Adaptive Computing Optimization for Industrial IoT using SDN with Edge Computing

In recent years, the rapid growth of industrial Internet of Things (IIoT) introduces the concept of the smart industry under industry 4.0, smart logistics and, smart grid. In the context of industry 4.0, the emerging technologies like network function virtualization, software defined network (SDN), fog computing, and edge computing (EC) will bring great advancements in manufacturing industries. However, a few research are discussed about offloading tasks in edge servers. In smart industries, the IIoT devices generate huge data to communicate among different entities with delays. Therefore, the IIoT system faces the computation offloading issues. To overcome the drawbacks and to improve the quality of service (QoS), the SDN-based energy efficient resource management is proposed for industrial IoT. Moreover, in order to make adaptive computing the proposed method is incorporated with edge computing. Therefore, the SDN-based IIoT architecture with EC outperforms the traditional methods over adaptive computation, effective resource management and latency in industrial wireless networks (IWNs). The simulation results shows that the proposed method corroborate the findings in terms of higher throughput, reduced overall delay and improved success ratio.