{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T10:33:52Z","timestamp":1762079632623,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,12,6]],"date-time":"2022-12-06T00:00:00Z","timestamp":1670284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010041","name":"Tianjin Natural Science Foundation","doi-asserted-by":"publisher","award":["18JCYBJC84900"],"award-info":[{"award-number":["18JCYBJC84900"]}],"id":[{"id":"10.13039\/501100010041","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Tiled maps are one of the key GIS technologies used in the development and construction of WebGIS in the era of big data; there is an urgent need for high-performance tile map services hosted on big data GIS platforms. To address the current inefficiency of massive tile map data management and access, this paper proposes a massive tile map data access model that utilizes the jump consistent hash algorithm. Via the uniformity and consistency of a certain seed of a pseudo-random function, the algorithm can generate a storage slot for each tile data efficiently. By recording the slot information in the head of a row key, a uniform distribution of the tiles on the physical cluster nodes is achieved. This effectively solves the problem of hotspotting caused by the monotonicity of tile row keys in the data access process, thereby maximizing the random-access performance of a big data platform and greatly improving concurrent database access. Experiments show that this model can significantly improve the efficiency of tile map data access by more than 39% compared to a direct storage method, thereby confirming the model\u2019s advantages in accessing massive tile map data on a big data GIS platform.<\/jats:p>","DOI":"10.3390\/ijgi11120608","type":"journal-article","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T04:00:37Z","timestamp":1670385637000},"page":"608","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Map Tile Data Access Model Based on the Jump Consistent Hash Algorithm"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2564-8826","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"College of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300391, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9745-3150","authenticated-orcid":false,"given":"Xiaojing","family":"Yao","sequence":"additional","affiliation":[{"name":"The Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300391, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.jmsy.2022.06.015","article-title":"Digital twin modeling","volume":"64","author":"Tao","year":"2022","journal-title":"J. Manuf. Syst."},{"key":"ref_2","first-page":"1","article-title":"On Geospatial Information Science in the Era of IoE","volume":"51","author":"Li","year":"2022","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.cirpj.2020.02.002","article-title":"Characterising the Digital Twin: A systematic literature review","volume":"29","author":"Jones","year":"2020","journal-title":"CIRP J. Manuf. Sci. Technol."},{"key":"ref_4","first-page":"2","article-title":"Development and Prospect of GIS Platform Software Technology System","volume":"23","author":"Song","year":"2021","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_5","first-page":"641","article-title":"Big Data GIS","volume":"39","author":"Li","year":"2014","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2153","DOI":"10.11834\/jrs.20210480","article-title":"Big Geodata Aggregation: Connotation, Classification, and Framework","volume":"25","author":"Pei","year":"2021","journal-title":"Natl. Remote Sens. Bull."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"110755","DOI":"10.1016\/j.rser.2021.110755","article-title":"A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities","volume":"140","author":"Kim","year":"2021","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_8","first-page":"120","article-title":"Key Technologies and Application Exploration of Aerospace Big Data in the Construction of New Smart City","volume":"8","author":"Shi","year":"2022","journal-title":"Big Data Res."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ramzan, S., Bajwa, I.S., and Kazmi, R. (2019). Challenges in NoSQL-Based Distributed Data Storage: A Systematic Literature Review. Electronics, 8.","DOI":"10.3390\/electronics8050488"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1587\/transinf.2017DAP0017","article-title":"G-HBase: A High Performance Geographical Database Based on HBase","volume":"E101.D","author":"Van","year":"2018","journal-title":"Ieice Trans. Inf. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2931","DOI":"10.1016\/j.procs.2021.09.065","article-title":"An improved tile-based scalable distributed management model of massive high-resolution satellite images","volume":"192","author":"Hajjaji","year":"2021","journal-title":"Procedia Comput. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Shen, B., Liao, Y.C., Liu, D., and Chao, H.C. (2018). A method of hbase multi-conditional query for ubiquitous sensing applications. Sensors, 18.","DOI":"10.3390\/s18093064"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6483","DOI":"10.1007\/s10586-018-2270-4","article-title":"An extra spatial hierarchical schema in key-value store","volume":"22","author":"Zheng","year":"2019","journal-title":"Clust. Comput."},{"key":"ref_14","first-page":"74","article-title":"Design and Implementation of Cloud Storage System for Map Tiles Based on Hadoop","volume":"42","author":"Yu","year":"2017","journal-title":"J. Geomat."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wang, X., Sun, Y., Sun, Q., Lin, W.W., Wang, J.Z., and Li, W. (2022). HCIndex: A Hilbert-Curve-based clustering index for efficient multi-dimensional queries for cloud storage systems. Clust. Comput., 1\u201315.","DOI":"10.1007\/s10586-022-03723-y"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"47580","DOI":"10.1109\/ACCESS.2020.2979250","article-title":"MI-HCS: Monotonically increasing Hilbert code segments for 3D geospatial query window","volume":"8","author":"Wu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.cageo.2019.06.003","article-title":"GeoBeam: A distributed computing framework for spatial data","volume":"131","author":"He","year":"2019","journal-title":"Comput. Geosci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"30","DOI":"10.3389\/fdata.2020.00030","article-title":"LocationSpark: In-memory Distributed Spatial Query Processing and Optimization","volume":"3","author":"Tang","year":"2020","journal-title":"Front. Big Data"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Baig, F., Vo, H., Kurc, T., Saltz, J., and Wang, F. (2017, January 7\u201310). SparkGIS: Resource Aware Efficient In-Memory Spatial Query Processing. Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA.","DOI":"10.1145\/3139958.3140019"},{"key":"ref_20","first-page":"24","article-title":"Research on Spark-based Real-time Query of Spatial Data","volume":"6","author":"Fang","year":"2015","journal-title":"Geomat. World"},{"key":"ref_21","first-page":"1584","article-title":"Design of Secondary Indexes in HBase Based on Memory","volume":"38","author":"Cui","year":"2018","journal-title":"J. Comput. Appl."},{"key":"ref_22","first-page":"132","article-title":"Research and Implementation of the Temporal Map Tile Data Storage Model Based on NoSQL Database","volume":"43","author":"Wang","year":"2020","journal-title":"Geomat. Spat. Inf. Technol."},{"key":"ref_23","unstructured":"(2022, November 18). Web Map Tile Service Implementation Standard. Available online: https:\/\/www.ogc.org\/standards\/wmts."},{"key":"ref_24","first-page":"144","article-title":"Research and Practice of Tiles Pyramid Model Technology","volume":"37","author":"Huo","year":"2012","journal-title":"Sci. Surv. Mapp."},{"key":"ref_25","first-page":"9","article-title":"The Research of Key Technologies for The Tile Map in WebGIS","volume":"2","author":"Xuming","year":"2012","journal-title":"Beijing Surv. Mapp."},{"key":"ref_26","unstructured":"Ying, X., and Yang, X. (2012). Remote Sensing Image Data Storage and Search Method Based on Pyramid Model in Cloud. International Conference on Rough Sets & Knowledge Technology, Springer."},{"key":"ref_27","first-page":"116","article-title":"Spatio-temporal Block Index for Traffic Data Based on HBase","volume":"12","author":"Jia","year":"2019","journal-title":"Inf. Technol."},{"key":"ref_28","first-page":"163","article-title":"Geo-spatial Big Data Storage Based on NoSQL Database","volume":"42","author":"Li","year":"2017","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_29","unstructured":"Lamping, J., and Veach, E. (2014). A Fast, Minimal Memory, Consistent Hash Algorithm. arXiv, Available online: https:\/\/arxiv.org\/ftp\/arxiv\/papers\/1406\/1406.2294.pdf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1365815.1365816","article-title":"Bigtable: A Distributed Storage System for Structured Data","volume":"26","author":"Chang","year":"2008","journal-title":"ACM Trans. Comput. Syst."},{"key":"ref_31","unstructured":"(2022, November 18). Apache HBase Reference Guide. Available online: https:\/\/hbase.apache.org\/book.html#rowkey.design."},{"key":"ref_32","unstructured":"(2022, November 22). Design Principles for HBase Key and Rowkey. Available online: https:\/\/ajaygupta-spark.medium.com\/design-principles-for-hbase-key-and-rowkey-3016a77fc52d."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Huang, J., Zhao, J., Guo, Y., Mao, X., and Wang, J. (2021, January 26\u201329). The Application on Distributed Geospatial Data Management Based on Hadoop and the Application in WebGIS. Proceedings of the 2021 9th International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Shenzhen, China.","DOI":"10.1109\/Agro-Geoinformatics50104.2021.9530350"},{"key":"ref_34","first-page":"178","article-title":"The Design and Verification of Row Key in HBase Database","volume":"18","author":"Li","year":"2019","journal-title":"Softw. Guide"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/12\/608\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:34:59Z","timestamp":1760146499000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/12\/608"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,6]]},"references-count":34,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["ijgi11120608"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11120608","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2022,12,6]]}}}