Bandwidth in the Cloud

TL;DR

This study measures and analyzes bandwidth dynamics across multiple cloud data-centers and providers, revealing predictable patterns related to location and low correlation between paths, which impacts cloud robustness and deployment strategies.

Contribution

It provides the first extensive measurement campaign characterizing cloud bandwidth as a combination of stationary and infrequent events, with analysis linking these to data-center location and provider.

Findings

Bandwidth is predictable based on location and provider.

Low correlation (10%) between data-center paths.

Correlation depends on specific data-center relationships.

Abstract

The seek for the best quality of service has led Cloud infrastructure clients to disseminate their services, contents and data over multiple cloud data-centers often involving several Cloud Service Providers (CSPs). The consequence of this is that a large amount of bytes must be transmitted across the public Cloud. However, very little is known about its bandwidth dynamics. To address this, we have conducted a measurement campaign for bandwidth between eighteen data-centers of four major CSPs. Such extensive campaign allowed us to characterize the resulting time series of bandwidth as the addition of a stationary component and some infrequent excursions (typically, downtimes). While the former provides a description of the bandwidth users can expect in the Cloud, the latter is closely related to the robustness of the Cloud (i.e., the occurrence of downtimes is correlated). Both components have been studied further by applying a factor analysis, specifically ANOVA, as a mechanism to formally compare data-centers' behaviors and extract generalities. The results show that the stationary process is closely related to data-center locations and CSPs involved in transfers, which fortunately makes both the Cloud more predictable and the set of reported measurements extrapolate. On the other hand, although the correlation in the Cloud is low, i.e., only 10% of the measured pair of paths showed some correlation, we have found evidence that such correlation depends on the particular relationships between pairs of data-centers with little link to more general factors. Positively, this implies that data-centers either at the same area or CSP do not show qualitatively more correlation than others data-centers, which eases the deployment of robust infrastructures. On the downside, this metric is barely generalizable and, consequently, calls for exhaustive monitoring.