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Sen. Netw."],"published-print":{"date-parts":[[2025,11,30]]},"abstract":"<jats:p>The development of the Internet of Things promotes the increasing demand for edge computing, resulting in a large amount of temporal data. Protecting data from tampering has become key to industrial intelligent management. Blockchain technology has become an ideal choice for ensuring data trustworthiness due to its immutability and other characteristics. However, existing technologies do not provide sufficient support for temporal data. There are still issues such as chaotic data organization, low query efficiency, and insufficient lightweight validation. To address these challenges, we combine the Secure Hash Algorithm\u00a0and Merkle tree to serialize temporal data. We design a temporal Merkle prefix forest on the blockchain cloud main chain and construct an index for intra-block localization. Verification can be completed by monitoring the latest tree, significantly improving query efficiency. For edge-side devices with limited computing resources, we design a temporal Bloom Merkle tree, where lightweight nodes only need to pass the Merkle proof of the root node to verify data integrity. Experimental results demonstrate that our method significantly improves query efficiency and reduces storage requirements, meeting the reliability and lightweight requirements of temporal data management in the Internet of Things.<\/jats:p>","DOI":"10.1145\/3770915","type":"journal-article","created":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T11:10:57Z","timestamp":1759749057000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Lightweighted Blockchain Deploying Method in IoT Systems"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3386-5864","authenticated-orcid":false,"given":"Ruihan","family":"Wang","sequence":"first","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology","place":["Harbin, China"]},{"name":"State Key Laboratory of Smart Farm Technologies and Systems","place":["Harbin, China"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0396-9485","authenticated-orcid":false,"given":"Qi","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology","place":["Harbin, China"]},{"name":"State Key Laboratory of Smart Farm Technologies and Systems","place":["Harbin, China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1263-9907","authenticated-orcid":false,"given":"Siyao","family":"Cheng","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology","place":["Harbin, China"]},{"name":"State Key Laboratory of Smart Farm Technologies and Systems","place":["Harbin, China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5786-0392","authenticated-orcid":false,"given":"Dongbo","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology","place":["Harbin, China"]},{"name":"Department of information engineering, The Chinese University of Hong Kong","place":["Harbin, China"]},{"name":"State Key Laboratory of Smart Farm Technologies and Systems","place":["Harbin, China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6209-6886","authenticated-orcid":false,"given":"Jie","family":"Liu","sequence":"additional","affiliation":[{"name":"AI Research Insititute, Harbin Institute of Technology(Shenzhen)","place":["Shenzhen, China"]},{"name":"State Key Laboratory of Smart Farm Technologies and Systems","place":["Shenzhen, China"]}]}],"member":"320","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"key":"e_1_3_1_2_2","article-title":"An instance segmentation model for strawberry diseases based on mask R-CNN","volume":"21","author":"Afzaal Usman","year":"2021","unstructured":"Usman Afzaal, Bhuwan Bhattarai, Yagya Raj Pandeya, and Joonwhoan Lee. 2021. 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