Modeling middleware platform for supporting communication between IoT devices

Internet of Things (IoT) applications consists of diverse Things including both resource-constrained/rich devices with a considerable portion being mobile. Such devices demand lightweight, loosely coupled interactions in terms of time, space, and synchronization. IoT middleware protocols support one...

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Bibliographic Details
Main Author: Fakhri, Marwan Najm
Format: Thesis
Language:English
English
English
Published: 2019
Subjects:
Online Access:http://eprints.uthm.edu.my/555/1/24p%20MARWAN%20NAJM%20FAKHRI.pdf
http://eprints.uthm.edu.my/555/2/MARWAN%20NAJM%20FAKHRI%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/555/3/MARWAN%20NAJM%20FAKHRI%20WATERMARK.pdf
http://eprints.uthm.edu.my/555/
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Summary:Internet of Things (IoT) applications consists of diverse Things including both resource-constrained/rich devices with a considerable portion being mobile. Such devices demand lightweight, loosely coupled interactions in terms of time, space, and synchronization. IoT middleware protocols support one or more interaction types (e.g., asynchronous messaging, streaming) ensuring Thing communication. This work provides a sensor abstract layer, a system layer and an interaction layer. These enable integrated sensing device operations, efficient resource management, and active interconnection between peripheral IoT devices. In addition, this work provides a high-level API to develop IoT devices easily for IoT device developers. We aim to enhance the energy efficiency and performance of IoT devices through the performance improvements offered by this work resource management and request processing. The main contribution of this thesis is to introduce an approach and provide a supporting platform for the automated synthesis of interoperability software artifacts. Such artifacts enable the interconnection between mobile Things that employ heterogeneous middleware protocols. Our platform further supports evaluating the effectiveness of the interconnection in terms of end-to-end QoS. More specifically, we derive formal conditions for successful interactions, and we enable performance modeling and analysis as well as end-to-end system tuning, while considering several system parameters related to the mobile IoT.