An energy-efficient data management scheme for industrial IoT

Industry 4.0 is the emerging trend of manufacturing technologies towards smart factories. The industrial internet of things (IIoT) plays a primordial role to achieve the objectives of Industry 4.0, by enabling the cyber-physical production systems to communicate and cooperate with each other and with humans both internally and across the participants of the supply chain. The Publish/Subscribe is the communication model used commonly in IIoT networks, in which the data generated by sensors are cached in a central controller to be subsequently consumed by actuators. However, the traditional centralized data management is inappropriate for real applications because of its communication overhead and inability to cope with strict delay requirements of IIoT applications and energy constraints of IIoT networks. To address these issues, we propose an energy-efficient data management scheme (EDMS), in which a set of IoT nodes are selected to cache data distributedly, so that the network energy consumption is optimized while the constraints on data access latency and nodes' cache capacity are met. In this measure, the extra IoT nodes not involved in data transmission nor in data caching are switched off to prolong the network lifetime. We model the aforementioned optimization problem as an integer linear programming (ILP) considering the realistic constraints and characteristics of IIoT networks and solve it using the CPLEX tool. Moreover, we propose a metaheuristic algorithm based on ant colony optimization to solve the aforementioned problem in a timely manner. Simulation results show that EDMS outperforms significantly alternative solutions in terms of energy consumption, data latency, and cache utilization.