Hybrid models for computing fault tolerance of IoT networks

Abstract

Many Internet of Things (IoT) -based networks are being built to develop applications spanning multiple domains. Many small to large devices connected in various ways increases the risk of IoT networks failing. Small devices in the devices layer frequently fail due to their small size and high usage. Intermittent failures of the IoT networks lead to catastrophes at times. The IoT systems must be designed to be fault-tolerant. Fault tolerance of IoT networks must be computable so that the same can be considered while designing IoT networks. However, the computation of fault tolerance of IoT networks is complex, especially when heterogeneous structures are used for building a specific IoT network. Fault tree-based models are not suitable for computing fault-tolerance of complex models, which requires probability assessment. Hybrid fault tolerance computing models have been presented in this paper that consider both linear and probabilistic methods of computing the fault tolerance considering many complex networking topologies used in each layer of IoT networks. The fault-tolerance computing models are formal methods that can be used to compute the fault tolerance of any IoT network built with any internal processing. The accuracy of fault tolerance computing is 12.9% higher than other methods.

Implementing Dual Base Stations within an IoT Network for Sustaining the Fault Tolerance of an IoT Network through an Efficient Path Finding Algorithm

“…A flow diagram depicting the execution of the proposed methods is shown in Figure 1. The blocks relating to metrics development, initial prototype development and its FTA development, implementing a crossbar network in the device layer, implementing fault detection and isolation method in the sensing and actuating devices to counter the possible fault in injection in the device layer and its related FTA model and the improvement in fault tolerance capability of the IoT network were explained by Bhupathi et al [11,42]. Further to the implementations carried out in the device layer, a second base station has been added to the controller layer.…”

“…Bhupathi et al [42] presented different metrics for computing the fault tolerance of the IoT network. They also presented [11] a crossbar network topology to connect the clusters to the cluster heads. Moreover, they implemented a method to predict the fault that a device will inject due to the power depletion rate.…”

“…An IoT network with changes at the device level is presented in Figure 2. The updated IoT system implements the following in the device layers to enhance the fault tolerance of the network [11,42].…”

“…The fault tolerance of an IoT network can be measured in terms of success rate, failure rate, false alarm rate, and power depletion rate [8] and the computation of these metrics. In addition, different computation models are to be used, which include FTA (Fault Tree Analysis) [9] for linear models, probability models [10], hybrid models [11] that combine linear and probability models, empirical model [12], and bipartite flow graph modeling [13].…”

“…For developing a fault tree of the sample IoT network, the crossbar network is replaced by a single device whose success rate is computed using probability models connected with the crossbar network [11]. The success rate of such a network is computed as 0.842.…”