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Evolutionary computation approach for spatial workload balancing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

The growing demand for Geographic Information Systems (GIS) calls for high computation reliability to handle vast and complex spatial data processing tasks. A better parallel computing scheme should ensure balanced workload at different data processors to ensure optimal use of computing resources and minimise execution times, which poses more challenges with spatial data due to the nature of having spatial correlations and uneven distributions. In this paper, we propose a spatial clustering approach for workload balance, by using an evolutionary computation method that considers the nature of spatial data, to increase the computation performance for processing GIS polygon-based maps
with massive number of vertices and complex shapes. To evaluate our proposed approach, We proposed two different experimental approaches for comparing our results: (i) Non{merging based experiment, and (ii) merging based experiment. The results demonstrated the advantage of the proposed spatial clustering approach in real GIS map based partitioning scenarios. The advantages and limitations of the proposed approach are discussed and further research directions are highlighted toward a development work by the research community.
Original languageEnglish
Title of host publicationProceedings of the Computing Conference 2021
PublisherSpringer
Publication statusAccepted for publication - 4 Dec 2020
EventComputing Conference 2021 - London, United Kingdom
Duration: 15 Jul 202116 Jul 2021
https://saiconference.com/Computing

Conference

ConferenceComputing Conference 2021
CountryUnited Kingdom
CityLondon
Period15/07/2116/07/21
Internet address

Documents

  • SAI_Computing_Conference_2021

    Rights statement: The embargo end date of 2050 is a temporary measure until we know the publication date. Once we know the publication date the full text of this article will be able to view shortly afterwards.

    Accepted author manuscript (Post-print), 1.33 MB, PDF document

    Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 1/01/50

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