Comparative Studies on Intelligent Swarming Network (iSWAN) Geno-Generative Algorithm and Top-K Query Processing Algorithm

Authors

  • Nlerum Promise Anebo  Computer Science and Informatics Department, Federal University Otuoke, Bayelsa State, Nigeria
  • Obasi Emmanuela C. M   Computer Science and Informatics Department, Federal University Otuoke, Bayelsa State, Nigeria

DOI:

https://doi.org/10.32628/CSEIT23903140

Keywords:

Geno-generative, database Intelligent Swarming Network (iSWAN) Geno-Generative Model, sensor, swarm, Top-k

Abstract

This paper proposed an enhanced Top-k query processing in a real time distributed database system. The system employs a Particle Swarm Optimizer (PSO) based Geno-Generative iSWAN Model technique that enhances and allows multi-task concurrent query processing in a real time co-simulation data acquisition platform and as part of refinement to an existing Top-k query processing Technique. In this paper, the proposed system is compared for efficiency with the Top-K Query Algorithm, which is emerging as an alternative to more conventional technique for real time query processing in distributed databases. Dynamic simulations were performed with a real time small testbed comprising of physical and non-physical devices to test and evaluate the performance and efficiency of the two systems. Considering the estimated and expected temperatures, the result of simulation study proves that the Intelligent Swarming Network (iSWAN) Geno-Generative Model is more preferred over Top-K Query Algorithm due to its 70% accuracy over the Top-K Model, which reported a lower accuracy level of 40%.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-06-30

Issue

Volume 9, Issue 3, May-June-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Nlerum Promise Anebo, Obasi Emmanuela C. M , " Comparative Studies on Intelligent Swarming Network (iSWAN) Geno-Generative Algorithm and Top-K Query Processing Algorithm" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 3, pp.581-594, May-June-2023. Available at doi : https://doi.org/10.32628/CSEIT23903140