Research Article
Collision Mitigation algorithm for tracking of RFID based assets in Defence
@ARTICLE{10.4108/eai.9-3-2021.168963, author={C. Hema and Sharmila Sankar}, title={Collision Mitigation algorithm for tracking of RFID based assets in Defence}, journal={EAI Endorsed Transactions on Energy Web}, volume={8}, number={36}, publisher={EAI}, journal_a={EW}, year={2021}, month={3}, keywords={RFID, Reader Collision, Tag Collision, Cuckoo Search based Clustering Protocol, Linear Classifier, Hill Climbing}, doi={10.4108/eai.9-3-2021.168963} }- C. Hema
Sharmila Sankar
Year: 2021
Collision Mitigation algorithm for tracking of RFID based assets in Defence
EW
EAI
DOI: 10.4108/eai.9-3-2021.168963
Abstract
INTRODUCTION: Asset tracking plays a crucial role in Military warehouses, deploying RFID system will be beneficial. When an RFID reader scans multiple tags in the Military warehouse, the missing tags and redundant tag problem occurs due to the signal interferences. To overcome these issues of missing tags and redundant tags, we proposed Cuckoo Search-based Clustering Protocol (CSCP) followed by linear classifier algorithm.
OBJECTIVES: The primary objective of this paper is reducing the collision problems in military warehouse.
METHODS: In this paper, we propose Cuckoo Search-based Clustering Protocol (CSCP), where cluster heads deleteduplicate data and sends processed data to the base station, Later the TDMA-based graph colouring technique is implemented to prevent reader collision issues in the RFID network. The Linear Classifier algorithm first separates similar data for classification, which in turn reduces the collision occurrence of missing tags and redundant tags.
CONCLUSION: In the RFID deployed military warehouse, cluster head readers are selected, and clusters are created. Readers are scheduled to read information from tags in the cluster using the TDMA-based graph coloring algorithm. The linear classifier algorithm classifies the weapon’s data and filters the redundant weapon’s data in RFID deployed military environment.
Copyright © 2021 C. Hema et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.
