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Wireless Sensor Networks (WSN), consisting of a large number of sensor nodes connected through wireless medium has emerged as a ground-breaking technology that offers the unprecedented ability to monitor the physical world accurately. Because of resource-constrained nature of sensor nodes, a number of issues have emerged out of which energy-efficiency is an important matter of concern. In this work, we propose an energy-efficient routing scheme called Enhanced Energy-Efficient Protocol with Static Clustering (E 3 PSC) which is basically a modification of an existing routing scheme, Energy-Efficient Protocol with Static Clustering (EEPSC). Similar to EEPSC, the present work partitions the network into distance-based static clusters. However, unlike EEPSC, cluster-head selection is performed by taking into account both the spatial distribution of sensors nodes in network and their residual energy with an objective to reduce the intra-cluster communication overhead among the nodes making the scheme more energy-efficient. Both qualitative and quantitative analysis is performed to establish our claim of energy efficiency of the proposed scheme. A set of experiments is carried out to evaluate the performance of the scheme and to compare the results with EEPSC. Based on our experimental results, it has been found that E 3 PSC outperforms EEPSC in terms of network lifetime and energy consumption.

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The advent of Industrial IoT (IIoT) along with Cloud computing has brought a huge paradigm shift in manufacturing industries resulting in yet another industrial revolution, Industry 4.0. Huge amounts of delay-sensitive data of diverse nature are being generated which needs to be locally processed and secured due to its sensitivity. But, the low-end IoT devices are unable to handle huge computational overheads. Also, the semitrusted nature of Cloud introduces several security concerns. To address these issues, this work proposes a secure Fog-based IIoT architecture by suitably plugging a number of security features into it and by offloading some of the tasks judiciously to fog nodes. These features secure the system alongside reducing the trust and burden on the cloud and resource-constrained devices respectively. We validate our proposed architecture through both theoretical overhead analysis and practical experimentation including simulation study and testbed implementation.