TY - GEN
T1 - COPS
T2 - 2025 IEEE International Conference on Communications, ICC 2025
AU - Aujla, Gagangeet Singh
AU - Jindal, Anish
AU - Kaur, Kuljeet
AU - Garg, Sahil
AU - Chaudhary, Rajat
AU - Sun, Hongjian
AU - Kumar, Neeraj
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - To mitigate various challenges in the edge-cloud ecosystem, such as global monitoring, flow control, and policy modification of legacy networking paradigms, software-defined networks (SDN) have evolved as a major technology. However, the dependency on a single centralized controller is challenging due to the scalability and resilience issues. Thus, deploying multiple controllers becomes inevitable to process the data with maximum throughput and minimum delay. Controller placement problem (CPP) is a major issue that needs to be addressed by designing efficient solutions. To address the CPP, two parameters, i) number of controllers and ii) location of controllers, need to be handled optimally. Thus, an Optimal COntroller Placement Scheme (COPS) using the multi-objective evolutionary approach for SDN is proposed in this paper. The results prove its effectiveness in terms of various evaluation parameters.
AB - To mitigate various challenges in the edge-cloud ecosystem, such as global monitoring, flow control, and policy modification of legacy networking paradigms, software-defined networks (SDN) have evolved as a major technology. However, the dependency on a single centralized controller is challenging due to the scalability and resilience issues. Thus, deploying multiple controllers becomes inevitable to process the data with maximum throughput and minimum delay. Controller placement problem (CPP) is a major issue that needs to be addressed by designing efficient solutions. To address the CPP, two parameters, i) number of controllers and ii) location of controllers, need to be handled optimally. Thus, an Optimal COntroller Placement Scheme (COPS) using the multi-objective evolutionary approach for SDN is proposed in this paper. The results prove its effectiveness in terms of various evaluation parameters.
KW - Clustering
KW - Controller placement
KW - Multi-objective evolutionary algorithm
KW - Software-defined networks
UR - https://www.scopus.com/pages/publications/105018465166
U2 - 10.1109/ICC52391.2025.11161194
DO - 10.1109/ICC52391.2025.11161194
M3 - Contribution to conference proceedings
AN - SCOPUS:105018465166
T3 - IEEE International Conference on Communications
SP - 2168
EP - 2173
BT - ICC 2025 - IEEE International Conference on Communications
A2 - Valenti, Matthew
A2 - Reed, David
A2 - Torres, Melissa
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 June 2025 through 12 June 2025
ER -