Privacy and security are the key issues in Industrial Wireless Sensor Networks (IWSN) as the wireless sensor nodes are typically deployed in a hostile environment (i.e., in a remote location where minimum or no human intervention is required) and can be easily compromised by an attacker. Several protocols have been proposed to address these issues. However, none of them can fulfill the required privacy and security goals. Additionally, the traditional network architecture presents a performance bottleneck due to the rapidly increasing traffic volume and heterogeneous sensor nodes. Hence, the existing architecture needs to be upgraded accordingly. In this article, we propose a Software-Defined Networking (SDN)-based authentication protocol for real-time data transfer in IWSN, called SDIWSN. SDIWSN puts the management and control functions of the network into a set of logically centralized SDN controllers, thus providing a global view of the network. SDIWSN achieves several privacy and security requirements such as anonymity, unlinkability, mutual authentication, key agreement, forward secrecy and robustness against passive and active attacks. Moreover, SDIWSN provides a simple velocity-based strategy to detect cloning attacks. We validate the privacy and security features of SDIWSN using formal and informal verification. Finally, the efficiency of SDIWSN is measured through a performance-based comparison.

We propose a novel scheme for multi-path routing in a Cognitive Radio Network (CRN) for multimedia communication, even when a contiguous band of required width is not available for any hop in the route. The proposed scheme is based on an extension of the idea of Sample Division Multiplexing (SDM) as given in [1] for single-hop communication. Starting from the source node, we first explore the available (free) number of channels (not necessarily contiguous) between every pair of 1-distance neighbor nodes by the help of appropriate control messages. With the information gathered from this step, the network graph G is constructed. We run the max-flow algorithm [8] on this network graph to find the set of routes between the source and the destination nodes so that the sum total of the usable numbers of channels through all these routes is equal to the required number of channels for the multimedia signal to be communicated. In essence, each data packet of the multimedia signal is split into several sub-packets following the basic concept given in [1] each of which needs much smaller bandwidth than the original packet, and these sub-packets are sent through all these routes to be eventually received by the destination node with the desired QoS. The time complexity of our proposed algorithm for this route discovery is O(pf + TSD), where p is the number of edges in the network graph (G), f is the maximum flow in G and TSDis the initialization time for constructing the network graph. We have shown that TSDis O(Δδmax), where Δ is the diameter and δmaxis the maximum node degree of the network graph.