The rapid development of Internet of Things (IoT) attracts growing attention from both industry and academia. IoT seamlessly\nconnects the real world and cyberspace via various business process applications hosted on the IoT devices, especially on smart\nsensors. Due to the discrete distribution and complex sensing environment, multiple coordination patterns exist in the heterogeneous\nsensor networks, making modeling and analysis particularly difficult. In addition, massive sensing events need to be\nrouted, forwarded and processed in the distributed execution environment. Therefore, the corresponding sensing event\nscheduling algorithm is highly desired. In this paper, we propose a novel modeling methodology and optimization algorithm for\ncollaborative business process towards IoT applications. We initially extend the traditional Petri nets with sensing event factor.\nThen, the formal modeling specification is investigated and the existing coordination patterns, including event unicasting pattern,\nevent broadcasting pattern, and service collaboration pattern, are defined. Next, we propose an optimization algorithm based on\nDynamic Priority First Response (DPFR) to solve the problem of sensing event scheduling. Finally, the approach presented in this\npaper has been validated to be valid and implemented through an actual development system.
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