Big data storage and processing are considered as one of the main applications for cloud computing systems. Furthermore, the development of the Internet of Things (IoT) paradigm has advanced the research on Machine to Machine (M2M) communications and enabled novel tele-monitoring architectures for E-Health applications. However, there is a need for converging current decentralized cloud systems, general software for processing big data and IoT systems. The purpose of this paper is to analyze existing components and methods of securely integrating big data processing with cloud M2M systems based on Remote Telemetry Units (RTUs) and to propose a converged E-Health architecture built on Exalead CloudView, a search based application. Finally, we discuss the main findings of the proposed implementation and future directions.

Due to the ever-increasing number of radio communication technologies, lack of frequency spectrum has become a serious problem recently. Cognitive Radio (CR) technology promises to be one possible solution to this problem, by allowing access of unlicensed users in licensed bands, based on an opportunistic approach and without interfering with the licensed (primary) user. In order to identify which frequency bands are more suitable for such purposes, it is necessary to evaluate the degree in which licensed bands are actually used. Although some measurement campaigns have already been carried out, most of them were done in the USA and only a few in other locations worldwide. This paper presents results of a measurement campaign conducted in Bucharest, Romania, covering the frequency range from 25 MHz up to 3.4 GHz. The measurement results are confronted with the frequency allocation table published by the national authority for communications and an analysis of the obtained data is being made.

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