Probabilistic models for access strategies to dynamic information elements

In various network services remote access to dynamically changing information elements is a required functionality. Three fundamentally different strategies for such access are investigated in this paper: (1) a reactive approach initiated by the requesting entity, and two versions of proactive approaches in which the entity that contains the information element actively propagates its changes to potential requesters, either (2) periodically or (3) triggered by changes of the information element. This paper develops probabilistic models for these scenarios, which allow to compute a number of performance metrics, with a special focus on the mismatch probability. In particular, we use matrix-analytic methods to obtain explicit expressions for the mismatch probability that avoid numerical integration. Furthermore, limit results for information elements spread over a large number of network nodes are provided, which allow one to draw conclusions on scalability properties. The impact on mismatch probability of different distribution types for the network delays as well as for the time between changes of the information element are obtained and discussed through the application of the model in a set of example scenarios. The results of the model application allow for design decisions on which strategy to implement for specific input parameters and specific requirements on the performance metrics.