Manchester Metropolitan University's Research Repository

Energy Efficiency in Green Internet of Things (IoT) Networks

Farhan, Laith Kadhim (2020) Energy Efficiency in Green Internet of Things (IoT) Networks. Doctoral thesis (PhD), Manchester Metropolitan University.

Restricted to Repository staff only until 26 November 2020.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

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Internet of Things (IoT) is having a major impact on the digital world and how we interact with the internet. The wireless sensor network (WSN) is a promising wireless communication system for enabling IoT networks. But these networks have limited energy (battery) resources and energy-saving has become a pressing need in such networks and there have been increasing efforts to minimise energy consumption via message scheduling, optimal routing, clustering formation, aggregation techniques, etc. However, significant improvement is still required and this study has produced algorithms which have been shown to reduce energy consumption and prolong network life. Increasing the number of neighbour nodes around a node has a negative impact on the network lifetime of WSNs. This is due to the adverse effects caused by overhearing and interference. This thesis presents a new routing technique that considers the transmission distances from one node to all neighbouring nodes within its transmission range. The interference measurement approach is adopted to select the next-hop node. The cluster head (CH) node selection is based on transmission distances to the base station (BS) with the nearest node to the BS in a sub-cluster elected as CH node for that sub-cluster. The thesis also introduces a novel scheduling algorithm called the “long hop” (LH) which assigns high priority to messages coming from sensor nodes that are located farthest away and have accessed a high number of hops, to be served first at CH nodes. This minimised energy consumption caused by the retransmission process. Redundant data increases the unnecessary/unwanted processing and transmission of data. Thus, the thesis introduces a new method that reduces redundant data transmission and lowers the communication costs related to sending unnecessary data. The study also provides a remote monitoring system for the end-user that can check and track the performance of the sensors/IoT devices during real-time communication. Extensive simulation tests on randomly situated WSNs show the potential of the solutions proposed in this thesis to reduce energy consumption and extend network lifetime.

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