In part one of this tip on WLAN design for video delivery, we discussed capacity requirements and 802.11n considerations for wireless video optimization. Part two addresses additional network
enhancements for video and ways to measure wireless video performance on WLANs.
Going beyond basic 802.11n features for video optimization, it's important to consider using other proprietary functions that are built into network components for improved video performance. Once that's done, it's also key to measure wireless video performance continuously to maintain quality.
Proprietary network enhancements that improve wireless video performance
Vendors include a variety of features in their network hardware that can be used to optimize wireless video delivery and performance. Here are some proprietary network features to look for:
Extending prioritization into the wired network. Look for access points (APs) that support mapping between Wi-Fi Multimedia classes; 802.1p (at the MAC level); and Differentiated Services Code Point, or DSCP, IP priority markings. Consider APs that are video-aware and capable of applying the right prioritization to specific video flows.
More on managing wireless video performance
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Video-aware APs. Because multicasting over Wi-Fi tends to reduce data rates and increase error rates, look for features that optimize multicast video. For example, video-aware APs might auto-select higher rates for multicasting, or they could convert wired multicast packets into wireless unicast frames. Conversion is beneficial when a video is being received by only a few clients; some products can take this into account and still use multicast where it makes sense (in webcasts, for example). Some products are actually sensitive to specific codecs and frame types. This intelligence can be used to adjust AP behavior to reduce the loss of more important frame types or perform transcoding (conversion to more error-resilient encodings) or transrating (reducing video resolution as needed to accommodate lower data rates).
Features to manage client diversity. Client diversity can degrade WLAN performance in general and wireless video performance in particular (especially multicast videos). But many vendors have developed optimizations to deal with diversity, including transmit beamforming and radio management tweaks. With transmit beamforming, APs customize transmissions to each client to reduce errors. Radio management algorithms can alter the airtime allocated to each device so that newer or faster clients aren't slowed by older or slower clients. Ideally, these optimizations should also be video-aware.
Wireless mesh networking. Some wireless video applications (outdoor wireless cameras and digital signage, for example) can be facilitated by a wireless mesh network. Although many dual-radio 802.11n APs support wireless mesh, be aware that not all are designed to prioritize and optimize video over wireless backhaul links.
Wired-side network optimization. This includes such video optimization methods as Internet Group Management Protocol snooping to avoid needless multicast forwarding from controller to the AP and to prioritize handling of video traffic tunnelled between the AP and controller.
Measuring wireless video performance
In an 802.11n WLAN, signal strength is not a good proxy for acceptable wireless video performance. Uplink and downlink data rates can differ because of multipath behavior, as well as differences among APs, client antennas and chipsets. Therefore, the only way to verify that the viewer experience is good is to measure results for video and multimedia application performance using representative applications and devices in situ.
One industry-standard metric for measuring video quality is the Media Delivery Index (MDI). It combines Delay Factor (DF), a metric used to quantify latency and jitter, with Media Loss Rate (MLR), a metric used to reflect lost and out-of-order packets. Because DF measures how many milliseconds it takes to drain a buffer, keeping DF low (for example, under 50 msec) is important for interactive video but doesn't have much impact on IP TV, streaming, or on-demand video. Media Loss Rate measures the number of packets lost per second, and must be kept very low for high-quality video (that is, under 0.001 -- in effect, zero). Video service-level agreements (SLAs) and measurements are usually specified as a ratio of DF) to MLR (for example, 50:0).
Video equipment manufacturers often use specialized traffic generators and measurement tools to test products, such as set-top boxes, media gateways and video cameras. AP vendors can use similar tools to measure video Quality of Experience (QoE) under artificial loads; for example, generating a single standard-definition TV or high-definition TV stream consumed by hundreds of simulated Wi-Fi clients.
Using live network tools for WLAN video measurement
Product developers find these tests extremely useful in optimizing their video handling, but enterprises need live network test tools to measure and compare actual QoE to design goals.
For example, Ixia's IxVeriwave WaveDeploy is a suite of test tools for WLAN site assessment. Testers can install the WaveDeploy Agent on live Wi-Fi client devices, such as laptops, iPhones and Android tablets, and these devices can be wheeled around on a cart inside the venue to be measured, receiving video test traffic while recording MDI and other metrics, such as received signal strength indicator, or RSSI. Alternatively, a purpose-built traffic generator can be used to simulate as many as 64 Wi-Fi clients. MDI scores then are compared to SLAs to produce heat maps on a floor plan, helping testers see which devices and locations require improvement.
Of course, it's also possible to send live wireless video to a squadron of laptops or iPads and subjectively eyeball the outcome. But a more formal testing method and tools such as these can help identify problematic client devices and help an enterprise understand the impact of steps taken to improve video performance -- particularly in higher-density or diverse WLANs.
This was first published in September 2012