Mamushiane, LusaniMwangama, JLysko, Albert A2019-03-072019-03-072018-09Mamushiane, L., Mwangama, J. and Lysko, A.A. 2018. Optimum placement of SDN controllers in African backbones: SANREN and ZAMREN as a case study. Southern Africa Telecommunication Networks and Applications Conference (SATNAC) 2018S, Arabella Hotel & Spa, Cape Town, 2-5 September 2018978-0-620-81022-7http://www.satnac.org.za/proceedings/2018/SATNAC%202018%20Proceedings%20Final.pdfhttp://hdl.handle.net/10204/10745Paper presented at the Southern Africa Telecommunication Networks and Applications Conference (SATNAC) 2018S, Arabella Hotel & Spa, Cape Town, 2-5 September 2018Software Defined Networking (SDN) has emerged as a potential solution to the ICT inequality challenge in emerging markets. This technology promises to revolutionize the telecommunications industry by introducing decoupled architectures to facilitate network management and configuration. A consensus was reached that a huge portion of OpEx comes from the cost associated with the management and configuration of tightly coupled legacy networks. This has contributed to operators’ reluctance to extend broadband coverage to the poor rural areas and sparsely populated areas due to the potential low profit margins. SDN opens unprecedented opportunities such as non-discriminatory infrastructure sharing, hardware commoditization (through the use of cheap commodity hardware), and business agility. This is likely to encourage operators to cover rural areas with low or no network footprint. At the heart of SDN is a controller with a global view of the current network status. It is critical that this controller is placed in a manner that optimizes network performance. This design choice is commonly known as the controller placement problem (CPP). This paper proposes an algorithm for placement of the controller that optimizes network performance, particularly propagation latency. The algorithms are tested on two African backbones, namely SANREN and ZANREN.enAverage latencyController placementJohnson’s algorithmOptimizationPartition Around MedoidsPAMSANRENSoftware Defined NetworkingSDNWorst-case latencyZAMRENConference PresentationMamushiane, L., Mwangama, J., & Lysko, A. A. (2018). Optimum placement of SDN controllers in African backbones: SANREN and ZAMREN as a case study. SATNAC. http://hdl.handle.net/10204/10745Mamushiane, Lusani, J Mwangama, and Albert A Lysko. "Optimum placement of SDN controllers in African backbones: SANREN and ZAMREN as a case study." (2018): http://hdl.handle.net/10204/10745Mamushiane L, Mwangama J, Lysko AA, Optimum placement of SDN controllers in African backbones: SANREN and ZAMREN as a case study; SATNAC; 2018. http://hdl.handle.net/10204/10745 .TY - Conference Presentation AU - Mamushiane, Lusani AU - Mwangama, J AU - Lysko, Albert A AB - Software Defined Networking (SDN) has emerged as a potential solution to the ICT inequality challenge in emerging markets. This technology promises to revolutionize the telecommunications industry by introducing decoupled architectures to facilitate network management and configuration. A consensus was reached that a huge portion of OpEx comes from the cost associated with the management and configuration of tightly coupled legacy networks. This has contributed to operators’ reluctance to extend broadband coverage to the poor rural areas and sparsely populated areas due to the potential low profit margins. SDN opens unprecedented opportunities such as non-discriminatory infrastructure sharing, hardware commoditization (through the use of cheap commodity hardware), and business agility. This is likely to encourage operators to cover rural areas with low or no network footprint. At the heart of SDN is a controller with a global view of the current network status. It is critical that this controller is placed in a manner that optimizes network performance. This design choice is commonly known as the controller placement problem (CPP). This paper proposes an algorithm for placement of the controller that optimizes network performance, particularly propagation latency. The algorithms are tested on two African backbones, namely SANREN and ZANREN. DA - 2018-09 DB - ResearchSpace DP - CSIR KW - Average latency KW - Controller placement KW - Johnson’s algorithm KW - Optimization KW - Partition Around Medoids KW - PAM KW - SANREN KW - Software Defined Networking KW - SDN KW - Worst-case latency KW - ZAMREN LK - https://researchspace.csir.co.za PY - 2018 SM - 978-0-620-81022-7 T1 - Optimum placement of SDN controllers in African backbones: SANREN and ZAMREN as a case study TI - Optimum placement of SDN controllers in African backbones: SANREN and ZAMREN as a case study UR - http://hdl.handle.net/10204/10745 ER -