Towards Osmotic Computing: a BlueGreen Strategy for the Fast ReDeployment of Microservices The rapid development of Cloud, Edge, Fog Computing and Internet of Things (IoT) technologies has played a key role in the Industry 4.0 evolution. In this context, the Osmotic Computing paradigm, theorized in 2016 as integration between a centralized Cloud layer and Edge andor IoT layers, has further emphasized the Industry 4.0 objectives including productivity and Quality of Services (QoS). This emerging paradigm proposes a new elastic management model of microservices, where deployment and migration strategies are strongly related to the underlaying infrastructure requirements (i.e., load balancing, reliability, availability, and so on) and applications (i.e., anomalies detection, awareness of the context, proximity, QoS, and so on). Specifically, knowing that an Osmotic application must have a failover behavior (highly horizontallyvertically scalable, 24 hours 24 available, faulttolerant and secure), this paper highlights the Osmotic ecosystem platform focusing on the implementation of a bluegreen mechanism for the fast redeployment of microservices, exploiting emerging technologies, such as Docker, Kubernetes, Agento and MongoDB. Experiments shows the time required to arrange, deploy and destroy microservices.

MQTTbased Middleware for Container Support in Fog Computing Environments Distributed architectures where the Internet of Things (IoT) and the cloud are efficiently integrated play an increasingly important role for IoT solutions. Among these architectures, there is a growing interest in the ones that support the opportunity of functionality offloading towards either intermediate fog nodes or IoT end devices. Relevant existing research work has mainly focused so far on virtual machine and container migration to intermediate fog nodes and on migration of very simple functions to IoT endpoints (to preserve their limited resources available). In this paper, we originally concentrate on the gap associated with benefitting from fog functionality at resourcepowerful IoT endpoints, to create a continuum deployment that glues IoT devices and the cloud. In particular, this paper originally presents a middleware that manages application deployment and lifecycle by simplifying and optimizing management operations such as device configuration and application constraint satisfaction. The proposed solution particularly fits highly articulated scenarios with large numbers of IoT devices and intermediate fog nodes, by supporting the opportunity to offload functionality in a split way between IoT endpoints and edge nodes. The reported experimental results confirm the feasibility of our approach in term of overhead, scalability, and application lifecycle management.