• Title/Summary/Keyword: Grid Coordinator

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A Bio-inspired Hybrid Cross-Layer Routing Protocol for Energy Preservation in WSN-Assisted IoT

  • Tandon, Aditya;Kumar, Pramod;Rishiwal, Vinay;Yadav, Mano;Yadav, Preeti
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1317-1341
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    • 2021
  • Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

Design and Implementation of Factory Equipment Monitoring System using Grid-based Key Pre-Distribution (그리드 기반 키 선분배 방식을 사용하는 공장 설비 모니터링 시스템 설계 및 구현)

  • CHO, YANGHUI;PARK, JAEPYO;YANG, SEUNGMIN
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.11
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    • pp.51-56
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    • 2016
  • In this paper, we propose an Arduino-based plant monitoring system. The proposed system is based on the Arduino platform, using an environmental sensor and a pressure sensor for measuring temperature, humidity and illuminance in order to monitor the state of the environment and the facilities of the plant. Monitoring data are transmitted to a ZigBee coordinator connected to a server through a radio frequency transceiver. When using a pressure sensor and the environment sensor data stored on the host server, checking the pressure in the environment of the plant and equipment is intended to report any alarm status to the administrator. Using a grid line-based key distribution scheme, the authentication node dynamically generates a data key to protect the monitoring information. Applying a ZigBee wireless sensor network does not require additional wiring for the actual implementation of a plant monitoring system. Possible working-environment monitoring of an efficient plant can help analyze the cause of any failure by backtracking the working environment when a failure occurs. In addition, it is easy to expand or add a sensor function using the Arduino platform and an expansion board.