A Green Data Management Layer in Industrial IoT. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Ghaderi, A; Qavany, Z; Movahedi, Z
• Is Part Of: IOP conference series. Volume 1067:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Industry 4.0 -- Industrial IoT -- Data Management -- Energy Efficiency -- Green Manufacturing; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1067/1/012131
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: All Nowadays, industry 4.0, which aims at transforming industrial manufacturing systems to the smart factories, has gained considerable attention from both industry and academia. 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 (CPPS) to communicate and cooperate with each other and with humans both internally and across the participants of the supply chain. A communication model used commonly in IIoT networks consists of the publish-subscribe model, in which the data generated by sensor nodes are cached in a central controller to be subsequently consumed by actuator nodes. However, the traditional centralized data management is inappropriate for real application 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 a Green Data Management Layer (GDML), which caches data distributedly in some IoT nodes, called proxy nodes, so that the network energy consumption is optimized while the constraints on data access latency and IoT 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 battery lifetime of constrained IoT nodes. We modeled the aforementioned optimization problem as an Integer Linear Programming (ILP) and solved it using the CPLEX tool. The obtained results show that the proposed GDML outperforms significantly alternative solutions in terms of overall energy consumption, energy consumption devoted to data transmission, energy consumption devoted to keeping active the involved nodes, while the constraints on data applications latency and the cache size of IoT nodes are satisfied.