Hierarchical Policy Decision Framework for Cloud-Native Telecom
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cloud-native telecommunication systems face challenges with functional separation of policy enforcement points (PEP) and policy decision points (PDP), leading to overwhelmed central policy servers, increased network traffic, packet loss, and unpredictable decision-making due to lack of consideration for the current state of PEPs and their dependencies.
Innovation Solution
A hierarchical policy-based decision framework is introduced, where a central policy server receives network policies, and a separate cluster policy server determines relevance and stores policies in a cluster database. A PDP module, separate from the cluster policy server, obtains and evaluates these policies based on queries from PEP modules, enabling localized and dynamic decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central policy server is used to make all policy decisions, then centralized control is achieved, but the server becomes overwhelmed and network traffic increases
Solution Approach 1:
The patent divides the centralized policy server into multiple distributed Policy Decision Points (PDPs) that are co-located with Policy Enforcement Points (PEPs) in the network hierarchy. This segmentation allows policy decisions to be made locally at each network level rather than funneling all requests to a single central server, thereby distributing the decision-making load and improving overall system productivity while maintaining centralized control through the hierarchical structure.
2Productivity
If the number of network hops between PDP and PEP increases, then more distributed decisions can be made, but packet loss and jitter increase causing unreliable decisions
Solution Approach 1:
The patent introduces a hierarchical dimension to the network architecture, organizing PDPs and PEPs into multiple levels (core network, edge network, access network). This hierarchical structuring allows policy decisions to be made at the most appropriate level in the hierarchy, minimizing the number of network hops required while still enabling distributed decision-making. The hierarchical approach maintains reliability by keeping communication paths short and predictable.
3Measurement precision
If state information of all PEPs is pushed to the central policy server, then complete policy decisions can be made, but network bandwidth and delay issues make it difficult and unviable
Solution Approach 1:
The patent enables each distributed PDP to maintain and use local state information of PEPs co-located with it, rather than requiring all state information to be centralized. Each PDP makes policy decisions based on locally available state information, which is sufficient for making accurate decisions at that specific network level. This local quality approach maintains policy decision accuracy while dramatically reducing network bandwidth consumption and eliminating the need to push all state information to a central server.
Data Source
AI summary
A method of policy decision includes receiving, by a central policy server, a network policy, determining, by a cluster policy server that is separate from the central policy server, whether the network policy is relevant to a cluster corresponding to the cluster policy server, storing, by the cluster policy server, the network policy in a cluster policy database based on determining that the network policy is relevant to the cluster corresponding to the cluster policy server, obtaining, by a policy decision point (PDP) module that is separate from the cluster policy server, the network policy stored in the cluster policy database, and determining, by the PDP module, whether to implement the network policy based on a policy query received from a policy enforcement point (PEP) module.