Simulation Modeling of Temporal Multimodality in Online Streams

Temporal variability in online streams arises in information systems where heterogeneous modalities exhibit varying latencies and delay distributions. Efficient synchronization strategies help to establish a reliable flow and ensure a correct delivery. In this paper, we establish a formal modeling foundation to address temporal dynamics in streams with multimodality using a discrete event system specification framework. This specification captures different latencies and interarrival dynamics inherent in multimodal flows. We also incorporate a Markov variant to account for variations in delay processes, thereby capturing timing uncertainty in a single modality. The proposed models are modular with inherent accounts for diverse temporal integration, thereby facilitating heterogeneity in information flows and communication. Various structural and behavioral forms can be flexibly represented and readily simulated. We demonstrate the experiments of several model permutations through the time-series behavior of individual stream components and the overall composed system, highlighting performance metrics in both, while quantifying the composability and modular effects.