A Self-Configurable Edge Computing for Industrial IoT
S. Chandramohan1, M. Senthilkumaran2
1S. Chandramohan, Department of Electronics and Communication Engineering, Sri Chandrasekharendra Viswa Mahavidyalaya, SCSVMV Deemed to be University, Kanchipuram, INDIA.
2M. Senthilkumaran, Department of Computer Science and Engineering, Sri Chandrasekharendra Viswa Mahavidyalaya, SCSVMV Deemed to be University, Kanchipuram, INDIA.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 2890-2894 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3868129219/2019©BEIESP | DOI: 10.35940/ijeat.B3868.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The proliferation of Industrial Internet of Things (IIoT) introduces the concept of a smarter production environment. The emerging technologies like software defined network (SDN), IIoT and cloud computing will bring great advancements in the modern industrial revolution called Industry 4.0. Therefore, with the rapid development of IIoT technology, the proposed work incorporates with Edge Computing (EC). The current manufacturing process and automation, computing and wireless network reaches out to headways in innovation from easy to the point where all things (devices) and machines can interface through an Internet of Everything (IoE). This paper extends the work carried out in traditional methods, by integrating the cloud layer, Automatic Guided Vehicles (AGV), Industrial Wireless networks (IWN) and Industrial robots through EC is conferred to make autonomous decision-making capabilities. EC is emerging as a significant element in the smart industry to bring legacy in the context of Industrial IoT (IIoT). Finally, our proposed framework demonstrates that the active RFID-enabled AGV and industrial robots are brought in to exploit for effective resource management under the EC-based IIoT architecture, subsequently, it improves the conveyor efficiency and overall energy consumption in the warehouse for material handling.
Keywords: IoE, Edge Computing, Industrial Robot, AGV, Active RFID and IIoT.