Cellular for the skies: exploiting mobile network infrastructure for low altitude air-to-ground communications

In this article we presented an overview of UASs for civil applications focusing on the communication component. We identified several available communication technologies for UAVs, their constraints, and also protocols available for implementing the remote operation of the vehicles. As an attractive solution for the A2G communication link for UAVs, we discussed the potential of mobile networks with their fully deployed infrastructures, wide radio coverage, high throughputs, reduced latencies, and large availability of radio modems. We described how a UAS can be implemented in a flexible and modular approach that allows it to rely on one or several wireless (UAVs and GCSs) and wired (GCSs) technologies. Despite the advantages of a system based on cellular and IP networks, there are problems that must be dealt with, namely, possible loss of radio coverage, presence of NAT, delay, jitter, and packet loss. Following the proposed architecture, we implemented an UAS and conducted some flight tests, which showed that the operation of the vehicles in semi-automatic or fully-automatic modes is feasible. It is expected that future enhancements for 4G networks and evolution to 5G will benefit UAV communications even further with lower latencies, higher throughput, and higher reliability.info:eu-repo/semantics/acceptedVersio

An adaptive management proposal for optimizing the performance of a virtualized computing environment

The number of virtualized servers is overtaking, by a large amount, the number of physical servers. One of the drawbacks of this new scenario is a much more complex computing infrastructure to manage. In this way, the current paper proposes a adaptive management prototype that controls a virtualized environment. This prototype guarantees an adaptive and automatic solution that efficiently supervises and controls any virtualized environment, without almost any human intervention. In addition, it manages the relevant physical computing resources allocated to each virtual machine, like memory and processing power. The results from our prototype suggest that it is possible to balance memory among various machines and perform an effective control of each machine's workload, with a simple and low cost solution for our initial problem.info:eu-repo/semantics/acceptedVersio