Extraction of abstracted sensory data to reduce the execution time of context-aware services in wearable computing environments
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Y. | - |
dc.contributor.author | Ye, J. | - |
dc.contributor.author | Choi, J. | - |
dc.contributor.author | Choi, J. | - |
dc.contributor.author | Ko, H. | - |
dc.date.available | 2019-05-20T01:40:04Z | - |
dc.date.created | 2019-05-17 | - |
dc.date.issued | 2020-09 | - |
dc.identifier.issn | 1532-0626 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/34725 | - |
dc.description.abstract | Context awareness is a necessary technique for providing optimized services to users by recognizing their surrounding environment at a particular time. To provide context-aware services, a context-aware middleware is required to detect the changes surrounding the user as well as the processing procedure. However, when the context-aware middleware is applied to wearable computing, the processing time increases in proportion to the increase in the number of context information due to the lack of processing capacity from the terminal devices. To access the terminal devices, a specific context representation with Resource Description Framework–based triplet is used. Since the triplet consists of three keyword elements that refer to the status of a given situation around the user, retrieving these elements takes O(n 3 ) time complexity with a linear search. To overcome this problem, a hash-based comparison method is suggested to minimize the response time. The suggested comparison method gives a better performance without searching every single keyword element among the triplet sets. In the experiment, we applied the suggested method to the context-aware workflow middleware and demonstrated that the proposed method improves the processing time by at least 30% compared with the linear search by enhancing the comparison module in the middleware. © 2019 John Wiley & Sons, Ltd. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | John Wiley and Sons Ltd | - |
dc.relation.isPartOf | Concurrency Computation | - |
dc.title | Extraction of abstracted sensory data to reduce the execution time of context-aware services in wearable computing environments | - |
dc.type | Article | - |
dc.identifier.doi | 10.1002/cpe.5286 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | Concurrency Computation , v.32, no.18 SI | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000565246000003 | - |
dc.identifier.scopusid | 2-s2.0-85065021052 | - |
dc.citation.number | 18 SI | - |
dc.citation.title | Concurrency Computation | - |
dc.citation.volume | 32 | - |
dc.contributor.affiliatedAuthor | Choi, J. | - |
dc.contributor.affiliatedAuthor | Choi, J. | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.subject.keywordAuthor | abstracted sensory data | - |
dc.subject.keywordAuthor | context-aware services | - |
dc.subject.keywordAuthor | preprocessing | - |
dc.subject.keywordAuthor | situational information | - |
dc.subject.keywordAuthor | wearable computing | - |
dc.subject.keywordPlus | Abstracting | - |
dc.subject.keywordPlus | Information services | - |
dc.subject.keywordPlus | Middleware | - |
dc.subject.keywordPlus | Wearable sensors | - |
dc.subject.keywordPlus | Context aware services | - |
dc.subject.keywordPlus | preprocessing | - |
dc.subject.keywordPlus | Sensory data | - |
dc.subject.keywordPlus | situational information | - |
dc.subject.keywordPlus | Wearable computing | - |
dc.subject.keywordPlus | Wearable computers | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Soongsil University Library 369 Sangdo-Ro, Dongjak-Gu, Seoul, Korea (06978)02-820-0733
COPYRIGHT ⓒ SOONGSIL UNIVERSITY, ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.