Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Master of Engineering Science

Program

Electrical and Computer Engineering

Supervisor

Wang, Xianbin

Abstract

Recent evolution in the Internet of Things (IoT) and Cyber–physical systems (CPS) is expected to change everyday life of its users by enabling low latency and reliable communication, coordinated task execution and real time data processing among pervasive intelligence through the communication network. Precise time synchronization, as a prerequisite for a chronological ordering of information or synchronous execution, has become a vital constituent for many time-sensitive applications.

On one hand, Internet of Things (IoT) systems rely heavily on the temporal coherence among its distributed constituents during data fusion and analysis, however the existing solutions for data synchronization, do not easily tailor to resource-constrained scenarios. On the other hand, timestamping accuracy is of the utmost importance to achieve accurate time synchronization of large-scale connected systems, however the heterogeneity and complexity inherent to Internet of Things (IoT) systems lead to multi-source timestamping uncertainties and significantly deteriorate performance of traditional inflexible synchronization methods.

Therefore, this thesis aims at solving these challenges by proposing a low overhead and application-oriented synchronization in heterogeneous IoT systems. First, a low-overhead data synchronization scheme is proposed to achieve accurate temporal consistency prior to fusing the massive data collected from the distributed IoT devices. More specifically, a task period is scheduled for each sensor device to deliver the sampled data to Sink Node (SN). By comparing the difference between the predefined period and the real observed one, the clock parameters can be estimated accurately so that the misalignment of the data can be compensated accordingly. Simulation results show that the proposed scheme can enhance the data fusion accuracy to tens of microseconds with significantly reduced network overhead by up to 90%.

Next, a situation-aware hybrid time synchronization protocol is designed based on multi-source timestamping uncertainty modeling and integrated time information exchange mechanism for heterogeneous IoT systems. More specifically, the multi-source timestamping error inherent to the overall synchronization process are accurately modeled by exploring the impact of the multi-faceted operating conditions. By analyzing the real-time timestamping uncertainties, a hybrid time synchronization scheme is actualized, which can achieve optimal synchronization strategy for clock parameters estimation. In addition, an integrated time information exchange mechanism is designed to reduce timestamping redundancy during time synchronization. Simulation results show that the proposed scheme can enhance the synchronization accuracy for heterogeneous operating scenarios.

Summary for Lay Audience

By enabling low latency and reliable communication, coordinated task execution, and real-time data processing among intelligent devices through the communication network, recent development in the Internet of Things (IoT) is expected to change daily life of its users. Many time-sensitive applications now require precise time synchronization as a cornerstone for the accurate data processing and efficient task collaboration.

Internet of Things (IoT) systems strongly depend on consensus on time domain among their widespread participants during data fusion and analysis, however the current methods for data synchronization and clock synchronization are difficult to be applied to resource-constrained and heterogeneous scenarios. Therefore, this thesis aims at solving these challenges by proposing a low overhead and application-oriented synchronization in heterogeneous IoT systems.

Therefore, this thesis aims at solving these challenges by proposing a low overhead and application-oriented synchronization in heterogeneous IoT systems. First, a low-overhead data synchronization scheme is proposed to achieve accurate temporal consistency to data collected from the distributed IoT devices. To be more specific, each sensor device is given a task period to provide the sampled data to the sink node (SN). The clock parameters can be precisely estimated so that the misalignment of the data can be adjusted by comparing the difference between the specified period and the actual observed one.

Next, a situation-aware hybrid time synchronization protocol is designed based on multi-source timestamping uncertainty modeling and integrated time information exchange mechanism for heterogeneous IoT systems. By investigating the influence of the multi-faceted operating conditions, the multi-source timestamping errors inherent in the entire synchronization process is correctly estimated. By observing the uncertainties in real-time timestamping, a hybrid time synchronization with an integrated time information sharing mechanism is realized, which could accomplish optimal synchronization strategy for clock parameters estimation.

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