%0 Conference Paper %1 Lange.2017 %A Lange, Stanislav %A Grigorjew, Alexej %A Zinner, Thomas %A Tran-Gia, Phuoc %A Jarschel, Michael %B 29th International Teletraffic Congress (ITC 29) %C Genoa, Italy %D 2017 %K itc itc29 %T A Multi-Objective Heuristic for the Optimization of Virtual Network Function Chain Placement %U https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc29/Lange.2017.pdf?inline=true %X The Network Functions Virtualization (NFV) paradigm offers network operators benefits in terms of cost efficiency, vendor independence, as well as flexibility and scalability. However, in order to profit most from these features, new challenges in the area of management and orchestration of the virtual network functions (VNFs) need to be addressed. In particular, this work deals with the VNF chain placement problem (VNFCP). For a given network situation, the task consists of determining the number, location, and assignment of VNF instances and the routing of demands. At the same time, several metrics like CPU utilization and the delay of individual flows need to be taken into account. For applicability in networks with dynamically changing conditions, algorithms need to explore the solution space of this NP-hard problem in a timely manner. The contribution of this work is threefold: firstly, we design MO-VNFCP, a multi-objective heuristic for the VNFCP. Secondly, we investigate the convergence behavior of the algorithm in a case study. Finally, we provide a comparison between the proposed algorithm and an alternative approach from literature.

@inproceedings{Lange.2017, abstract = {The Network Functions Virtualization (NFV) paradigm offers network operators benefits in terms of cost efficiency, vendor independence, as well as flexibility and scalability. However, in order to profit most from these features, new challenges in the area of management and orchestration of the virtual network functions (VNFs) need to be addressed. In particular, this work deals with the VNF chain placement problem (VNFCP). For a given network situation, the task consists of determining the number, location, and assignment of VNF instances and the routing of demands. At the same time, several metrics like CPU utilization and the delay of individual flows need to be taken into account. For applicability in networks with dynamically changing conditions, algorithms need to explore the solution space of this NP-hard problem in a timely manner. The contribution of this work is threefold: firstly, we design MO-VNFCP, a multi-objective heuristic for the VNFCP. Secondly, we investigate the convergence behavior of the algorithm in a case study. Finally, we provide a comparison between the proposed algorithm and an alternative approach from literature.}, added-at = {2017-10-05T16:41:49.000+0200}, address = {Genoa, Italy}, author = {Lange, Stanislav and Grigorjew, Alexej and Zinner, Thomas and Tran-Gia, Phuoc and Jarschel, Michael}, biburl = {https://www.bibsonomy.org/bibtex/26dc514ea51b8dc3fcb32587651620a4d/itc}, booktitle = {29th International Teletraffic Congress (ITC 29)}, interhash = {f9cbbfa7d6098ae129a056f679d8d181}, intrahash = {6dc514ea51b8dc3fcb32587651620a4d}, keywords = {itc itc29}, timestamp = {2020-04-30T18:18:14.000+0200}, title = {A Multi-Objective Heuristic for the Optimization of Virtual Network Function Chain Placement}, url = {https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc29/Lange.2017.pdf?inline=true}, year = 2017 }