In this paper, we propose an energy-aware routing algorithm and a control overhead reduction technique for prolonging the network lifetime of software-defined multihop wireless sensor networks (SDWSNs). This is an effort to optimize the energy consumption of WSNs that provide services to the Industrial Internet of Things (IIoT). A centralized controller grants a global view of the sensor network by introducing extra control overhead in the network, but this leads to extra energy costs. However, our new algorithm takes advantage of this global view and balances the network energy by selecting paths with the highest remaining energy level among multiple paths for each sensor node. We also identify key functions draining energy from the SDWSN and minimize their impact by implementing a data packet aggregation function, and minimizing the control overhead by keeping track of the sensor nodes' routing tables using a simple checksum function. We show that the proposed approach prolongs the network lifetime of the WSN by 6.5% on average compared to the standard shortest-path algorithm, and that the control overhead is reduced by approximately 12% while still maintaining a very high packet delivery ratio.

and Turkey. The document reflects only the authors' view, and the Commission is not responsible for any use that may be made of the information it contains. Danish participants are supported by Innovation Fund Denmark under grant agreemet No. 0228-00004A.

The software defined networking framework facilitates flexible and reliable internet of things networks by moving the network intelligence to a centralized location while enabling low power wireless network in the edge. In this paper, we present SD-WSN6Lo, a novel software-defined wireless management solution for 6LoWPAN networks that aims to reduce the management complexity in WSN's. As an example of the technique, a simulation of controlling the power consumption of sensor nodes is presented. The results demonstrate improved energy consumption of approximately 15% on average per node compared to the baseline condition.Index Terms-Wireless sensor networks; Internet of Things; software-defined networking; 6LoWPAN.

In this paper, we propose a model-based characterization of energy consumption in a software-defined wireless sensor network (SD-WSN) architecture in an effort to examine the implications for network performance when making the WSN reprogrammable. The proposed model consists of breaking down all key functions involved in the correct functioning of an SD-WSN, namely; neighbor discovery, neighbor advertisement, network configuration, and data collection. The model is analyzed from a multi-hop network perspective. We consider two static SD-WSN scenarios to examine scalability, and one scenario to assess the performance implications in a pseudo-dynamic SD-WSN. Extensive simulation results are presented regarding the control overhead introduced, the percentage of alive nodes and remaining energy, and the impacts on network lifetime. We show that the accumulated control overhead is inversely proportional to the interaction period with the controller, whereas the remaining energy and the network lifetime are directly proportional to this parameter. Results show that the control overhead, for static SD-WSNs, can take up 10-29% of the total data flowing to the controller for the large SD-WSN and 6-19% for the small SD-WSN. For a pseudo-dynamic network, the control overhead can take up to two-thirds of the total data sent to the controller, and the network lifetime was reduced by up to 80% compared with the static scenarios.