Risk Aware Traffic Engineering

Analysis and use risk measures a favorite approach of mine.  Risk-aware always a good idea.  Especially considering architectures.

Using Wall Street secrets to reduce the cost of cloud infrastructure
“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.

By Rob Matheson | MIT News Office 

Stock market investors often rely on financial risk theories that help them maximize returns while minimizing financial loss due to market fluctuations. These theories help investors maintain a balanced portfolio to ensure they’ll never lose more money than they’re willing to part with at any given time.

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. ..... "