4.6 Article

A Cloud-based Middleware for Self-Adaptive IoT-Collaboration Services

Journal

SENSORS
Volume 19, Issue 20, Pages -

Publisher

MDPI
DOI: 10.3390/s19204559

Keywords

internet of things; self-adaptation; middleware platform; cloud service

Funding

  1. Next-Generation Information Computing Development Program through National Research Foundation of Korea (NRF) - Ministry of Science, ICT [2017M3C4A7080245]
  2. National Research Foundation of Korea [2017M3C4A7080245] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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.

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