Scheduling resources in Cloud distributed videoconferencing systems presents a complex challenge not resolved yet. Traditional scheduling models are not applicable due to the particular characteristics of such type of systems. One of the main issues is estimating how many resources will consume a new client that connects to a videoconferencing session. Otherwise, it is difficult to decide where to allocate new requests. This paper proposes a new metric to perform this estimation basing on different parameters of the sessions. To validate the metric we set up a real scenario comparing the behaviour with and without the proposed metric. The conclusion is that the metric enables the design of more advanced and precise scheduling algorithms. Furthermore, thanks to this metric, resources are used more efficiently resulting in performance improvements and cost saving.
['Álvaro Alonso', 'Ignacio Aguado', 'Joaquín Salvachúa', 'Pedro Rodriguez']
A Metric to Estimate Resource Use in Cloud-Based Videoconferencing Distributed Systems