Rankothge, WindhyaLe, FranckRusso, AlessandraLobo, Jorge2019-05-132019-05-132017Rankothge W, Le F, Russo A, Lobo J. Optimizing resource allocation for virtualized network functions in a cloud center using genetic algorithms. IEEE Trans Netw Serv Manage. 2017;14(2): 343-56. DOI: 10.1109/TNSM.2017.26869791932-4537http://hdl.handle.net/10230/37214With the introduction of network function virtualization technology, migrating entire enterprise data centers into the cloud has become a possibility. However, for a cloud service provider (CSP) to offer such services, several research problems still need to be addressed. In previous work, we have introduced a platform, called network function center (NFC), to study research issues related to virtualized network functions (VNFs). In an NFC, we assume VNFs to be implemented on virtual machines that can be deployed in any server in the CSP network. We have proposed a resource allocation algorithm for VNFs based on genetic algorithms (GAs). In this paper, we present a comprehensive analysis of two resource allocation algorithms based on GA for: 1) the initial placement of VNFs and 2) the scaling of VNFs to support traffic changes. We compare the performance of the proposed algorithms with a traditional integer linear programming resource allocation technique. We then combine data from previous empirical analyses to generate realistic VNF chains and traffic patterns, and evaluate the resource allocation decision making algorithms. We assume different architectures for the data center, implement different fitness functions with GA, and compare their performance when scaling over the time.application/pdfeng© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at http://ieeexplore.ieee.org/document/7885521/info:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/TNSM.2017.2686979Network function virtualization (NFV)Cloud resources optimizationGenetic algorithmsinfo:eu-repo/semantics/openAccess