“Time–Location–Frequency”–aware Internet of things service selection based on historical records
The advertised quality of an Internet of things service is not always trustable due to the exaggerated quality propagation and dynamic network environment. Therefore, it is more trustable to evaluate the Internet of things service quality based on the historical execution records of service. However...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147716688696 |
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| _version_ | 1850166425648365568 |
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| author | Lianyong Qi Peiqiang Dai Jiguo Yu Zhili Zhou Yanwei Xu |
| author_facet | Lianyong Qi Peiqiang Dai Jiguo Yu Zhili Zhou Yanwei Xu |
| author_sort | Lianyong Qi |
| collection | DOAJ |
| description | The advertised quality of an Internet of things service is not always trustable due to the exaggerated quality propagation and dynamic network environment. Therefore, it is more trustable to evaluate the Internet of things service quality based on the historical execution records of service. However, an Internet of things service often has multiple historical records whose invocation time and location are different, which makes it necessary to weigh each historical record of an identical Internet of things service. Besides, for different candidate Internet of things services, their invocation frequencies are often varied, which may also affect the final service selection decision of target user. In view of the above two challenges, a novel service selection approach “Time–Location–Frequency”–aware Service Selection Approach is put forward in this article. In Time–Location–Frequency–aware Service Selection Approach, we first weigh each historical record of an Internet of things service, based on its service invocation time and location; afterward, we weigh each candidate Internet of things service based on its invocation frequency; finally, with the derived two kinds of weights, we evaluate each candidate Internet of things service and return the quality-optimal one to the target user. At last, through a set of experiments deployed on a real service quality data set WS-DREAM , we validate the feasibility of our proposal. |
| format | Article |
| id | doaj-art-e11fabb3c6a849a2b348bb8b6b71465b |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-e11fabb3c6a849a2b348bb8b6b71465b2025-08-20T02:21:28ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-01-011310.1177/1550147716688696“Time–Location–Frequency”–aware Internet of things service selection based on historical recordsLianyong Qi0Peiqiang Dai1Jiguo Yu2Zhili Zhou3Yanwei Xu4School of Information Science and Engineering, Qufu Normal University, Rizhao, ChinaHuangdao District Experimental Middle School, Qingdao, ChinaSchool of Information Science and Engineering, Qufu Normal University, Rizhao, ChinaJiangsu Engineering Center of Network Monitoring, School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, ChinaSchool of Information Science and Engineering, Qufu Normal University, Rizhao, ChinaThe advertised quality of an Internet of things service is not always trustable due to the exaggerated quality propagation and dynamic network environment. Therefore, it is more trustable to evaluate the Internet of things service quality based on the historical execution records of service. However, an Internet of things service often has multiple historical records whose invocation time and location are different, which makes it necessary to weigh each historical record of an identical Internet of things service. Besides, for different candidate Internet of things services, their invocation frequencies are often varied, which may also affect the final service selection decision of target user. In view of the above two challenges, a novel service selection approach “Time–Location–Frequency”–aware Service Selection Approach is put forward in this article. In Time–Location–Frequency–aware Service Selection Approach, we first weigh each historical record of an Internet of things service, based on its service invocation time and location; afterward, we weigh each candidate Internet of things service based on its invocation frequency; finally, with the derived two kinds of weights, we evaluate each candidate Internet of things service and return the quality-optimal one to the target user. At last, through a set of experiments deployed on a real service quality data set WS-DREAM , we validate the feasibility of our proposal.https://doi.org/10.1177/1550147716688696 |
| spellingShingle | Lianyong Qi Peiqiang Dai Jiguo Yu Zhili Zhou Yanwei Xu “Time–Location–Frequency”–aware Internet of things service selection based on historical records International Journal of Distributed Sensor Networks |
| title | “Time–Location–Frequency”–aware Internet of things service selection based on historical records |
| title_full | “Time–Location–Frequency”–aware Internet of things service selection based on historical records |
| title_fullStr | “Time–Location–Frequency”–aware Internet of things service selection based on historical records |
| title_full_unstemmed | “Time–Location–Frequency”–aware Internet of things service selection based on historical records |
| title_short | “Time–Location–Frequency”–aware Internet of things service selection based on historical records |
| title_sort | time location frequency aware internet of things service selection based on historical records |
| url | https://doi.org/10.1177/1550147716688696 |
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