A New Monitoring Approach with Cloud Computing for Autonomic Middleware-Level Scalability Management Within IoT Systems

Internet of Things (IoT) transformed the Internet into a fully integrated future Internet by developing the way objects exchange data with users all over the world; IoT has an important impact on intelligent decisions made by devices interacting with humans in different applications domains. However, IoT suffers from many issues, most importantly the incapability to scale automatically depending on the overload made by the enormous number of users and/or massive volume of exchanged data. This paper gives, for the first time, a new way to analyze the scalability issue in the IoT systems. In order to promote the vision of an autonomic middleware-level scalability management for IoT systems based on cloud computing, we propose an enhancement of the architectural design of the monitoring components making our IoT system more scalable without any QoS symptom degradation. Using two proposed oriented scalability mechanisms, a series of experiments have been carried out to evaluate the performance of our approach, for different scenarios testbed. Generally, our results are better than that provided by the current solving approaches taken as reference.