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Rule-Based On-Line Feature Interaction Detection for IMS Call Control Services

This paper presents a rule-based on-line feature interaction detection approach for IMS (IP multimedia sybsystem) call control services. We model dynamic service behaviors, intentions and party relationships in simple and effective service notations carried in extended SIP headers at run time. A small set of service actions is abstracted from possible service operations upon SIP messages. Based on the service behavior model, two groups of feature interaction detection rules, action interaction rules and address interaction rules, are developed to describe the condition when pairs of call control services interacts with each other. By applying the rules on appropriate detection set of service notations, conflicted service instances can be identified for following resolution. We present experiment results that proves the effectiveness of our approach.