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Data centers are critical to the commercial and social activities of modernsociety but are also major electricity consumers. To minimize theirenvironmental impact, it is imperative to make data centers more energyefficient while maintaining a high quality of service (QoS). Bearing thisconsideration in mind, we develop an analytical model using queueing theory forevaluating the QoS of a data center. Furthermore, based on this model, wedevelop a domain-specific evolutionary optimization framework featuring atailored solution representation and a constraint-aware initialization operatorfor finding the optimal placement of virtual network functions in a data centerthat optimizes multiple conflicting objectives with regard to energyconsumption and QoS. In particular, our framework is applicable to any existingevolutionary multi-objective optimization algorithm in a plug-in manner.Extensive experiments validate the efficiency and accuracy of our QoS model aswell as the effectiveness of our tailored algorithms for virtual networkfunction placement problems at various scales.

Evolutionary Multi-Objective Virtual Network Function Placement: A Formal Model and Effective Algorithms