{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T05:56:15Z","timestamp":1722664575593},"reference-count":38,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2019,10,20]],"date-time":"2019-10-20T00:00:00Z","timestamp":1571529600000},"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":"The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers to take considerable time and effort. Furthermore, the developed IoT collaboration services are often dependent on a particular domain, which cannot easily be referenced in other domains. This paper proposes a cloud-based middleware framework that provides a set of cloud services for self-adaptive IoT collaboration services. The proposed middleware framework is generic in the sense that it clearly separates domain-dependent components from the layers that leverage existing middleware frameworks. In addition, the proposed framework allows developers to upload domain-dependent components onto the cloud, search for registered components, and launch Virtual Machine (VM) running a new MAPE cycle via a convenient web-based interface. The feasibility of the proposed framework has been shown with a simulation of an IoT collaboration service that traces a criminal suspect. The performance evaluation shows that the proposed middleware framework runs with an overhead of only 6% compared to pure Java-based middleware and is scalable as the number of VMs increases up to 16.<\/jats:p>","DOI":"10.3390\/s19204559","type":"journal-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T07:40:29Z","timestamp":1571643629000},"page":"4559","source":"Crossref","is-referenced-by-count":11,"title":["A Cloud-based Middleware for Self-Adaptive IoT-Collaboration Services"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-5935-9523","authenticated-orcid":false,"given":"Soojin","family":"Park","sequence":"first","affiliation":[{"name":"Graduate School of Management of Technology, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Korea"}]},{"given":"Sungyong","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1109\/TSG.2017.2750542","article-title":"A Hierarchical Framework for Intelligent Traffic Management in Smart Cities","volume":"10","author":"Li","year":"2019","journal-title":"IEEE Transact. 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