{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:22:44Z","timestamp":1783009364287,"version":"3.54.5"},"reference-count":30,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,5,31]],"date-time":"2021-05-31T00:00:00Z","timestamp":1622419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Bluetooth Low Energy (BLE), a short-range and low-power communication protocol, has gained a lot of popularity in recent years. A part of BLE is the Generic Attribute Profile (GATT) which defines the data communication between two devices. During the initial connection between two BLE devices a discovery of services, characteristics and descriptors is required for the GATT to operate. During this discovery phase, the device is unusable as it builds the foundation for further data transactions. When unoptimized, this discovery step can take up to a few seconds, leading to frustrations for the end user or delays in some applications. In this paper, we aim to find guidelines on how to optimize this discovery process. A simulation framework was developed, able to simulate and analyze the packet exchange of the service discovery, while taking link layer parameters into account. The results show that minimizing the connection interval and maximizing the data length leads to the lowest discovery times. Practical experiments in real environment, however, show that the theoretically calculated times are not reachable due to processing overhead and retransmissions. Theoretical results also show that the current BLE discovery process, even after optimizations, has a lot of overhead. To fix the problems with the current protocol, this paper proposes a new Rapid Service Discovery Protocol, which enables a fast and efficient service discovery.<\/jats:p>","DOI":"10.3390\/s21113812","type":"journal-article","created":{"date-parts":[[2021,5,31]],"date-time":"2021-05-31T21:42:06Z","timestamp":1622497326000},"page":"3812","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Optimizing the Bluetooth Low Energy Service Discovery Process"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4150-4144","authenticated-orcid":false,"given":"Kristof","family":"T\u2019Jonck","sequence":"first","affiliation":[{"name":"M-Group, imec-DistriNet, Department of Computer Science, KU Leuven Bruges Campus, 8200 Bruges, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6709-8813","authenticated-orcid":false,"given":"Bozheng","family":"Pang","sequence":"additional","affiliation":[{"name":"M-Group, imec-DistriNet, Department of Computer Science, KU Leuven Bruges Campus, 8200 Bruges, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2623-9055","authenticated-orcid":false,"given":"Hans","family":"Hallez","sequence":"additional","affiliation":[{"name":"M-Group, imec-DistriNet, Department of Computer Science, KU Leuven Bruges Campus, 8200 Bruges, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7902-8537","authenticated-orcid":false,"given":"Jeroen","family":"Boydens","sequence":"additional","affiliation":[{"name":"M-Group, imec-DistriNet, Department of Computer Science, KU Leuven Bruges Campus, 8200 Bruges, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Lee, J.S., Su, Y.W., and Shen, C.C. 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