LoRaWAN networks might be a technology that could facilitate extreme energy-efficient operation while offering great capacity for suburban and rural area deployment, but this can be a challenging task for a network administrator. Constraints that deform the trade-off triangle of coverage, scalability and energy efficiency need to be overcome. The scope of this study is to review the limitations of the LoRaWAN protocol in order to summarize and assess the crucial factors that affect communication performance, related to data rate allocation, bidirectional traffic and radio spectrum utilization. Based on the literature, these factors correspond mostly to configurable payload transmission parameters, including transmission interval, data rate allocation, requirement for acknowledgements and retransmission. In this work, with simulation experiments, we find that collision occurrences greatly affect channel occupancy. In particular, it was evaluated that collision occurrence is increasingly affected by transmission intervals, which have the most significant negative impact on packet delivery rate (PDR). We then validated that clustering of end nodes in the vicinity of a gateway, taking into account distance and transmission settings, can improve network scalability. This can assure distribution of the total transmission time to end nodes with respect to application-related QoS requirements. Following this clustering approach, we achieved a PDR greater than 0.90 in a simulation setting with 6000 end nodes in a 10 km coverage.

Ontologies are widely used nowadays. However, the plethora of ontologies currently available online, makes it really difficult to identify which ontologies are appropriate for a given task and to decide on their quality characteristics. This is further complicated by the fact that multiple quality criteria have been proposed for ontologies, making it even more difficult to decide which ontology to adopt. In this context, in this paper we present Delta, a modular online tool for analyzing and evaluating ontologies. The interested user can upload an ontology to the tool, which then automatically analyzes it and graphically visualizes numerous statistics, metrics, and pitfalls. Those visuals presented include a diverse set of quality dimensions, further guiding users to understand the benefits and the drawbacks of each individual ontology and how to properly develop and extend it.