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Feature Article
March 2002

VoIP In The Call Center: A Guide To Call Quality And SLA Metrics

By Bob Massad, Telchemy

Use of Voice over IP (VoIP) is spreading. Not only are more people turning to VoIP in general, but also it's moving into specific areas of the enterprise. Call centers represent one such area. We at Telchemy believe that applications in call centers will be a major market driver for VoIP over the next several years. Industry forecasters have noted that in a few years, call centers may account for a third of VoIP use. This is all part of the 'IP-everywhere' disposition in the communications world. To be sure, there is not a wholesale change out, but a steady migration to IP-based services is evident.

The benefits of VoIP for the enterprise, and for the call center specifically, are many. Not only does VoIP provide a quality experience at low cost, but also it leverages and reduces existing infrastructure. No longer is there a need for separate and parallel 'telecom' and 'data comm' infrastructures and management teams, for example. IP networks also provide a more open and efficient, less expensive and complex environment, one which is quicker to deploy and provides richer application potential than does the closed, circuit-switched world of the PSTN.

Given the move to VoIP, how do we ensure that it is successful? That is, how do we ensure that the quality is on par with the PSTN and that the service expected (and paid for) is the service delivered?

Call Quality
Call quality measurement comes first. We need to understand how to measure it and where to measure it. From that understanding, we can construct service level agreements (SLAs) that focus on the metrics that are important and accurately reflective of call quality.

Call quality, often misrepresented under the moniker of Quality of Service (QoS), should be measured against real traffic and in real-time. There are tools available that inject pre-recorded audio files in the network, record the received file, either at the other end or looped back to the source, and then do a mathematical comparison of the sent and received files. This process is complex, slow and not necessarily indicative of real traffic.

It is much better to implement call quality metering technology into voice end points, such as a VoIP gateway, media server or IP phone, and/or into 'on the wire' analyzer and probe devices that are normally instantiated between domains and have access to live calls. It is often beneficial to utilize both types of devices. For example, having metrics available in both allows for quick 'problem isolation,' e.g., knowing that the call was good at the access point, but not good at the end point may isolate the problem to the local network. If the metrics show poor quality at both points, then the problem may be in the access network. Moreover, analyzers and probes can then be configured to capture traffic at offending levels or from offending sources for detailed analysis and problem resolution.

Once we've determined how (real traffic) and where to monitor (end points and aggregation points between domains), we need to understand what specifically to monitor. VoIP and video over IP traffic are of a different nature than traditional packet network traffic, even though they are packetized. Traditional IP traffic has been non-real-time, TCP-based traffic (such as e-mail and file transfer) that is not 'perceptual' in nature, whereas VoIP traffic is necessarily real-time, UDP-based and totally perceptual in nature (i.e., 'could I hear what was said?').

Given that, the traditional utilization-based approaches and metrics do not apply. Reporting the number of bytes or packets sent or lost, and reporting the averages per call or per link are not of much help. Some tools will extend the traditional data set to include delay and jitter, but these are not too helpful either. None of the tools traditionally available correlate these statistics so that a quick and clear indication of call quality is possible, especially for nontechnical staff. And none includes the end user's perception of the call. Let's look a bit closer to see why.

Previously we noted that packet loss, delay and jitter metrics are ineffectual indicators of call quality. End points such as IP phones or media gateways employ a jitter buffer, sometimes called a de-jitter buffer. Its task is to remove jitter from the listener's point of view. To do that, it adds a reasonable amount of packet delay, on the order of 50 to 150 milliseconds ' the upper boundary on what would be considered 'toll quality.' It then plays out those packets at a 'constant' rate, discarding those packets that have exceeded the jitter buffer's delay boundary. Thus, the listener does not directly experience jitter. The jitter has been turned into additional delay and excessive delay is turned into packet loss.

Taking delay a bit further, we find that delay issues don't relate so much to call quality, (i.e., the listener's ability to discern exactly what was said) as much as it relates to conversational quality (i.e., the ability of carry on a smooth conversation where the person speaking changes based on some occasional 'cue'). When delay is too long, people have a tendency to think they missed a cue and will start or resume speaking. When the cue finally arrives, it collides with the started or resumed speech of the other party, causing what is called 'double talk.' The phonetics are fine, they are simply out of sync.

The last area of concern is packet loss. Here the issue becomes a bit subtler. At a high level, packet loss is the issue that has the most impact when determining call quality. But at a detailed level, it's a specific kind of packet loss we need to be concerned about, and we need to understand its specific source.

Packet loss is generally classified as randomly occurring (a packet lost here or there) or as occurring in bursts (several consecutive packets are lost). For VoIP, the real problem is burst loss. VoIP end points employ codecs (coder/decoder) that typically implement packet loss concealment (PLC) algorithms. The algorithms may, in the event of packet loss, replay the last packet, insert comfort noise, interpolate, etc. In effect, they render packet loss unnoticeable. For example, using the values provided under ITU standard G.113, which defines network transmission impairments such as packet loss and their impact on call quality, a standard G.711 codec without PLC in a 2 percent loss scenario has a 35 impairment rating, whereas with PLC in the same scenario, it has only a 7 impairment rating. The moral: be sure to deploy codecs that are PLC enabled.

One can see intuitively where these algorithms are only useful for random or isolated packet loss. With burst loss, replaying the last packet several times would produce a stuttering or 'rrrrrr' effect, or continuous insertion of comfort noise would produce extended silence, or frames of reference would be lost for interpolation. So clearly, the most important network factor in call quality metering is burst packet loss.

It also turns out that most lost packets occur in bursts. Studies have shown that approximately 50 percent of lost packets occur in the top 1 percent of burst loss occurrences. Other studies have shown that the average burst consumes seven or eight packets, well beyond packet loss concealment capabilities.

In traditional monitoring tools and agents, packet loss is presented in terms of percentage loss, average loss and total loss. None of these measurements contains the notion of 'burst.' Moreover, as a data point, they go from being unenlightening in the total loss case, to being misleading in the percentage or average cases. For example, if one assumes 5 percent packet loss in a 1,200 packet call, one would deduce that 60 packets were lost and then likely deduce that 1 in 20 was lost. From our previous discussion, we know that PLC will handle this situation easily, rendering the loss unnoticeable. So, this may be construed as being a 'toll quality' call. However, the actual packet loss distribution may reveal that there were 6 bursts of 8 lost packets and 2 bursts of 6 lost packets, both beyond the scope of PLC, and therefore it was really a very poor call. The point is that to understand and measure call quality, the monitoring device or system must account for burst loss in order to be accurate.

Other Perceptual Factors
There are other factors as well that contribute to call quality that must be taken into account, i.e., correlated with burst loss, for accurate call quality measurement. One such factor is codec type. Different codec types offer different levels of call quality degradation for similar packet loss levels. This is due to the fact that most codecs differ in compression level. The greater the compression, which is implemented to save link width, the more voice information is lost per loss event. For example, a standard G.711 PCM codec is uncompressed. It consumes 64 Kbps. G.729A consumes only 8 Kbps for the same amount of voice and therefore can pack more voice into a packet. Thus, each packet lost with G.729 encoding loses much more voice than does G.711. For example, according to G.113, a G.711 codec with PLC in a 2 percent packet loss environment registers an impairment value of 7, while G.729A codec registers an impairment value of 19 in the same loss scenario.

In correlating the relevant factors, both with each other and in real-time, the VoIP call quality monitor can provide a single-number, accurate, clear and unambiguous quality rating of the call. These ratings have been the subject of much study and have been standardized by international standards bodies such as ITU and ETSI and are called 'R' factors. They are very much like school test grades. For example, an 80 'R' is a toll quality or good call; a 60 'R' is a very poor quality call. Measuring call quality should be that simple.

Three key points have emerged for making VoIP successful in the call center, and across the enterprise in general. One is to implement voice quality monitoring capabilities or agents into VoIP end points such as gateways, IP phones and media servers, as well as into 'on the wire' analyzers and probes so that live traffic can be monitored in real-time and provide for problem isolation and resolution. The second key point is that for call quality metrics to be an accurate and direct indication of call quality, they must consider burst packet loss, i.e., the actual packet loss distribution. The third key point is that the truly relevant factors in measuring call quality must be correlated against each other and in real-time to allow for a single-number metric of call quality.

Bob Massad is vice president of marketing for Telchemy. For more information, please visit their Web site at www.telchemy.com.

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