IoT based systems are error-prone and fragile, leading to the creation of faults in the entire network, causing misbehaviour many times. Many types of faults do happen within IoT networks due to the node, link, protocol conversion, and communication failures. Failures can happen due to malfunctioning of hardware and software installed into the devices. Among all network failures due to failure of nodes or links are more serious. A network topology which considers alternate links and redundant devices greatly improves the reliability of an IoT network. An IoT network as such, built through different inter-linked layers which include Device, controller, restful services, gateway, internet and storage, and computing layers. Most of the studies in the literature have considered single topology generally hierarchical for connecting devices situated in different layers. The fault tolerance level of an IoT network dependent on the topology used as many issues such as alternate paths for communication, use of redundancy, and many such factors considered while building a network. A single computational model normally used for computing the fault tolerance level of an IoT network. Sometimes the fault tolerance computing model chosen may not suit the topology used for building a network for a specific layer within an IoT network. Use of different topologies suiting a sub-network in a layer and choice of different fault-tolerance computing models will help accurately determine the fault tolerance level of an IoT network. In this paper, a Fault computing model that considers different topologies for developing sub-nets in different layers and computing models suited to a specific topology presented. The improvement in the fault tolerance of an IoT network achieved through consideration of two topologies, which include hierarchical and butterfly networks presented in this paper.
CITATION STYLE
JKR, S. (2020). Enhancing Fault Tolerance of IoT Networks within Device Layer. International Journal of Emerging Trends in Engineering Research, 8(2), 491–509. https://doi.org/10.30534/ijeter/2020/37822020
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