue of signalling

    overload may thus be exported to countries where mobile networks are able to

    cope with local demand but not with additional smart devices. And this could well lead to

    many unhappy mobile users (even though the reason will not be roaming data fees).

    Thenumberofapplicationsforusewithsmartdeviceshasincreasedrapidlyinjustafewyears, and is set to increase further. Apple is now claiming 300,000 mobile apps for the iphone, while

    competitor platforms/devices are doing their best to catch up. with more applications trying

    to connect to the mobile network, more signalling issues are likely to occur.

  • SOS: Signalling Overload due to Smart devices 10Anite 2011

    Theuseofsocialnetworkingapplicationsisrising.Therearenow200millionmobileFacebook users, who are typically twice as active as fixed-line Facebook users. According to gSmA, 50%

    of the UK mobile data traffic is social networking related. more importantly, many applications

    may involve more than one person, especially as users start using their smart device in the

    same way they would use their pc/laptop.

    Theconsiderationofsmartdevicesinfinancialtransactionsorhealthschemes(patient monitoring), as part of an all-encompassing mobile life or m-life world vision, could lead to

    additional signalling concerns too. this also applies to many other areas of great interest

    for mobile network operators, such as location-based services, which are expected

    to expand further in the future.

    Asbroadbandistobecomeahumanright,supportformobilebroadbandmayneedtobe extended in many countries. Although not limited to smart devices, such a development could

    be a challenge for mobile networks that have not faced problems up to now.

    it is also important to note the commercial impact of signalling overload. According to leading

    network infrastructure vendors, as much as 60% of the network resources may be dedicated

    to supporting connection attempts and only 40% to data throughput. in economic terms, the

    signalling related expense may thus account for 60% of an operators network cost. So, while the

    amount of data that a mobile user consumes is driving the operator revenues, it is the number and

    length of times that the users device gets connected to the network that actually cost more.

    the impact of smart device signalling is not restricted to network operation and efficiency. User

    experience is also of great significance, as signalling can directly/indirectly affect the mobile

    subscriber, from the ability to connect to the network to how long the device battery lasts for.

    Subscribers expect a lot from their smart devices, and are likely to be disappointed and use

    them less or even churn if these do not live up to expectations. Ultimately, the bottom line for

    operators is inevitably related to signalling overload.

    Signalling overload due to Smart devices is a significant issue for mobile network operators. of

    course, the SoS urgency will differ from operator to operator and from device (or application) to

    device (or application). operators are now interested in methodologies and tools that will help

    them quantify the issue for different devices/applications in their network.

  • SOS: Signalling Overload due to Smart devices 11Anite 2011

    7 SOS EVALUATION

    Reactive or proactive methodologies can be used to understand the impact of smart devices

    on the signalling health of the mobile network. the most representative ways to measure the

    signalling temperature of the network or run a signalling check-up are briefly described below.

    Real-time monitoring

    mobile network operators have been interested in real-time or near-real-time monitoring systems

    for a while. From cell focused network performance management (based on post-processing

    cell measurements), to call/user specific evaluation tools (based on detailed data from network

    traces and/or gpS), such systems have been deployed worldwide with considerable success.

    these monitoring schemes are also related with the elaborate network optimisation (and self-

    optimisation) mechanisms that operators are now looking into, as part of next-generation systems.

    Real-time monitoring systems are useful in identifying various network issues, including signalling

    overload due to smart devices. however, such systems are generally costly and complex, due to

    the large amount of considered data and the processing speed they may need to provide. more

    importantly, their use for SoS prevention is limited, as they rely on a posteriori analysis. in other

    words, real-time monitoring systems cannot prevent the launch of devices/applications that may

    wreak network havoc. Even if test devices are considered for this purpose, these could have a

    negative impact on the live mobile network and on its users.

    Field testing

    Field testing (also known as drive testing, if performed outdoors) has been a popular way for mobile

    network operators to understand how their network is performing. Field testing is a useful tool

    especially when a new and not so well tested or mature technology is considered, such as ltE.

    Field testing can be used by operators to check the signalling performance of smart devices too.

    indeed, the information that is recorded in a field trial can help operators understand exactly how

    a device/application is behaving in their network. however, field testing is subject to the dynamic

    network conditions and is not statistically bullet-proof. more importantly, similar to real-time

    monitoring systems, field tests can be costly, have limited preventative use and may also affect the

    performance of the live network.

  • SOS: Signalling Overload due to Smart devices 12Anite 2011

    Lab testing

    lab (laboratory) testing has been the proactive approach to testing mobile devices/applications

    for a number of years. lab testing has enabled operators and device manufacturers to test devices

    in a controlled and repeatable environment, which is immune to statistical uncertainty. Based on

    systems that simulate a cell or a number of cells, lab testing has helped identify device issues early

    and accelerate their time-to-market in a cost-effective fashion.

    Figure 3 below depicts in a simplified manner the setup of the leading network simulator solution

    for device interoperability testing. the simulated network system shown at the top can be driven

    locally or remotely via a pc/laptop and is connected to the mobile device under test via an RF

    cable. As shown in Figure 3, the device interoperability tests can also be run in an automated mode

    via remote control and without manual intervention.

    this setup can be extended to consider RF fading, and hence simulate the dynamic mobile network

    environment in an even more realistic fashion. in addition, mobile applications can be tested by

    connecting the system to internal or external data servers. in these terms, it is possible to quantify

    the impact of chatty smart devices on network signalling, and test devices/applications thoroughly

    with regard to SoS, before these are launched.

    Remote C

    ontrol

    Device Control

    RF C

    onnection

    Device under test

    Automation PC

    ANITE SAS

    Figure 3A simplified (Anite SAS) system diagram for smart device interoperability testing in the lab

  • SOS: Signalling Overload due to Smart devices 13Anite 2011

    Using a network simulator, different smart devices can be evaluated and their behaviour in terms

    of signalling measured as part of comprehensive device performance/comparison tests. network

    simulation can reveal how long a smart device stays in a particular state, how many transitions

    occur in representative test scenarios for commonly used mobile apps, and ultimately the potential

    signalling impact of the device and its applications on the real-life mobile network.

    Such signalling tests can be considered together with battery, acoustic quality, latency, data

    throughput or other tests that have been run in the lab for a while to make the assessment of

    smart devices more representative. this kind of testing is also expected to become part of the

    device acceptance schemes that many tier-1 operators have introduced to enhance the quality of

    smart devices launched on their network and gain the advantage over their competitors.

    in brief, lab testing can help operators assess the signalling impact of smart devices before they

    are deployed and with no/minimal need to test them on the live network. in terms of cost versus

    benefit, lab testing appears as the most attractive means to understand if the introduction of

    a new device/application will have an adverse effect on the mobile network and to decide on

    whether action should be taken at an early stage.

    the typical actions that a mobile network operator may take to ensure that the smart device

    boom will not lead to the network going bust are described in the next section.

    We want to test smart devices with popular applications,including mobile email. Lab testing can help us evaluatethe mobile user experience before we launch any device.Manager, Device Acceptance, Tier-1 Mobile Network Operator

  • SOS: Signalling Overload due to Smart devices 14Anite 2011

    8 SMART DEVICES, SMARTER INTEROPERBILITY

    As the issue of signalling overload due to smart devices is being acknowledged across the industry,

    mobile network operators are looking into ways not only to understand what the impact is, but

    also to mitigate/address this impact. in effect, operators are trying to find solutions to make the

    interoperability of smart devices with the mobile network smarter.

    More network resources

    Adding network resources appears to be the simplest way to counter the issue of signalling

    overload. At the same time, it is one of the least favoured solutions by mobile network operators,

    for obvious cost reasons. what may be more appealing to operators is to consider additional

    resources indirectly, by enhancing their network architecture. And this is where femtocells, the

    low-power wireless access points that connect devices to the mobile network by using residential

    DSl or cable, come to the fore.

    if the issue of signalling overload is seen from a user profile/location viewpoint, femtocells would

    be able to reduce the signalling load for mobile subscribers who are stationary, for example in an

    office or home environment. in fact, 80% of mobile traffic is located indoors. As a consequence,

    the impact of smart devices for professionals and subscribers that like to use a large number of

    always on applications could be significantly reduced.

    New technology features

    one of the most recently talked-about hSpA+ features is Enhanced cell FAch (a 3gpp Release 7

    Dl feature and Release 8 Ul feature). with Enhanced cell FAch implemented, smart devices will

    be able to receive and send high-speed packet data that it has not been possible to receive/send

    before. Furthermore, the device transition time from idle will be greatly reduced. in other words,

    with Enhanced cell FAch, smart devices will not require a dedicated channel for receiving/sending

    small amounts of data, including emails. this will also have a positive effect on the device battery

    performance, and hence the overall mobile user experience.

    Fast Dormancy, effectively the standardised version of the feature discussed earlier in this paper, is

    a related 3gpp Release 8 feature. with the new standardised feature implemented, smart device

    switching will now be under the control of the mobile network, and take into account both the need

    to save battery life as well as the signalling impact of state transition. it is far from surprising that,

    according to device manufacturers, Fast Dormancy is one of the few features requested by all mobile

    network operators.4

    4 in accordance with 3gpp, Fast Dormancy can be supported by devices that are not Release 8 compatible, as it involves limited changes

    to the relevant radio protocols. it is also important to point out that there are more 3gpp Release 7 and Release 8 features of interest in

    terms of signalling (including cell pch) or battery life efficiency that have been or will be implemented in mobile networks,

    and which are not commented herein.

  • SOS: Signalling Overload due to Smart devices 15Anite 2011

    More network intelligence

    mobile network operators have been looking into intelligent solutions for many years. the

    consideration of self-organisation and self-optimisation in 4g network discussions/standards is a

    tangible sign of what operators would like to see in the near future.

    As part of such intelligent network monitoring solutions, the ability to have an accurate real-time

    or near-real-time picture of the network and take action where needed is of great interest. in such

    a way, operators would be able to address situations where additional resources are required due to

    signalling overload. Furthermore, operators could take unilateral action with regard to devices and/

    or applications that have an unexpectedly negative impact on the network performance.

    More emphasis on the ecosystem

    the benefits of establishing an ecosystem to address specific issues have been experienced by many

    mobile network operators. A representative example is the introduction of operator-driven device

    acceptance programmes, which has encompassed tier-1 operators and mobile device manufacturers

    in an ecosystem that has substantially reduced the time to market new devices.

    Similarly, the issue of signalling overload due to smart devices is an opportunity for operators,

    manufacturers and application developers to work together, as partners. Device manufacturers

    would think twice before implementing any feature that may be saving battery life but could have

    a negative impact on the network performance. likewise, Apps stores would enhance their mobile

    application approval procedures by incorporating real-life network related criteria, which the current

    acceptance guidelines only consider to a limited degree.

    Such a modus operandi would be preferable to the alternative option of unilateral action from

    network operators. indeed, an operator has the power to shut down services that degrade the mobile

    network or to charge more for specific services or maybe to deliver email messages only on a periodic

    basis. Ultimately though, these decisions should be the last resort, and only for cases where the

    ecosystem fails to deliver on its promise.

    the solutions to the issue of signalling overload described here are far from an exhaustive list. other

    solutions that have been discussed include the consideration of common network access points (so as

    to reduce the number of packet data connections) or the setting of more appropriate network timers

    (so that devices stay in a particular state as much as necessary, neither too short nor too long).

    however, these solutions are generally regarded as service specific or difficult to implement without

    having an adverse effect on the user experience.

    in general, mobile networks are expected to consider features that will improve latency, data rates

    and power efficiency in different RRc states as well as the general state transition behaviour of

    smart devices. Achieving the optimal balance between staying in or moving from/to a radio state, in

    terms of the associated network signalling resources and device battery life, will be one of the most

    important challenges to address for smart devices. mobile network operators simply cannot afford to

    ignore this SoS.

  • SOS: Signalling Overload due to Smart devices 16Anite 2011

    APPENDICES

    About Anite

    Anite provides a comprehensive range of critical it solutions to the wireless and travel sectors

    across the globe. listed on the london Stock Exchange, Anite develops and implements software

    as well as provides consultancy, systems integration and managed services to ensure that our

    customers operate effectively and securely. By using the latest technologies to deliver quality and

    cost-effective solutions, Anite meets customers specific requirements and realises tangible results

    for its clients.

    Anite telecoms, a subdivision of Anite plc, is a global market leader with over 18 years of

    experience in providing cutting-edge technology within the handset testing industry to device

    manufacturers, operators and test laboratories. As an established leader, Anite was the first

    company to verify ltE conformance test cases in 2009. with highly flexible and reliable software

    solutions, Anite is known as an innovative, agile and responsive partner to the top players in

    the telecoms industry. with a diverse team focused on making a difference and exceeding

    expectations, Anite draws upon worldwide expertise and is enthusiastic about the future.

    headquartered in the UK, Anite employs around 500 staff in 13 countries across Europe, America,

    Asia and the middle East. For more information, please visit www.anite.com

    ABBREVIATIONS

    2G 2nd-generation3G 3rd-generation3GPP 3rd-generation partnership projectDCH Dedicated channelDL DownlinkFACH Forward Access channelGPS global positioning SystemHSPA high-Speed packet AccessLTE long term EvolutionM2M machine-to-machineMB megaBytePC personal computerPCH paging channelPCI peripheral component interconnectRRC Radio Resource control SAS Anites network simulator solution (originally introduced as Stand-Alone Simulator)SCRI Signalling connection Release indicationSOS Signalling overload due to Smart devicesTCP transmission control protocolUL UplinkURA UtRAn Registration AreaUTRAN UmtS terrestrial Radio Access network

  • SOS: Signalling Overload due to Smart devices 17Anite 2011

    APPENDICES

    FIGURES

    Figure 1 : page 6

    A simplified radio state transition diagram for mobile (3g) devices.

    Figure 2 : page 8

    A simplified normalised illustration of how smartphones and dongles rate in real-life networks

    with regard to: data (mB) consumption; number of connection attempts; number of connection

    attempts per data (mB.)

    Figure 3 : page 12

    A simplified (Anite SAS) system diagram for smart device interoperability testing in the lab.

    REFERENCES

    wcDmA for UmtS hSpA Evolution and ltE, h. holma and A. toskala, 5th Edition, 2010, wiley

    www.anite.com/wireless

    SOS: Signalling overload due to Smart Devices, represents the view of Anite as at the date of publication. the whitepaper is provided

    as is and for the purpose of information only. Anite does not make any warranty of any kind, expressed or implied, as to the information

    presented within the document, and does not undertake to notify recipients of this whitepaper of any subsequent changes to the facts

    and opinions included.