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

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4559
Author(s):  
Park ◽  
Park

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.

Author(s):  
Osman A. Nasr ◽  

This study aims to develop a web-based system that evaluates the teaching process based on the course learning outcomes. It includes the active involvement of both the course teacher and the enrolled students on the course. Usually, the teacher delivers the course contents by following the course specification and the course learning outcomes. Here, the teacher is a source of equipping students with all the necessary information about the course and the assessment policies. The students participate in the scheduled assessments, and the teacher evaluates students’ performances based on the course learning outcomes. Significantly, the presented study applies the ordinal scale method for evaluating the students’ performances in the conducted assessments. The students’ performances are measured, and the outcomes help the teacher understand the students' learned skills of the course. Further, the result of the measured outcomes uses for the program performance evaluation at the end of the academic cycle. The presented approach is easy to adapt for any academic course in higher education and enables an effective approach for performance evaluation.


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