Researchers have developed a ‘risk-aware’ model that improves the performance of cloud-computing infrastructure used across the globe.

Inspired by those theories, MIT researchers in collaboration with Microsoft have developed a «risk-aware» mathematical model that could improve the performance of cloud-computing networks across the globe. Notably, cloud infrastructure is extremely expensive and consumes a lot of the world’s energy.

Their model takes into account failure probabilities of links between data centers worldwide — akin to predicting the volatility of stocks. Then, it runs an optimization engine to allocate traffic through optimal paths to minimize loss, while maximizing overall usage of the network.

The model could help major cloud-service providers — such as Microsoft, Amazon, and Google — better utilize their infrastructure. The conventional approach is to keep links idle to handle unexpected traffic shifts resulting from link failures, which is a waste of energy, bandwidth, and other resources. The new model, called TeaVar, on the other hand, guarantees that for a target percentage of time — say, 99.9 percent — the network can handle all data traffic, so there is no need to keep any links idle. During that 0.01 percent of time, the model also keeps the data dropped as low as possible.

In experiments based on real-world data, the model supported three times the traffic throughput as traditional traffic-engineering methods, while maintaining the same high level of network availability. A paper describing the model and results will be presented at the ACM SIGCOMM conference this week.

Better network utilization can save service providers millions of dollars, but benefits will «trickle down» to consumers, says co-author Manya Ghobadi, the TIBCO Career Development Assistant Professor in the MIT Department of Electrical Engineering and Computer Science and a researcher at the Computer Science and Artificial Intelligence Laboratory (CSAIL).

Story Source: Materials provided by Massachusetts Institute of Technology. Original written by Rob Matheson. Note: Content may be edited for style and length.