Optimum VM Placement for NFV Infrastructures

Abstract

This paper constitutes an industrial experience report about the use of data center optimization strategies for softwarized network services within the Vodafone resource management unit for the management of virtualized network infrastructures. The problem of optimum virtual machine placement as needed in the network operator context is detailed, and different solving strategies are proposed and discussed, including heuristics based on genetic optimization. Also, experimental results are presented that compare these strategies with one another from the standpoint of optimality and execution times, using a data-set made of some of the real problems that had to be solved in the past few years by Vodafone, in order to optimize its capacity planning decisions. The presented experimental results highlight that an optimum solver leads to excessively high computation times for large problems, whereas simple heuristics may exhibit significant loss in optimality at reduced computation times. Genetic optimization, on the other hand, constitutes a very interesting trade-off between these two extremes. The data-set used for the provided results is published under an open data license, for possible reuse in future research works on the topic.

Near Real-Time Anomaly Detection in NFV Infrastructures

“…In the context of NFV and cloud computing, the monitoring subsystem of the infrastructure is a critical component, leveraged at various levels of daily operational activities. Specifically, monitoring of networking [9] appliances as well as com-putational elements (both physical hosts and virtualized instances), becomes critical [10] to support daily activities such as realizing appropriate elasticity [11] and placement [12], [13] policies or anomaly detection techniques [14], [15], where metric forecasting can also play a key role [16], [17].…”