Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/20191
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dc.contributor.advisorAl-Raweshidy, H-
dc.contributor.advisorLi, M-
dc.contributor.authorAl Atawi, Abdullah-
dc.date.accessioned2020-02-05T10:35:52Z-
dc.date.available2020-02-05T10:35:52Z-
dc.date.issued2018-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/20191-
dc.descriptionThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University Londonen_US
dc.description.abstractThe Internet of the Things (IoT) is evolving rapidly, and its significant impacts are expected to affect many application domains. Challenges in areas that humans have been striving to understand, measure, or predict—such as wildlife, healthcare, or environmental hazards—are likely to be addressed by the time IoT emerges. The underlying elements of IoT are wireless sensor networks (WSNs), which consist of a large number of sensor nodes. In the IoT sphere, sensor nodes represent tangible objects—Things—that monitor changes, collect information, and eventually send it through the Internet to a recipient party. Inherently, however, a wireless sensor node relies on limited computational resources with a limited power source. These undesirable qualities result in a low level of dependability. This research explores the viability of applying the unfolding network programmability concepts to overcome survivability obstacles in WSNs and the IoT. In particular, it examines the viability of software-defined networking (SDN) in network lifetime maximisation, failure detection, and failure recovery problems in WSNs. Software-defined networking is a new network programmability concept that separates the traditionally-tied control and data planes. It offloads the route computations and management from network devices to a logically centralised controller. This separation directly leads to better allocation of computational resources for the network nodes and allows endless orchestration possibilities for the controller. This thesis proposes an SDN-based solution to increase the survivability and resilience of WSN environments. Following an approach that conforms with the centralised nature of SDN environments and considers the limited resources of the WSN. A routing algorithm based on A-star was developed for WSNs, then deployed within an SDN environment to maximise the network lifetime. Apart from finding the path with the lowest energy burden, the algorithm offloads most of the control traffic from sensor nodes to the controller. This algorithm resulted in improved resource utilisation among the nodes due to plane decoupling. Additionally, it increased the lifetime of the network by 22.6% compared to the widely explored LEACH protocol. This thesis also investigates different failure detection and recovery practices in the SDN architecture. The simulation results show that adopting bidirectional forwarding detection (BFD) with the asynchronous echo mode for WSN in an SDN environment reduces control traffic for failure detection to between 27% and 48%. The thesis also evaluates the performance of multiple recovery approaches when adopting the premises of SDN. The simulation results indicate that path protection, using group tables from the OpenFlow protocol, has a recovery time up to eight times shorter than the restoration time. The results of the study reveal that using protection as a failure recovery technique significantly reduces control traffic overhead.en_US
dc.language.isoenen_US
dc.publisherBrunel University Londonen_US
dc.relation.urihttps://bura.brunel.ac.uk/bitstream/2438/20191/1/FulltextThesis.pdf-
dc.subjectIoTen_US
dc.subjectSDNen_US
dc.subjectVirtualizationen_US
dc.subjectWSNen_US
dc.subjectRecoveryen_US
dc.titleA software-defined survivability approach for wireless sensor networks in future internet of the thingsen_US
dc.typeThesisen_US
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Electrical Engineering Theses

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