Service-oriented architecture for internet-of-things based home area network
The Internet-of-Thing (IoT) is rapidly expanding year by year in terms of device, network capacity, connectivity, and data traffic in existing and future 5G networks. Among the most prevailing applications of the 5G IoT network is in a smart home setting or a Home Area Network (HAN). However, the cu...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/102816/1/MohdRozainiAbdRahimPSKE2022.pdf.pdf http://eprints.utm.my/id/eprint/102816/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:152227 |
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| Summary: | The Internet-of-Thing (IoT) is rapidly expanding year by year in terms of device, network capacity, connectivity, and data traffic in existing and future 5G networks. Among the most prevailing applications of the 5G IoT network is in a smart home setting or a Home Area Network (HAN). However, the current IoT HAN faces several challenges such as inefficient utilization and management of sensor nodes, lack of interoperability in the heterogeneous sensor nodes, limited applications, and application development dependency. Therefore, there is a need to overcome such limitations to provide multiple applications running on HAN. The objective of this work is to develop a middleware based on a layered model and service-oriented architecture that ensures multiple applications running on efficient HAN. The proposed Service Oriented Home Area Network (SoHAN) middleware is made up of two sublayers called sensor dependent sublayer and service dependent sublayer. The sensor dependent sublayer comprises a task manager and aggregation manager that manage the various sensors’ data and the service dependent sublayer consisting of scheduling manager, Quality of Service (QoS) manager, discovery manager, registry manager, composition manager and Data Distribution Service (DDS) manager handle multiple services that generate multiple applications. The SoHAN middleware was verified using simulation study and justified through implementation of a real testbed network. The simulation study shows that SoHAN generates the same packet rate as Smart Home and Ambient Assisted Living (SHAAL) and on the contrary 74.4% less compared to Ambient Intelligence Web Service Middleware (aWESoME). The result validates that SoHAN middleware uses adequate service packet size to carry multiple sensors’ data that optimize the network throughput and efficiency. The network efficiency was further verified with SoHAN experiencing the least latency. SoHAN experiences 52% and 30% less delay compared to SHAAL and aWESoME respectively. The SoHAN energy consumption is reduced by 34.1% and 47.3% compared to SHAAL and aWESoME respectively. The least Central Processing Unit (CPU) usage means the SoHAN middleware incurs minimum energy usage. The performance of SoHAN middleware has been validated via experimental testbed. The result shows the SoHAN middleware enables low total disk usage and CPU usage by 21.4% and 9.5% respectively compared to without middleware implementation. In brief, the SoHAN middleware provides a significant achievement in terms of interoperability, scalability, reusability, and power efficiency in the IoT based HAN application. |
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