Internet of Things (IoT) with edge computation enhances efficiency, safety, and availability of an industrial automation system. However, there is a continued effort to increase the reliability of the system with minimal downtime. This can be achieved through a modular, re-configurable, and integrable system design approach. In this paper, we propose Pro-Edge, a programmable edge network to reconfigure different services associated with industrial applications and networks. Pro-Edge employs programmable layers at the edge for re-configuring the sensor/actuator network and applications. The lowermost layer allows to reconfigure the communication related parameters and the middle layer consists of a Software-Defined Network (SDN) controller that can dynamically program different modules, handling actuation decisions from the edge. An interfacing protocol between the layers is proposed to provide reliability by considering the optimal configuration parameters among the layers. As a top-layer, a priority forwarding mechanism is designed for SDN core communication in case the sensor and actuator are in different edges. Pro-Edge significantly improves the actuation-latency and is highly energy efficient compared to the existing state-of-the-art.

Due to the multi-hop, long-distance, and wireless backbone connectivity, provisioning critical and diverse services face challenges such as low latency and reliability. This paper proposes ioFog, an offline fog architecture for achieving reliability and low latency in a large backbone network. Our solution uses a Markov chain-based task prediction model to offer dynamic service requirements with minimal dependency on the Internet. The proposed architecture considers a central Fog Controller (FC) to (i) provide a global status overview and (ii) predict upcoming tasks of Fog Nodes for intelligent offloading decisions. The FC also has the current status of the existing fog nodes in terms of their processing and storage capabilities. Accordingly, it can schedule the possible future offline computations and task allocations. ioFog considers the requirements of individual IoT applications and enables improved fog computing decisions. As compared to the existing offline IoT solutions, ioFog improves service time significantly and service delivery ratio up to 23%.

IEEE 802.11ah is considered as a promising and scalable solution for connecting a large number of drones. With the support of sub-1GHz channel bands, relay, and group-based channel access mechanism, 802.11ah can help drone stations for collecting commands, sending data, and processing response to the control room. However, achieving required throughput and latency is still challenging due to high mobility and dynamic relaying requirement. This article proposes an IEEE 802.11ahbased Internet-of-Drones (IoD) architecture for surveillance and remote control. Our scheme predicts the location of a drone and places the required association and channel access configuration to a relay node dynamically. Moreover, the current mode of a drone station is switched to relay from station as per the location. The relay nodes use transmission opportunity (TXOP) with implicit acknowledgement to increase the efficiency of the network. The performance analysis shows significant improvement in terms of throughput and latency.