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White Paper

Making Sense of Bandwidth the NetSense Way

Network Congestion in Unmanaged Networks

Bandwidth Estimation and Adaptation Techniques

RADVISION’s NetSense Technology

RADVISION WHITE PAPER | 2

White Paper

The growing use of video-based applications over the Internet has made bandwidth estimation and adaptation technologies a critical requirement in any visual communications system.

RADVISION’s NetSense technology is designed to deliver standardized and optimized video calling over unmanaged networks, enabling a consistently high quality of experience.

Applicable to a wide range of end-point devices and a variety of network configurations, NetSense allows visual communications to be implemented across all enterprise and consumer arenas. RADVISION’s integrated approach enables service providers, enterprises, and system integrators to provide their clients with the best user experience possible.

ContentsAbstract ................................................................................................................................... 3

Challenges of Real-Time Video Calling Over the Internet .......................................................... 3

Techniques for Bandwidth Estimation and Adaptation ............................................................... 4

The NetSense Algorithm ........................................................................................................... 5

NetSense In Action ................................................................................................................... 6

NetSense in RADVISION’s End-to-End Solution......................................................................... 6

Conclusion ............................................................................................................................... 7

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AbstractVideo calling over the Internet is becoming more and more popular. The quality of video in such applications is a major contributor to the overall user experience.

Video quality depends heavily on bandwidth availability. If the network path used is either under or over-utilized, high quality cannot be achieved. An accurate method for estimating available bandwidth across a network path and for adapting the bit rate accordingly is therefore very desirable.

This white paper presents NetSense, a novel technique developed by RADVISION for dynamic bandwidth estimation and adaptation designed for real-time, interactive video calling.

By detecting delays in received video frames, NetSense estimates available network bandwidth and adapts the transmitted bitrate accordingly in order to avoid packet loss.

Since NetSense uses only standard protocols for delay detection and flow control, it can be easily and effectively used with traditional visual communications systems.

NetSense has been shown to efficiently estimate available bandwidth, outperforming competing tools in terms of both detection time and accuracy. By implementing NetSense in its video conferencing solutions, RADVISION ensures superior video calls over unmanaged networks, compared to other solutions available in the market today.

Challenges of Real-Time Video Calling Over the InternetVideo calling has become one of the Internet’s fastest growing phenomena. Millions have discovered that reaching out and seeing someone is the next best thing to being there. Implemented in many products and form factors, from videophones to instant messaging and from video conferencing endpoints to mobile handsets, it has become a major mode of communicating.

Since video communication involves the transfer of high bandwidth multimedia data in real-time, ensuring minimal delay is critical. As the data is sent over managed networks (such as leased lines) and unmanaged networks (such as the Internet), quality of service (QoS) is not always guaranteed.

Congestion in IP networks and packet corruption frequently occur, leading to delay, jitter and packet loss, which all degrade the user experience.

Packet loss can be caused by a number of factors such as: signal degradation over the network due to multi-path fading, packet drop because of congestion, corrupted packets rejected in transit, faulty network hardware or faulty routing.

Network Congestion Explained

While all of these impairments must be dealt with in order to assure high quality of experience over unmanaged networks, this paper will focus specifically on the problem of network congestion.

Network congestion arises at overloaded network paths where the bitrate being sent exceeds the path’s maximum available bandwidth. This results in blocks of data, or packets, accumulating at bottleneck routers along the path and eventually being dropped.

Packet loss caused by network congestion is usually perceived at the receiver side as severe video artifacts and hence can significantly affect the quality of experience.

Congestion control algorithms, found in most video calling products, deal with this problem by lowering the bitrates whenever packet loss is detected. However, the packets that are dropped before packet loss is detected and bitrate is reduced already introduce a dramatic drop in video quality.

Furthermore, packet loss is not always caused by congestion, as explained previously. Reducing the bitrate will therefore not solve the problem in all cases.

Another way of dealing with packet loss, found in streaming and other non-real-time video solutions, is retransmitting the missing packets. However, retransmission is not applicable for interactive real-time calls due to the latency introduced by sending feedback from receiver to transmitter and then waiting for the retransmitted packets to arrive.

In short, one of the main challenges in real-time, interactive video calling is adapting the bitrate to the path without introducing packet loss.

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Changes in Effective Bandwidth

Changes in effective bandwidth occur even if the line has a guaranteed bandwidth, and even with leased lines. This is because the various applications on different devices consume variable amounts of bandwidth.

Another scenario, as depicted in figure 2 above: You could be in your home office making a video call over a 2Mbps DSL line, when your e-mail client starts to synchronize with the server at headquarters. Again, bandwidth will be reduced until the e-mail client has done synchronizing and then will increase again.

The challenges for any bandwidth estimation and adaptation technique include dealing with such fluctuations in bandwidth, adapting quickly and efficiently to the effective bandwidth at any given time and preventing packet loss during these changes in bandwidth.

Techniques for Bandwidth Estimation and AdaptationThe subject of bandwidth estimation and adaptation for communications over unmanaged networks is not new. In fact there has been a lot of research and development in this field in recent years.

However, many of the algorithms found in non real-time applications cannot be used by video calling systems because they lack the characteristics discussed hereunder.

The Characteristics of Video Calling

Video streams are made up of video frames, each comprised of a set of packets that are transmitted to the network at approximately the same time. These packets have to be treated as such in any bandwidth estimation solution.

Video streams usually have a strongly obeyed structure (known as GOP or Group of Pictures), and different frames in the GOP have different significance. Any viable solution must take this into consideration.

There are also bitrate fluctuations in real-time video calling that have to be modeled and compensated for in a bandwidth estimation algorithm.

Finally, and most importantly, video calling is very standardized in nature. It relies completely on existing protocols that strictly define the communication between sender and receiver. For an algorithm to be both vendor and protocol agnostic, it has to comply with these standards.

Standard protocols, for instance, define the communication means between sender and receiver and determine how commands and feedback are sent in a video call. Flow control commands, designed to alert the sender to change the bandwidth, are sent by the receiver according to these standards. In most cases the sender does not have any other control mechanism for bandwidth management.

Fig. 2: DSL connection between home office and HQ.

For example, an MPLS line of 10Mbps in a small branch office, as depicted in figure 1 above, would easily support a single video call between this office and headquarters; however, more people from that office connecting at the same time would reduce the effective bandwidth, making video calling more difficult.

Fig. 1: MPLS connection between remote branch and HQ

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Existing Bandwidth Estimation Techniques

Existing bandwidth estimation techniques generally fall into three categories: algorithms that are designed for specific networks, usually with guaranteed QoS; algorithms that use “probing” packets to evaluate bandwidth at the beginning of the call; and algorithms targeting video streaming, where a client-server model is assumed.

Most video calling solutions rely on a packet loss-based algorithm, where a flow control command reduces the bandwidth being transmitted as soon as packet loss is perceived on the receiver side. There are several methods of reducing and then converging bandwidth, but most are “cautious” in nature; they do not attempt to reach the true effective bandwidth but rather settle for a rough, lower estimation.

The NetSense AlgorithmNetSense was developed with unmanaged networks in mind, specifically the public Internet. Furthermore, it is designed to deal with real-time video calling, and so complies with the challenges defined in the relevant section.

RADVISION’s algorithm converges to the available bandwidth in a given path during call setup, and dynamically adjusts to mid-call changes in available bandwidth. It therefore perfectly fits the needs of a video calling system on the public Internet.

NetSense’s logic and decisions are executed only at the receiver side. As its name suggests, it senses significant increase or decrease trends in the delay of incoming video frames, and reacts accordingly.

NetSense is delay based. It monitors the delay between sender and receiver, thereby detecting over utilization of the path before packet loss occurs.

Furthermore, NetSense converges quickly and as closely as possible to the effective bandwidth. This means you can make the most of the available bandwidth, without sacrificing quality of experience.

Delay Detection

A clear understanding of how bandwidth over-utilization is experienced at the receiver side is essential for designing a bandwidth estimation tool that delivers best possible quality of experience.

When available bandwidth is over-utilized, packets enter the path at a rate faster than the network can process them. In this

case, the packets are usually stored by network router(s) in a buffer until processing is complete. This introduces a delay in packet arrival at the receiver end, known as queuing delay. The queuing delay is proportional to the router’s buffer size.

Packet loss occurs when the buffer overflows, i.e., when the buffer has no room to store further arriving packets. In most routers, packet loss can occur even earlier, as these routers randomly drop packets to reduce bandwidth when queuing delay is accumulated.

Figure 3 shows the delay and packet loss patterns obtained with nearly 50% over-utilization of available bandwidth. In this case, a 2Mbps video is transmitted over an MPLS line with a 1.4Mpbs limit. The blue line represents the delay in frame arrival at the receiver side. The orange dots represent packet loss events, with every dot corresponding to loss of one or more consecutive packets. Note that the delay accumulates during 2/3 of a second (or 19 video frames) before the first packet is lost.

Fig. 3: Delay and packet losses as perceived at the receiver side during over-utilization of bandwidth.

Similar setups substantiated the expected results: The receiver perceives accumulated delay for a significant period of time before the first packet is lost. As packet loss tremendously reduces video quality, identifying bandwidth over-utilization at the delay accumulation stage before packets are lost and reducing the transmitted bitrate accordingly is highly desirable.

Note that NetSense models the one-way delay between the sender and the receiver in a way that is agnostic to clock drifts. This makes NetSense applicable to any type of device, from embedded infrastructure to desktop and mobile handsets.

Effect of Bandwidth Over-Utilization

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Algorithm Flow

The NetSense bandwidth estimation algorithm has two modes of operation: At call initiation it scans the range of possible bitrates, and quickly but effectively converges to the precise available bandwidth. During the call, it detects changes in the available bitrate, adapting the bandwidth accordingly.

The algorithm supports the common scenario of multiple calls running over the same line, sharing the bandwidth, and assists in assuring fairness in bandwidth consumption. Figure 4 depicts an example of such scenario:

NetSense In ActionDue to its unique features and compliance with communication standards, NetSense works optimally in various network conditions, over different network links (MPLS, ADSL, cable) and with different vendors.

In real-life scenarios consisting of RADVISION video conferencing equipment with NetSense inside, as well as when connecting to equipment from leading vendors such as LifeSize (now Logitech), Polycom and Tandberg (now Cisco), NetSense proved to be a vital component and to significantly enhance the quality of experience.

NetSense is superior to other solutions in regards to convergence time - both for call initiation and response to mid-call changes in the available bandwidth. It converges to 90-95% of the available bandwidth in up to 15 seconds with no packet loss at all and an average detection time of 9.65 frames. In other words, when the bandwidth is over-utilized, NetSense takes only 9.65 frames, or less than a 1/3 of a second, to detect it.

NetSense in RADVISION’s End-to-End SolutionNetSense technology will be implemented across RADVISION’s entire product range, starting with the release of SCOPIA v7.5 and the BEEHD client framework. This will include RADVISION’s software clients (SCOPIA Desktop and BeeHD for desktop), endpoints (VC240 and XT1000) and the Elite MCU.

With this new technology, RADVISION offers the highest quality of experience even over unmanaged networks, specifically in these use cases:

Point-to-point calling.• The solution ensures high quality of experience, even if network conditions and/or available bandwidths are limited.

Remote calling• , such as when tele-workers call into the company network. The RADVISION offering enables a high quality call, even if the home connection suffers from limited bandwidth or low quality network.

Virtual MCU deployments• , where MCUs are deployed in different geographic locations (branches) and are connected over dedicated lines or the public Internet. The solution enables a perfect connection between network elements, even if the paths are limited.

In addition to its infrastructure products powered by NetSense, RADVISION will soon introduce NetSense as part of the unique SDK it offers vendors who wish to deploy a ready-made video calling engine within their products.

Fig. 4: Convergence of 2 calls sharing the same line

The above setup of an MPLS line, with a bandwidth limit of 850Kbps and a significant roundtrip delay of 700-800 milliseconds, shows how the NetSense algorithm enables multiple video calls to share the same connection and stabilize the use of their shared bandwidth in an as close to optimal manner as possible.

The 1st call was initiated with with a bitrate of 500Kbps, while the 2nd call was initiated with a bitrate of 300Kbps. NetSense attempts to optimize the bandwidth utilization of both calls, resulting finally (after around 15 seconds) in the 2 calls converging to 450Kbps and 375Kbps.

Convergence of a Multiple Call Scenario

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About RADVISIONRADVISION (NASDAQ: RVSN) is the industry’s leading provider of market-proven products and technologies for unified visual communications over IP and 3G networks. With its complete set of standards-based video communications solutions and developer toolkits for voice, video, data and wireless communications, RADVISION is driving the unified communications evolution by combining the power of video, voice, data and wireless – for high definition video conferencing systems, innovative converged mobile services, and highly scalable video-enabled desktop platforms on IP, 3G and emerging next-generation networks. For more information about RADVISION, visit www.radvision.com

This document is not part of a contract of license as may be expressly agreed RADVISION is registered trademarks of RADVISION, Ltd. All trademarks recognized. All rights reserved © 2010 RADVISION, Ltd. Rev D 07-10.

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ConclusionBandwidth estimation and adaptation techniques are truly a must for any video-based application that utilizes the Internet for communications.

RADVISION’s NetSense technology is focused on providing standardized and optimized video calling over the Internet. It enables consistently high quality visual communications, even over unmanaged networks, across all enterprise and consumer arenas.

The RADVISION solution delivers an optimized video experience, transmittable to a wide range of end point devices, on a variety of network configurations. This integrated approach enables service providers, enterprises and system integrators to provide a high quality user experience.

With effective bandwidth adaptation dramatically improving the video experience, NetSense brings substantial benefit to users while maintaining the high level of interoperability RADVISION is known for.