A framework for real time end to end monitoring and big data oriented management of smart environments.

Nowadays, the success of Internet of Things (IoT) applications depends on the intelligence of tools and techniques that can monitor, manage, and verify the correct operations of smart ecosystems including sensors and big data analytics tools, typically deployed in Cloud and Edge computing datacenters. In this paper, we propose a framework for the monitoring and management of IoT system that integrates the AllJoyn functionalities, useful to interconnect IoT devices, MongoDB, to implement Big Data storage, and Storm, to run real-time data analytics. We implemented the proposed framework and we tested its main functionalities in a smart home application scenario. In our experimentation, we investigated three different data patterns, i.e., regular, event-based, and automated, in order to evaluate performance of our framework in terms of response time under different operational conditions. Experimental results show that the latency of the monitoring and service strongly depends on the type of management application running in the system, whereas it is lightly affected by the data patterns. • Monitoring of IoT device requires the analysis of big data. • We propose a piece framework integrating AllJoyn with MongoDB and Storm. • Different data patterns were designed to manage several smart home scenarios. • Simulation experiments prove the feasibility of the proposed system. [ABSTRACT FROM AUTHOR]