latency matters

7/29/2019 Latency Matters

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www.o3bnetworks.com 1

Why Latency Matters toMobile Backhaul

by O3b Networks and Sofrecom

This paper is presented by O3b Networks to provide anunderstanding of the impact of latency on mobile backhaulservices. Several common voice and data applications areanalyzed to assess the impact of latency on the quality ofthe end user’s experience. The paper compares the Quality

of Experience (QoE) based on latency differences betweenGeosynchronous satellites and Medium Earth Orbit satellites.

Contents

About O3b Networks Ltd. 2

About Sofrecom 2

Proprietary Statements 2

Mobile Industry Landscape 3

Latency for satellite backhaul and impact of Latency on

Quality of Experience 6

Conclusion 14

Annexes 15




Why Latency Matters to Mobile Backhaul

About O3b Networks Ltd.

O3b Networks is a global satellite service provider building a new fiber-quality, global Internet backbone for telecommunications operators,internet service providers, enterprise and Government customers in

emerging markets. The O3b Networks system will combine the global reachof satellite with the speed of a fiber-optic network providing billions ofconsumers and businesses across 177 countries with low-cost, high-speed,low latency internet and mobile connectivity. With investments andoperational support from SES, Google Inc. Liberty Global, Inc. HSBC PrincipalInvestments, Northbridge Venture Partners and Allen & Company, the O3bsystem will provide telcos and ISPs with a low-cost, high-speed alternativeto connect their 3G, WiMAX and fixed-line networks to the rest of theworld. O3b Networks is headquartered inSt. John, Jersey, Channel Islands.

About Sofrecom

Sofrecom, a France Telecom – Orange Group Company, is a world leader intelecommunications consulting and engineering.

With more than 45 years international experience, Sofrecom has acquired aunique know-how of successfully managing change in thetelecommunications industry. Sofrecom has led major transformationprograms and has participated in the green field launch of multipleoperators, including all Orange mobile operators over the past 5 years.

This rich international experience provides Sofrecom with an unparalleledexpertise in all areas of telecommunications and makes it the naturalstrategic partner for operators, governments, investors and international

financial organizations.

Proprietary Statements

O3b provides this information in good faith, and has taken all reasonablesteps to ensure its accuracy and completeness as of the date hereof.However, O3b expressly disclaims any and all liability which may be basedon the use of such information, errors therein, changes and omissionsthereto. O3b shall not be liable for damages of any kind, including special,incidental or consequential damages or damages for loss of goodwill or lossof prospective profits, on account of omissions or errors contained herein.

O3b® and O3b Networks® are registered trademarks of O3b NetworksLimited. Other product names, company names, brand names, and tradenames mentioned within the corporate information center may be thetrademarks of their respective holders. All rights in the service marks,company names, trade names, and logos used for the products or servicesof O3b or of third parties belong exclusively to O3b or their respectiveowners, and are protected from reproduction, imitation, dilution, orconfusing or misleading uses under national and international trademarkand copyright laws.





Mobile Industry Landscape

The Mobile industry is changing rapidly, as it evolves from 2G to 3G and onto 4G networks. This evolution is driven by the need to provide betterperformance in three main areas:

− Provide subscribers with higher data rates− Support a wider variety of end user applications− Reduce the latency of the mobile network

Increasing sales of 3G smartphones, USB modems, tablets and PCs withbuilt in wireless radios is pushing data traffic on mobile networks to recordlevels. While email, social networks and Internet browsing are very popularamong nomadic users, the deployment of mobile broadband services hasthe biggest impact on network traffic. In rural areas, mobile networks areoften the only way to support applications historically delivered overcopper based networks. Video streaming is a major contributor to the boostin traffic, with the success of Internet services such as YouTube and

DailyMotion. The latest Cisco Visual Networking Index forecastsunprecedented global mobility demand.

Figure 1 – Mobile Data Growth





Data services are projected to grow by a staggering 78% annually over justthe next four years. It is also clear that the mix of applications is changing,particularly with the shift towards mobile video.

While the increasing data rates and the changing application mix are easilyunderstood, the impact of latency on performance requires a closer look.How does latency affect application quality and the end user experience?We will explain the significant difference lower latency can make in thedelivery of voice, video and data services. We will strive to answer thequestion: Why does latency matter to mobile backhaul?

QoE is the new challenge

Fierce market competition is driving network operators to identify truedifferentiators capable of separating them from the rest. The innovators, inturn, are intensifying efforts to boost the Quality of Experience for theirsubscribers. As a result, QoE is now one of the latest buzzwords in the

mobile industry.

The QoE experienced by a mobile subscriber for a voice call is influenced bya number of factors, including mouth-to-ear delay, voice call set-up delayand audio quality/noise. The QoE for data services is influenced by webpage response time and download speeds.

Network segment QoS indicators

For mobile network elements, such as components of the access, backhauland core networks, several indicators are used to define and monitor thetarget performance.

− Latency - Latency is the duration of time for information to transit fromone point to another point of the network. Depending on the type ofservice, it can be measured either in one direction (Ear-to-mouth orOne-way latency) or as a round trip time (RTT or Two-way latency).

− Jitter - Jitter is the variation of the measured latency. It is generated bythe variation of the load on the network due to usage levels.

− Packet loss - Packet loss is the ratio of packets being lost during transitfrom one point to another point of the network. It is generally causedby transmission errors, congestion of links, faults or the routing process.

In modern IP based networks jitter is easily compensated for byimplementing buffers in the endpoints. Likewise packet loss is very low on

today’s networks, which employ high performance error correction codessuch as LDPC which is used in DVB-S2. Latency, however, is more difficult toavoid. The root cause is linked to long distances and the speed of light.Once present in a system, latency cannot be removed. This is exactly whythe mobile industry has consistently engineered each new technologygeneration with lower latency, as seen in Figure 2.





Figure 2 – Latency in Mobile Technology Evolution

Every new mobile technology generation has reduced network latency. Theright side of the chart shows the latency of satellite backhaul for traditionalGEO satellite and O3b’s MEO constellation. It is easy to see that for latergeneration mobile networks satellite backhaul is the dominant contributorto end-to-end latency and the resulting subscriber QoE.





Latency for satellite backhaul and impact of Latency onQuality of Experience

End-to End latency Model

Each network component contributes to latency. The chart below, extractedfrom a study by Nokia Siemens Networks (NSN), shows the latencydistribution for a mobile network (exclusive of backhaul or internationalnetwork latency).

Figure 3 – Latency Distribution for Mobile Network (NSN1)

(1) Extracted from “The impact of latency on application performance, Nokia Siemens Networks”

With each release there has been a tremendous engineering effort tooptimize each network element and terrestrial link to provide the lowestpossible latency. Individual components have been optimized, framelengths reduced, protocols streamlined, and in the case of LTE, an entirenetwork layer has been eliminated.

The satellite backhaul element is much more difficult to optimize.Technologies, such as ComtechEFData’s VersaFEC, have improved themodem processing delay, but the fundamental distance of the path lengthto the satellite is what drives the delay.





Mobile Service Classification

From a mobile network perspective, the ITU and the 3GPP have groupedthe end-user services into four classes based on their sensitivity to latency.

Figure 4 – User services classification

This paper focuses on the three major service classes for mobile operatorsand the practical impact of latency on:

− Conversational Voice− Interactive Applications, such as cloud-based applications, online

shopping, instant messenger and online search.− Non real-time data, such as web browsing, email SMS/Text messaging,

file sharing, and video streaming.

Conversational Voice Services

Voice quality is measured in the ITU model by the R factor, which can alsobe translated into a Mean Opinion Score (MOS) score, a scale widely usedto evaluate the quality of a voice call. The MOS score and voice call qualitydegrades rapidly when the ear-to-mouth latency increases beyond 200ms.

Annex 1 provides a detailed explanation of the ITU model.

A latency comparison for a UMTS Release 99 voice call for two cases usingMEO and GEO satellites is shown below.

Figure 5 – End to end latency distribution for a voice call with O3b satellite backhaul





Figure 6 – End to end latency distribution for a voice call with GEO satellite backhaul.

For O3b’s MEO constellation, the fiber return path adds 30ms of latency,representing the case of more than 5000km of optical fiber.

The following diagram shows the resulting MOS scores for these two cases.

Figure 7 – Voice Quality / MOS score degradation as a function of latency

A side-by-side comparison of end-to-end latency values results in an MOSscore of 4.4 for O3b’s MEO constellation and a MOS score of 3.8 fortraditional GEO satellite.





Interactive user services

The impact of latency on interactive services is more subjective. As thedelay increases, the applications continue to function. However, the senseof immediacy and the usability degrades. At some point, the user becomesless tolerant of waiting for the response, eventually giving up and movingon to something more satisfying. A great deal of research has been doneby companies whose revenues are impacted when users abandon theirtransactions.

The importance of latency on web commerce was first showcased by ZonaResearch in 1999 with the popular “8-second rule”. Zona found that morethan $4 billion e-commerce sales were lost due to poor site performance,which ultimately led to transaction abandonment. In a follow up study in2006, Jupiter Research concluded that the threshold had been reduced to 4seconds, as more users experience the performance of high-speedbroadband.

Google discovered that the number of web searches and ad revenuedeclined as they increased the number of user search results from 10 to 30.Further research found the result was due to the additional time required tocompute and present more results to the user. Increasing the results from10 to 30 required an additional 500ms to compute and resulted in a 25%drop in the number of searches done by users. Following this initial study,Google performed additional tests focused exclusively on the latency. Theyinjected artificial delay into the display of the search results. An increase indisplay time of 400ms actually decreased the number of searches per usersby 0.44% to 0.76%. While these drops in usage appear small, they had adirect and meaningful impact on ad revenue.

Similarly with Amazon: “We tried delaying the page in increments of100 milliseconds and found that even very small delays would result insubstantial and costly drops in revenue,” said researcher Greg Linden.Linden provides a precise figure: -1% sales for 100ms or more latency.(Greg Linden in “Make Data Useful”, Data Mining course Stanford in 2006).

Steve Souders from O’Reilly adds more examples in a blog postinghttp://radar.oreilly.com/2009/07/velocity-making-your-site-fast.html.

In “Performance Related Changes and their User Impact,” Eric Schurman(Bing) explains that Bing researchers have conducted tests adding a staticdelay of 50 ms to 2 seconds to their servers. A negative impact on the Bingperformance indicators resulted as soon as the delay increased by more

than 50ms. The degradation noticed was linear.





DistinctQueries/User

QueryRefinement Revenue/User Any Cl icks Satisfact ion

Time to Click(increase

in ms)

50ms – – – – – –

200ms – – – -0.3% -0.4% 500

500ms – -0.6% -1.2% -1.0% -0.9% 1200

1000ms -0.7% -0.9% -2.8% -1.9% -1.6% 1900

2000ms -1.8% -2.1% -4.3% -4.4% -3.8% 3100

Figure 8 – Bing table of latency impact for user search service

Phil Dixon (Shopzilla.com) presented results from the Shopzilla siteredesign at the Velocity 2009 Conference. He illustrated that a reduction inpage load time from 7 to 2 seconds resulted in a 25% increase in pageviews and a 7-12% increase in revenue.

Below, a mobile subscriber is using a HSPA session over a satellite backhaulto access Internet data services.

Figure 9 - End to end latency for data services using O3b backhaul

Figure 10 - End to end latency data services using GEO satellite backhaul





The increase in latency of 420ms between O3b’s MEO solution and a GEOsatellite has a significant impact on interactive services.

As demonstrated, revenue loss is a significant consequence of the qualitydegradation of a users’ experience caused by download delays. End usersperceive latency increases of a few hundred milliseconds in a negativeway, which translates into a loss of business for providers and advertisers.

Users are unaware whether the delay in response time is due to a slowserver or a satellite link. The end result in both cases is the same: a pooruser Quality of Experience.

TCP in a nutshell

The Internet uses the Transmission Control Protocol (TCP) to provide end-to-end services. In particular, TCP ensures the error free sequenced delivery ofdata transmitted from a source to a destination.

Data is sent by the transmitter to the receiver in fragments called TCPsegments. A maximum size is defined for the segments. The receiver willconfirm the correct reception of sent TCP segments by acknowledging them(sending the transmitter a response “ACK message” with a correctsequence number). If an ACK message is not received or if it is not correct,the transmitter will return the message ensuring a reliable transfer. At theend of the session, it is correctly closed by exchange of FIN messages.

The key factor in this context is that TCP will only send a limited amount ofdata before it needs an acknowledgement. The amount of data is governedby the TCP buffer size, which in Windows 7 is 64 kbytes. If 64 kbytes ofdata has been sent but the acknowledgements have not yet been received,TCP will wait for an acknowledgement before it sends another packet. Thisacknowledgement mechanism is what limits the transmission rate overhigh latency links.

Non interactive data services

The major complexity of TCP comes from its flow and congestion control

mechanisms. The TCP flow control mechanism adjusts the TCP window size(the number of segments that can be sent and not yet be acknowledged)depending on the status of the end devices and congestion/latency on thelink during the transfer.





Figure 11 – Messages exchanged for TCP connections.

Each message is subject to transmission delay. For complex transmissions,such as web pages with multiple images and tables, the delay is

cumulative. If a page has ten elements, a 500ms increase in latency willproduce a 5 second increase in the page load time.

TCP throughput and transfer time

TCP throughput, and consequently file transfer duration, is a function ofend-to-end latency, packet loss rate and maximum segment size (moredetails are available in Annex 2).

− Throughput is increased by a maximum segment size increase.− Throughput is decreased by packet loss and/or latency increase.

Figure 12 – Maximum TCP throughput decrease due to latency





Figure 12 shows that the maximum TCP throughput degrades rapidly aslatency increases.

The same illustration for an interactive service is considered: an HSPAaccess over satellite to Internet service (c.f. Figure 9 and Figure 10 for detailon each case).

The maximum throughput for TCP Reno will be 2.1 Mbps for O3b and775 kbps for GEO satellite. This will be the maximum achievable rate for aTCP connection, such as a single user communicating with a server. Table 5estimates the transfer time for various media for both backhaul links for asingle TCP stream.

O3b GEO

2 MB Song 10 seconds 28 seconds

1.5GB Movie 1.66 Hours 4.5 Hours

3.8GB HD Movie 4.25 Hours 11.4 HoursTable 1: Estimated transfer time comparison between O3b and GEO backhaul

The subscriber QoE for these types of services is directly related to thedownload time. The lower latency of the MEO case results in a hugeimprovement in download times and subscriber QoE.

Non real time video streaming

Video streaming was traditionally transported over UDP, but major websites such as YouTube and DailyMotion now use either Adobe Flash Video or

HTML5:− HTML5 is delivered using HTTP over TCP.− Adobe Flash Video can be delivered using:− FLW or SWF Files downloaded using a browser with HTTP over TCP− Progressive download over HTTP over TCP− Real Time Messaging Protocol over TCP directly or through HTTP tunnel

over TCP− HTTP Live Streaming format over TCP.

With all the major providers of web video streaming now using TCPtransport for video streaming, the latency impact on the degraded userexperience will be exactly the same for Internet video streaming as it is for

data file transfer.





Conclusion

In the past, a boost in the subscriber data rate was all that was needed,and operators could simply focus on increasing voice minutes and datavolume. But as consumers become more sophisticated and networks

become more complex with the introduction of mobile broadband, Qualityof Experience has become an important indicator of network performance.

Latency is the critical factor in improving QoE across all services, includingtraditional voice services and the latest data services (i.e. interactive cloud-based applications and movie downloads).

− Voice quality is measurably improved using the ITU model− The response of interactive applications is dramatically improved− File download times are reduced by over 60%

The latency of O3b’s MEO constellation is substantially better thantraditional GEO satellites. This has a direct improvement on QoE and

provides a competitive advantage for operators who are deploying modernmobile networks in rural areas.





Annexes

Annex 1 Voice Codec, E-Model and MOS score

The quality of voice services has been defined in several ITU standards,

namely G.107, G.108 and G.109. Quality of the voice services is evaluatedusing a quality factor “R” ranging from 0 to 100.

The R factor can be directly translated to a MOS score, as defined in the ITUG.107 recommendation. The mapping formula can be represented by thefollowing curve.

Figure 13: MOS Score and R Rating mapping (ITU G. 107 / P. 800)





End to end latency, or so called “mouth to ear” has a strong impact on thevoice quality, as illustrated by the following figure extracted from the G.114recommendation.

Figure 14: End-to-end latency effect on R factor (ITU G.114)

The higher the latency, the lower the voice quality. And as shown in theright side of the graph, voice quality is directly related to user’s QoE andoverall satisfaction.





Finally, the absolute quality of the voice and latency impact is related tothe codec selected. Although in any case, higher latency means a decreasein quality. For Mobile backhaul, AMR-12.2 is widely used and correspondsto GSM-EFR codec.

Ie= 0 5 7 10 15 19 19 20 26

G.711 GSM-EFR

G.726

@32 G.729

G.723.1

@6.3

G.729A

+VAD

w/2% loss

G.723.1

@5.3 GSM-FR

G.729A

+VAD

w/4% loss

ms

G.728

@16

G.723.1

@

6.3+VAD

w/1% loss IS-54

~0 94 87

50 93 86 83 74 67

100 92 87 85 82 77 73 73 72 66

150 90 85 83 80 75 71 71 70 64

200 87 82 80 77 72 68 68 67 61

250 80 75 73 70 65 61 61 60 54

300 74 69 67 64 59 55 55 54 48

350 68 63 61 58 53 49 49 48 42

400 63 58 56 53 48 44 44 43 37

450 59 54 52 49 44 40 40 39 33

Note 1 – R-values in this table have been calculated using the indicated values for Ie and T (T=Ta=Tr/2) alongwith the default values from Table 6 for all other parameters.Note 2 – Unless indicated otherwise, examples do not include packet loss or Voice Activity Detection (VAD).Note 3 – Blackened cells indicate combinations of delay and codec that are impossible to realize.

Figure 15: R rating values for various voice codecs depending on End to end delay (ITU G. 108Annex B)

Annex 2 TCP details and throughput calculation

This annex gives more details on TCP Flow Control and TCP Congestion andMaximum TCP throughput and TCP transfer duration.

Flow control

Flow control is achieved using a feature called “sliding windows”.The receiver advertises the amount of data it can accept through time

(generally related to buffering capacity). The transmitter is allowedto transmit data up to this advertised value until it receives an ACKmessage.





For instance, the receiver advertised a maximum window size of 10segments. The transmitter will send the 10 segments (at a variable ratedescribed in the congestion avoidance) and will then stop until ACK isreceived. For each ACK (if window size stays constant) received, the

transmitter may send another segment. The algorithm may advertisea variable window size depending on the actual state of the receiver(i.e. buffers filling or emptying), allowing it to transmit more or fewersegments and vary the actual throughput.

Congestion Control

Flow control enables the two end devices to regulate the transmissionthroughput, but it does not take into account the status of the network linksbetween them. Congestion control mechanisms are required to regulatethe speed of the data transmission and the quality of the network link.

Using a slow start mechanism, the sender begins to transmit TCP segmentsat a low rate, gradually increasing the number of segments simultaneouslytransmitted until the full window size is reached or congestion is detected.In case of congestion, an avoidance mechanism will drastically decreasethe rate and initiate the step increase again, creating a saw-tooth effect.Various TCP flavors (Reno, Vegas, Cubic, Compound) have variations in thealgorithm used to define the increasing and decreasing rate, based on amaximum segment size and/or queuing delay.

Other optimizations include retransmission of selected segments and fastrecovery to increase the transmission rate more quickly.

TCP maximum throughput estimation

TCP maximum throughput can be estimated using a formula based on TCP

RENO (RFC2001) as described by Padhye et. al. in "Modeling TCPThroughput: a Simple Model and its Empirical Validation"

The model used is the following one:

( ) ( )⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

++≈

2

8

303

2

max

3213,1min

1,min)(

p pT RTT RTT

W p B

bpbp




Where

B(p): approximate model of TCP throughput [packet/s]

Wmax: maximum window buffer size of receiver [packets]

RTT: Round Trip Time [sec]

b: number of packets that are acknowledged by a received ACK

p: probability that a packet is lost

T0: time-out for re-transmitting an unacknowledged (lost) packet [sec]

RTT should take into account the additional delay due to serial transmissionof the packet (especially for low rate interfaces) and various TCP receivewindow sizes depending on the Operating System of the end-device.

TCP transfer duration estimation

Overall duration of file transfer can be approximated using the formulagiven by N. Dukkipati et al in “An argument for Increasing TCP’s InitialCongestion Window”

S being the size of the fileC being the bottleneck link-rateRTT being the two-way end-to-end latency

being 1.5 if ACK are delayed of 2 else.Init_cwnd is the initial congestion windows, generally no more than three segments or about 4kB.

The transfer time calculated does not take into account packet loss(no packet loss) for simplicity. Packet loss further increases the duration oftransfer due to retransmission of error packets and congestion control

mechanisms.

latency matters

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