Probability Modeling and Functional Validation of Dynamic Service Composition for Location Based Services with Uncertain Factors

Abstract

In the Internet of Things (IoT) environment, real-time servers run with many uncertain factors. The modeling and validation for the dynamic service composition of location based services (LBS) in the IoT environment are essential, but it is difficult to consider these uncertain factors. In this paper, after analyzing the advantage and shortage of traditional modeling methods, with the introduction of probability, we propose a Color Probability-TCPN (CPTCPN) by using the tokens with specific colors. The analysis and functional validation methods based on CPTCPN are proposed and described. After using it to model and analyze the LBS based in the IoT environment, we demonstrate the result which indicates the CP-TCPN based approach can satisfy the modeling and analysis of the IoT based real-time system with uncertain factors.