The next generation of mobile communication system will allow a plethora of new services and use cases. By offering support for high throughput connections, low latency response and massive number of connections, the fifth generation of the mobile network will trigger applications unseen in any other network. However, one important application scenario is not being properly addressed by the players responsible for the mobile networks’ standardization, that is the remote and rural areas network. This scenario requires large cells with high throughput, flexibility to opportunistically exploit free bands below 1 GHz and spectrum agility to change the operational frequency when an incumbent is detected. Incipient actions are being considered for the Release 17 but based on the new radio specification as starting point. The limitations imposed by orthogonal waveforms in the physical layers hinder the exploitation of vacant TV channels in rural and remote areas. 5G-RANGE, a Brazil-Europe bilateral cooperation project, aims at conceiving, implementing and deploying an innovative mobile network, designed to provide reliable and cost-effective connection in these regions. This network can be seamlessly integrated with the other 5G scenarios, closing the connectivity gap between the urban, rural and remote areas. Hence, 5G-RANGE network is an interesting complementary solution for beyond 5G standards. This paper presents the major achievements of the 5G-RANGE project, from the design of the physical, medium access control and network layers, to the field demonstrations. The paper also covers the business models that can be used to make the deployment of this technology a reality.

There is a concern about possible threats deriving from the widespread adoption of IoT (Internet of Things). The number of devices connected to the Internet is going to increase dramatically, potentiating their security risks. A Distributed Denial of Service (DDoS) attack is a good candidate to explore IoT security vulnerabilities, because of the enormous number of new devices connected to the Internet there is also an increase in the number of possible compromised devices. This study aims to analyze the efficiency of a DDoS attack in a typical IoT environment, by using simulations that, in the best of our knowledge, have not been conducted yet.

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

Hyperconverged infrastructures use distributed file systems to store and replicate data between multiple servers while using the processing capabilities of those same servers to host virtual machines and containers. In this work, the distributed file system GlusterFS and the VMware ESXi hypervisor are used to build a hyperconverged system to host Docker containers in order to evaluate the performance of this system compared to a traditional approach in which data is stored directly on local disks of the servers. The performance of container persistent data storage is assessed using FIO (Flexible I/O Tester) storage benchmark tool with different workloads from Microsoft data centers and with multiple disk configurations in the hyperconverged system. The experimental results show that with a greater amount of writing operations and that handle large files, the performance in the hyperconverged architecture is better than in local storage, which presents an economically viable option in the implementation of storage for datacenters.