Service Layer Optimization element to Improve Utilisation of Network Capacity

Picture Source: Simple LTE for 4G Mobile Broadband

The following is an extract from 4G Americas whitepaper, "Optimizing the Mobile Application Ecosystem":

Applications have diverse requirements on the mobile network in terms of throughput, relative use of uplink vs. downlink, latency and variability of usage over time. While the underlying IP based Layer 3 infrastructure attempts to meet the needs of all the applications, significant network capacity is lost to inefficient use of the available resources. This inefficiency stems primarily from the non-deterministic nature of the aggregate requirements on the network from the numerous applications and their traffic flows live at any time.

This reduction in network utilization can be mitigated by incorporating application awareness into network traffic management through use of Application or Service Layer optimization technologies. A Service Layer optimization solution would incorporate awareness of:

1) device capabilities such as screen size and resolution;

2) user characteristics such as billing rates and user location;

3) network capabilities such as historic and instantaneous performance and;

4) application characteristics such as the use of specific video codecs and protocols by an application such as Video on Demand (VOD) to ensure better management of network resources.

Examples of Service Layer optimization technologies include:

* Real-time transcoding of video traffic to avoid downlink network congestion and ensure better Quality of Experience (QoE) through avoidance of buffering

* Shaping of self-adapting traffic such as Adaptive Streaming traffic through packet delay to avoid downlink network congestion

* Shaping of error-compensating flows such as video conferencing through use of packet drops to avoid uplink network congestion

* Shaping of large flows such as file uploads on the uplink through packet delays to conserve responsiveness of interactive applications such as web browsing

* Explicit caching of frequently accessed content such as video files on in-network CDNs to minimize traffic to backbone

* Implicit caching of frequently accessed content such as images in web content on in-network caches to improve web page retrieval speeds

Service Layer optimization technologies may be incorporated in the data path in many locations:

1) the origin server;

2) the UE device;

3) as a cloud-hosted offering through which devices and/or applications and/or networks route traffic or;

4) as a network element embedded in a service provider’s network.

Further, in a service provider’s network the optimization function may be deployed in either the core network and/or edge aggregation locations. When Service Layer optimization entities in the network are deployed at both core and edge locations, they may operate in conjunction with each other to form a hierarchy with adequate level of processing to match the traffic volume and topology. Such a hierarchy of network entities is especially effective in the case of caching.

The 3GPP standard network architecture defines a number of elements such as QoS levels that are understood and implemented in the network infrastructure. However, much of this network capability is not known or packaged for use in the Service Layer by application developers. One approach to resolving this discrepancy may be to publish standard Service Layer APIs that enable application developers to request network resources with specific capabilities and also to get real-time feedback on the capabilities of network resources that are in use by the applications. Such APIs may be exposed by the network to the cloud or may be exposed to application clients resident on mobile devices through device application platforms and SDKs. The network APIs being defined by the Wholesale Application Community are an example of the recognition of the need for such Service Layer visibility into network capabilities. Future versions of the WAC standards will likely incorporate and expose network Quality of Service (QoS) capabilities.

Pic Source: Aria Networks

Why does Optimization matter? A good answer to this question is provided in Telecoms.com article as follows:

For many people, says Constantine Polychronopoulos, founder and chief technology officer of mobile internet infrastructure specialist Bytemobile, the definition of optimisation as it relates to mobile networks is too narrow; restricted to compressing data or to the tweaking of the radio access network in a bid to improve throughput. While these are key elements of optimisation, he says, the term ought to be interpreted far more broadly. “The best way for us to think of optimisation,” he says, “is as a set of synergistic technologies that come together to address everything that has to do with improving network and spectrum utilisation and user experience. If you stretch the argument, it includes pretty much every thing that matters. This holistic, end-to-end approach to optimisation is the hallmark of Bytemobile’s solutions. Point products tend to be costly and difficult or impossible to evolve and maintain.”

And optimisation matters, he says, because the boom in mobile data traffic experienced in some of the world’s most advanced mobile markets represents a serious threat to carrier performance and customer satisfaction. US operator and pioneer iPhone partner AT&T is a case in point, Polychronopoulos says.

“If you look at what’s been said by Ralph de la Vega (president and CEO of AT&T Mobility) and John Donovan (the firm’s CTO), they have seen a 5,000- per cent increase in data traffic over the past two years. The data points from other operators are similar,” he continues. “They see an exponential growth of data traffic with the introduction of smartphones, in particular the iPhone.”

Operators may have received what they’d been wishing for but the scale of the uptake has taken them by surprise, Polychronopoulos says. The type of usage consumers are exhibiting can be problematic as well. Bytemobile is seeing a great deal of video-based usage, which can often be a greater drain on network resource than web browsing. Given the increasing popularity of embedding video content within web pages, the problem is becoming exacerbated.

Dr. Polychronopoulos is keen to point out that there are optimisation opportunities across different layers of the OSI stack—Bytemobile offers solutions that will have an impact on layers three (the IP layer) through seven (the application layer). But he stresses that some of the most effective returns from optimisation technologies come from addressing the application layer, where the bulk of the data is to be found.

“An IP packet can be up to 1,500 bytes long,” he says. “So at layer three, while you can balance packet by packet, there is only so much you can do to optimise 1,500 bytes. At the top layer, the application can be multiple megabytes or gigabytes if you’re watching video. And when you’re dealing with those file sizes in the application layer, there is a whole lot more you can do to reduce the amount of data or apply innovative delivery algorithms to make the content more efficient,” he says.

By optimising content such as video, Polychronopoulos says, significant gains can be made in spectral and backhaul network utilisation. A range of options are open to operators, he says, with some techniques focused on optimising the transport protocol, and others designed to reduce the size of the content.

“With video, we can resize the frame, we can reduce the number of frames, we can reduce the resolution of the frame or apply a combination of the above in a way that does not affect the video quality but greatly improves network efficiencies,” he says. “So if you go to a site like YouTube and browse a video, you might download something like 100MB of data. But if you were to go through a platform like ours, you may download only 50MB when the network is congested and still experience not only the same video quality, but also fluid video playback without constant re-buffering stalls.”

It is possible, he explains, to run these solutions in a dynamic way such that data reduction engages only when the network is congested. If a user seeks to access high-volume data like video during the network’s quiet time, the reduction technologies are not applied. But when things are busier, they kick in automatically and gradually. This could have an application in tiered pricing strategies. Operators are looking at such options in a bid to better balance the cost of provisioning mobile data services with the limited revenue stream that they currently generate because of the flat rate tariffs that were used to stimulate the market in the first place. Being able to dynamically alter data reduction and therefore speed of delivery depending on network load could be a useful tool to operators looking to charge premium prices for higher quality of service, Polychronopoulos says.

If it is possible to reduce video traf- fic in such a way that data loads are halved but the end user experience does not suffer proportionally, the question arises as to why operators would not simply reduce everything, whether the network was busy or not. Polychronopoulos argues that in quiet times there are no savings to be made by reducing the size of content being transported.

“The operator has already provisioned the network one way or another,” he says, “so there is a certain amount of bandwidth and a certain amount of backhaul capacity. When the network is not congested, the transport cost is already sunk. When it becomes congested, though, you get dropped calls and buffering and stalled videos and the user experience suffers. That’s where optimisation shines. Alternatively, media optimisation can be factored in during toplevel network provisioning when the savings in CAPEX can be extremely compelling.”

While LTE is held up by some within the industry as the panacea to growing demand for more mobile broadband service, Polychronopoulos is unconvinced. If anything, he says, the arrival of the fourth generation will serve only to exacerbate the situation.

“LTE is going to make this problem far more pronounced, for a number of reasons,” he says. “As soon as you offer improved wireless broadband, you open the door to new applications and services. People are always able to come up with new ways of inundating any resource, including bandwidth. We’re going to see more data-driven applications on mobile than we see on the typical desktop, because the mobile device is always with you.” And while LTE promises greater spectral efficiency than its 3G forebears, Polychronopoulos says, the fact that spectrum remains a finite resource will prove ever more problematic as services evolve.

“We’re reaching the limits of spectral efficiency,” he says. “Shannon’s Law defines the limit as six bits per Hertz, and while we may be moving to higher-bandwidth wireless broadband, spectrum remains finite. To offer 160Mbps, you have to allocate twice the amount of spectrum than in 3G, and it’s a very scarce and very expensive resource.”

Operators have been wrong to focus exclusively on standards-based solutions to network optimisation issues, Polychronopoulos says. In restricting themselves to 3GPP-based solutions, he argues that they have missed what he describes as “the internet component of wireless data.” Internet powerhouses like Google, Yahoo and Microsoft (which he dubs ‘the GYM consortium’) have established a model that he says is a great threat to the mobile operator community in that it establishes a direct consumer relationship and disregards the “pipe” (wireless broadband connection) used to maintain that relationship.

“The operators have to accelerate the way they define their models around wireless data so that they’re not only faster than the GYM consortium in terms of enabling popular applications, but smarter and more efficient as well,” he says. Dr. Polychronopoulos then makes a popular case for the carriers’ success: “The operators have information about the subscriber that no other entity in the internet environment can have; for example, they know everything the subscriber has done over the lifetime of their subscription and the location of each event. They don’t have to let this data outside of their networks, so they are very well positioned to win the race for the mobile internet.”