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Real-Time Data Delivering Based on Prediction Scheme over Internet of Things

Ding-Jung Chiang,


Internet of Things is a technology to connect machines, objects, and people with electronic devices. With the emergence of large mobile and wireless networks, many real-time applications need to period operate data stream. At the same time, many of these systems have inherent timing constraints. Providing deadline guarantees for data stream with time constraint is a challenging problem due to large real-time data arrival rates and time-varying data contents. In this paper, we propose a prediction-based scheme for data stream with time constraint over Internet of Things (IoT). It is an important issue to effectively disseminate various materials in IoT environments. This paper highlights important problems that have mobile realtime systems from improving the system performance it could be for IoT applications. While current systems aim to foster significant improvements in deployment of IoT applications, this paper argues that most systems are still limited to just design architecture without performance concerns. IoT real-time infrastructure has become a topic for research. A performance driven model to IoT real-time delivery is proposed in this paper. A novel methodology for deploying real-time data stream based on prediction mechanism in IoT environments is presented. Our experimental evaluation of the management scheme shows that our approach performs very well even with workload fluctuations and our QoS management scheme yields better overall system utility than the existing approaches for QoS management.


Internet of Things (IoT); Kalman filter; Realtime data stream

Citation Format:
Ding-Jung Chiang, "Real-Time Data Delivering Based on Prediction Scheme over Internet of Things," Journal of Internet Technology, vol. 18, no. 2 , pp. 395-405, Mar. 2017.

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