For many applications with inter-datacenter cloud deployments it is important to rely on an accurate model of delay times across different geolocations. Unfortunately, such a model is currently not available to researchers and practitioners. To fill that gap, this letter presents a thorough analysis of real-life latency values collected between different Amazon datacenter locations, and proposes a novel Gaussian mixture approximation model of the round-trip time distribution based on the relaxed boxed approximation algorithm. The proposed model can be effectively used for the emulation/simulation of cross-cloud application and service deployments.
Cerroni, W., Foschini, L., Grabarnik, G.Y., Shwartz, L., Tortonesi, M. (2018). Estimating delay times between cloud datacenters: A pragmatic modeling approach. IEEE COMMUNICATIONS LETTERS, 22(3), 526-529 [10.1109/LCOMM.2017.2782722].
Estimating delay times between cloud datacenters: A pragmatic modeling approach
Cerroni, Walter;Foschini, Luca;
2018
Abstract
For many applications with inter-datacenter cloud deployments it is important to rely on an accurate model of delay times across different geolocations. Unfortunately, such a model is currently not available to researchers and practitioners. To fill that gap, this letter presents a thorough analysis of real-life latency values collected between different Amazon datacenter locations, and proposes a novel Gaussian mixture approximation model of the round-trip time distribution based on the relaxed boxed approximation algorithm. The proposed model can be effectively used for the emulation/simulation of cross-cloud application and service deployments.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
