UPDATED 10:31 EDT / NOVEMBER 12 2014

How Software-Defined Access Networks bring service agility to operators

Big Data, Worldwide connected Big DataSoftware-defined networking (SDN) is generating big interest as a technology that makes networks programmable and less expensive to build and operate. SDN is achieved by separating the control and the data-forwarding functions of network equipment, and centralizing the control functions of multiple network elements. More generally, SDN is a framework for the automatic and dynamic management of multiple network elements. Major carriers that already have announced SDN initiatives include Telefonica, AT&T, and Deutsche Telekom.

So far, SDN control has referred to the control of network functions that reside above the physical layer – such as packet forwarding – and in the carrier’s data centers. But can there be a Software-Defined Access Network? Absolutely yes! The SDN framework also applies to access networks – the so-called “last mile,” where virtualizing access-network control and management functions results in enormous gains in service agility and reliability, particularly in multi-operator environments. Benefits of virtualizing the access network include:


  • Streamlining operations
  • Accelerating services creation
  • Enhancing access network performance
  • Enabling competition among service providers on a shared infrastructure


There are three models for a software-defined Access network (SDAN), which can apply to any access technology. Unlike traditional SDN, the control and configuration of physical layer parameters also are an integral aspect of a SDAN.

SDAN Model 1


The first model of an SDAN uses software to centrally control and manage lines connected to the access hardware. Control functions include the optimization of the physical layer configuration of the broadband connection—for example, changing parameters, such as data rates, coding schemes and power levels, to ensure a reliable connection that meets all service requirements.

Management functions include network diagnostics and analytics that drive maintenance operations and marketing campaigns. Such functions can include line diagnostics used by technicians for isolating and correcting problems in the outside plant, and targeted recommendations for service upsell based on line qualification and past usage records.

Centralizing these functions enables the use of advanced analysis and resource allocation algorithms implemented in standard servers instead of relying on the more limited and inflexible functionality available in access hardware. Most importantly, this model allows for homogeneous, vendor-agnostic management of the access hardware, and does not require hardware changes since it relies on existing management interfaces.

SDAN Model 2


The second model of an SDAN uses software to manage virtualized access networks. The return on investment (ROI) in new access infrastructure (e.g., FTTN, FTTH) is improved when the infrastructure can be shared among multiple, competing service providers. The physical network is partitioned into virtual networks corresponding to the customers of each of the retail providers.

Software maps the physical access hardware (e.g., DSL access multiplexers or optical network terminals) to virtual hardware. The virtual hardware can be controlled and managed by the service providers (or virtual network operators), while providing for determinacy in the operation and performance of the underlying physical network. This model greatly improves the virtual network operator’s information about, and control over, the access network, almost as though the operator owns its own hardware. As opposed to the use of Bit-stream Access (Layer 2) unbundling, this model lets the virtual network operator design its own competitive service products and make real-time changes on the network.

Figure 1 shows an architecture that combines the above two models. The access hardware interfaces with multi-tenant software that implements a Virtualization and Management layer. The tenants include the virtual network operators and the infrastructure provider. Each has access to functions for diagnostics, analytics and optimization, which are configured to meet their specific objectives. For example, a service qualification function for operator A can favor higher access speeds and accept a small amount of stability loss, while operator B may prefer to offer its customers the most reliable services, even if that means that access speeds are conservatively set.

This architecture allows individual operators to develop competitively differentiated services. Further, the shared management system improves coordination for trouble resolution: when an issue emerges, the system can clearly identify the source(s) of the problem.

Screen shot 2014-11-12 at 9.11.04 AM

Figure 1.  This diagram illustrates SDAN Model 1, which uses software to centrally control and manage lines connected to the access hardware; and SDAN Model 2, which uses software to manage virtualized access networks.


SDAN Model 3


The third model of an SDAN provides a natural framework for fusion of broadband service performance data, both horizontally and vertically across the access and service networks. This framework enables management of the home network, which becomes a necessity as the number of devices continues to grow. Additionally, this framework allows monitoring and tuning of the customer’s broadband experience with OTT services.

Figure 2 depicts the architecture for leveraging end-user network diagnostics data.  It exposes performance and diagnostics data from multiple network elements and services of the end-user to broadband access management platforms via a secure and published API.

Screen shot 2014-11-12 at 9.13.10 AM

Figure 2.  This diagram illustrates SDAN Model 3, which fuses broadband service performance data, both horizontally and vertically, across the access and service networks.


In the horizontal direction, data from agents in the home (but possibly also from the core and edge) portions of the network are combined to assess performance and identify underperforming segments. For example, throughput bottlenecks can be identified by comparing speed and oversubscription bottlenecks along the path to the end-user. In the vertical direction, data from agents in devices at different network layers are compared to assess user experience and develop strategies for optimization. For example, excessive MPEG decoder errors combined with an absence of congestion indications indicate that a higher level of error protection is required on one or more constituent links.

For more information on this rapidly emerging technology, read the latest white paper from ASSIA experts, Software-Defined Access Networks, here.



Georgios Ginis-Headshot_editAbout the Author

George Ginis is senior vice president of service provider marketing with ASSIA, Inc., overseeing marketing and development of DSL network management products and helping service providers maximize the profit and performance of broadband access networks.

feature image by marsmet547 via photopin cc

A message from John Furrier, co-founder of SiliconANGLE:

Your vote of support is important to us and it helps us keep the content FREE.

One click below supports our mission to provide free, deep, and relevant content.  

Join our community on YouTube

Join the community that includes more than 15,000 #CubeAlumni experts, including Amazon.com CEO Andy Jassy, Dell Technologies founder and CEO Michael Dell, Intel CEO Pat Gelsinger, and many more luminaries and experts.

“TheCUBE is an important partner to the industry. You guys really are a part of our events and we really appreciate you coming and I know people appreciate the content you create as well” – Andy Jassy