优化物联网数据聚合:用于提高农业效率的萤火虫-人工蜂群混合算法

Q2 Economics, Econometrics and Finance
Narayanaswamy Venkateswaran, Kayala Kiran Kumar, Kirubakaran Maheswari, Radha Vijaya Kumar Reddy, Sampath Boopathi
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引用次数: 0

摘要

本研究中的数据聚合过程通过混合萤火虫-人工蜂群算法(HFABC)得到了增强,提高了平均数据包交付率、端到端延迟和寿命计算量。在本研究中,HFABC 和多跳 LEACH 是两种用于聚合物联网数据的算法。使用平均端到端延迟、PDR 和网络寿命等评估标准对它们的性能进行了比较。与多跳 LEACH 相比,HFABC 方法能更有效地减少平均端到端延迟,收益率从 2.20% 到 8.66%。这表明它能很好地减少物联网网络中数据传输的延迟时间。HFABC 的改进幅度从 3.45% 到 45.39%,在有效传递数据包方面比多跳 LEACH 成功率更高。HFABC 可将网络寿命延长 0.047% 至 2.286%,这表明它有助于延长物联网网络的运行时间。对于物联网网络中的有效数据聚合,HFABC 是一种出色的解决方案,它能减少延迟、改善数据包交付并延长网络寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing IoT Data Aggregation: Hybrid Firefly-Artificial Bee Colony Algorithm for Enhanced Efficiency in Agriculture
The data aggregation process in this study has been enhanced by the hybrid firefly-artificial bee colony algorithm (HFABC) by increasing the average packet delivery ratio, end-to-end delay, and lifespan computation. In this study, HFABC and Multi Hop LEACH are two algorithms that are used to aggregate IoT data. Their performance is compared using evaluation criteria including average End-to-End Delay, PDR, and network lifetime. The HFABC method reduces average End-to-End Delay more effectively than Multi Hop LEACH, with gains of 2.20 to 8.66 %. This demonstrates how well it works to reduce the lag times for data transfer in IoT networks. With improvements ranging from 3.45% to 45.39%, HFABC has a greater success rate than Multi Hop LEACH in effectively delivering packets. HFABC increases network lifetime by 0.047 to 2.286 percent, indicating that it helps keep IoT networks operating for longer. For effective data aggregation in IoT networks, HFABC is a superior solution that decreases delays, improves packet delivery, and lengthens network lifetime.
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来源期刊
Agris On-line Papers in Economics and Informatics
Agris On-line Papers in Economics and Informatics Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
28
期刊介绍: The international journal AGRIS on-line Papers in Economics and Informatics is a scholarly open access, blind peer-reviewed by two reviewers, interdisciplinary, and fully refereed scientific journal. The journal is published quarterly on March 30, June 30, September 30 and December 30 of the current year by the Faculty of Economics and Management, Czech University of Life Sciences Prague. AGRIS on-line Papers in Economics and Informatics covers all areas of agriculture and rural development: -agricultural economics -agribusiness -agricultural policy and finance -agricultural management -agriculture''s contribution to rural development -information and communication technologies -information and database systems -e-business and internet marketing -ICT in environment -GIS, spatial analysis and landscape planning The journal provides a leading forum for an interaction and research on the above-mentioned topics of interest. The journal serves as a valuable resource for academics, policy makers and managers seeking up-to-date research on all areas of the subject. The journal prefers scientific papers by international teams of authors who deal with problems concerning the focus of our journal in the world-wide scope with relation to Europe.
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