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Method for autonomous intelligent runtime policy management system Disclosure Number: IPCOM000202286D
Publication Date: 2010-Dec-13
Document File: 2 page(s) / 31K

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The Prior Art Database


Disclosed is a mechanism that enables existence of dynamic policies used by web service in Telecommunication environments.

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Method for autonomous intelligent runtime policy management system

Today subscribers are looking for the right balance between their quality of experience (QoE), the availability of the applications they are commonly using, and the budget available to them. Explosive growth in network bandwidth utilization; strong competition to acquire new customers; congested networks; cheap mobile data service plans; and the inability to assure application performance for users lead to poor end-user satisfaction. The result is customer churn, the need to drop service plan prices, and increased costs in customer retention and acquisition. Additionally, mobile operators are investigating ways to enable a subscriber to delay their usage of the service in exchange for a bandwidth credit. However this requires visibility at the subscriber level and the ability to communicate with customers concerning their specific usage - today it is widely done through customer portals or call center interactions. This knowledge, essential to ensure the end user QoE, can be enhanced by a multi-dimensional data model that supports realtime business analytics to gain a better understanding of how subscribers use specific services and how applications consume the service providers limited network bandwidth and resources.

One place to explore customer habits and usage pattern is service invocation in Service Delivery Platforms. Large number of these invocations are based on web service calls and typically are ParlayX compliant.. Typical high level architecture overview is shown with Fig 1. Invokers access service through access gateway layer that checks policies according to data stored in directory server.


Backend network elements

Fig 1.

Typically all existing systems deal with static policy or eventually with dynamical discovering of the new attributes to be stored in policy, however once those are stored they are not updated based on future invocations. Therefore there is a need for run time adjustment of policy data based on invoker, usage, messages and context. Method for autonomous policy information adjustment solves problem of static data stored in policy management system which enables existence of dynamic run time policies. The end result is much better customer experience (automatic