The Rise of Policy in Network Management:
Seductive Opportunities Along with Complex Risks

author: Grant Lenahan

The role of policy is about to expand rapidly, projecting a little-understood area, mostly associated with the operation of real-time routers, into the domain of management. It’s a great boon, but will demand re-thinking both what we think policy is, and what we think “OSS and BSS” are. Success will demand a well-defined plan, executed in a series of clearly defined steps.

Policy has been with us since the relatively early days of the Internet, when the IETF defined “Policy Decision Points” and “Policy Execution Points” – or PDPs and PEPs. Used only in very specific instances, policy has been limited to AAA/edge routers, and in 3G and 4G mobile networks “flow based charging”, where 3GPP defined the derivative “PCRF” and PCEF” to manage flow based charging.

The bottom line is that policy will quickly expand from relatively few use cases, to handling a wide range of network configuration tasks, all based on some key questions:

  • Who is the user, and what priority does that user have?
  • What is the product/service, or plan, and what parameters are demanded, possibly by SLA?
  • What is the network condition? Is it congested? Empty?
  • What are the technical and economic feasibility limits we must work within?

Policy is already being defined to control many attributes in SDN and NFV – scale, reliability, bandwidth, security, and location (geographic or datacenter) among others. Elements of a policy model are being talked about in various industry groups, from ETSI/MANO to the TMForum (Den-ng, ZOOM). But this is the dry “how?”; let’s discuss the exciting “what?”.

The real excitement begins when we understand that policy, combined with analytics and real-time (MANO-style) orchestration, can implement real-time, all-the-time, optimization of networks. While scary, these sorts of feedback loops have long been used in military and commercial guidance systems, in machine control, and in myriad other control systems. In fact, the basic ideas are called, in academia, “control theory”.

Imagine a data-center that approaches congestion, and through analytics driving new policy rules, automatically moves demand to a lightly used datacenter – improving performance and averting capital spend; quite the happy outcome. Or, consider analytics that correlate a set of security breaches with specific parameters, and closes the loophole, changing the policies that define those parameters. SDN, SON, NFV, and “3rd Network” based MEF services can all benefit from such dynamic and far-reaching policy.

Discussing each is beyond the scope of this Blog, but I’d like to set the stage for future dives into several elements of policy. In preparation, let’s consider that control-theory flow, from information collection (analytics), to determining the corrective action (optimization) to issuing the revisions (policy control and possibly orchestration). This simple, yet complex concept can fundamentally change the economics, flexibility and operation of networks. In my opinion, it is essential to derive the greatest benefit from virtualized networks.

Policy Circle

Before we begin a new hype cycle though, consider the challenges and risks. This level of automation will be difficult to deploy and tune. Policy conflicts must be managed, and autonomous systems must be tested, and trusted (“I wouldn’t do that, Dave”), and instability must be controlled (all control systems can oscillate). Success will likely come from a set of incremental steps, each of which adds – and tests – a layer of automation, and will therefore take years to complete. But those that benefit greatly will be those who build, brick by brick, to well understood goal or vision.

Stay tuned for future installations touching on specific areas of policy in tomorrow’s network.

Grant

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