SUMMARY REMARKS & TESTBEDS
Galgus is an SME highly specialised in the R&D of innovative solutions to optimise the performance of high-density Wi-Fi networks. Galgus solutions are agglutinated in its patented technology named Cognitive HotspotTM Technology (CHT), a multi-platform software product capable of performing a real-time optimisation of the network in a distributed and decentralised way. Latest prior-art proposals claim that maximizing the performance of Wi-Fi networks requires of accurate physical layer information of received and transmitted signals, information that is not commonly provided by the Wi-Fi firmware to the Operating System’s user space. Therefore, these prior-art solutions propose to modify the firmware of Wi-Fi devices, an approach which is very invasive and “unscalable”. In contrast, Galgus vision consists in developing innovative solutions capable of performing in any commercial hardware by using only information available in the Operating System’s user space (e.g. SNIR, MCS, transmitted packets, etc.). In this project, Galgus proposes to analyse the behaviour of its latest algorithms specifically designed to tackle the following problems detected by its clients: optimisation of channel assignments considering different channel bandwidths, indoor positioning and automatic transmit power control for heterogeneous Wi-Fi networks (i.e. networks with APs of many different manufacturers), predictive methods to minimise service disruptions due to roaming processes, and an efficient and user-friendly network manager for decentralised Wi-Fi networks. These experiments will be carried out in both set-ups of the w-ilab.t testbed to get accurate insights about the well-performance, scalability, and robustness of these innovative solutions. Thanks to the use of controlled and near-real use-cases within the w-ilab.t testbed, Galgus will be able to increase its own technical scope and competitiveness while reducing the time to market of these innovative solutions. Finally, but not less important, Galgus aims to provide periodic feedback to the w-ilab.t team of experts in order to improve its facility.