Sep 2026· EAI Endorsed Transactions on Internet of Things· 0 citations· 23 references
TL;DR
A detailed comparative evaluation of six controller placement strategies like random placement method, degree centrality, latency-aware, hierarchical, k-median, and genetic algorithm using two widely adopted SDN controllers shows that load balancing improves latency in most configurations and consistently enhances throughput.
Abstract
Software defined networking (SDN) introduces a flexible network control paradigm by separating the control plane from the data plane. Due to its improved programmability and scalability, it raises two important challenges: determining optimal controller placement and ensuring efficient load distribution among multiple controllers. These factors directly influence key performance metrics such as latency, throughput, and recovery time during failures. This work presents a detailed comparative evaluation of six controller placement strategies like random placement method, degree centrality, latency-aware, hierarchical, k-median, and genetic algorithm using two widely adopted SDN controllers. They are Open Network Operating System(ONOS) and OpenDaylight (ODL). Experiments are conducted on a 500-node fat-tree topology under two operating modes: without load balancing (No-LB) and with dynamic control-plane load balancing (With-LB). In addition, a failure-aware extension of the genetic algorithm is incorporated to evaluate time-to-recovery (TTR) under simulated controller failures. The results show that load balancing improves latency in most configurations and consistently enhances throughput. The best performance is achieved by ONOS combined with genetic algorithm or latency-aware placement under load balancing, reaching a minimum latency of 5.16 ms and an average RTT of 2.11 ms. OpenDaylight demonstrates stable and predictable behaviour across all placement strategies, although with slightly higher latency compared to ONOS. A notable observation is the degradation in performance under hierarchical placement when load balancing is enabled, where latency increases by approximately 11% for ONOS and 13% for OpenDaylight. Under failure conditions, the recovery time ranges between 242 ms and 277 ms depending on the controller and configuration. These findings provide practical insights into selecting suitable controller-placement and load-balancing combinations for both latency-sensitive and reliability-focused SDN deployments.
Software-defined networking (SDN) decouples the control plane from the data plane, enabling centralized network management and programmability. However, as the network scale continues to expand, a single controller becomes a performance bottleneck and a single point of failure. To address this, multi-controller archite...
Hui Xu, Pan Hu, Yong-Lei Yang· Applied Sciences· 0 citations
ConFlet is presented, a congestion-aware load balancing with Flowlet switching based on the cooperation of the data and control plane, where the control plane monitors the global network status to perform the optimized routing decision, and the data plane implements the flow splitting and path switching.
Zi-Yong Li, Yu-Sheng Xia, Jun-Fei Li et al.· Computers, Materials & C...· 0 citations
This thesis provides an end-to-end mathematical and machine learning framework for designing dependable, low-latency, and scalable SDN infrastructures.
This paper proposes SDN-based traffic engineering approach that combines in one control-plane link utilization monitoring, delay-aware path selection and proactive failure recovery, and proposes a greedy congestion and latency aware routing algorithm and a mechanism of pre-computation of backup paths.
M. S., B. M.· International journal of all...· 0 citations
Findings affirm that the suggested scalable control plane is practical in supporting large scale SDN implementation and is therefore applicable in future carrier grade, data center and wide area network deployments at realistic workloads with varying topological setups in the modern programmable networks in the world.
A. Nagadeepan, Vishakha Abhay Gaidhani, Bhambare Rajesh et al.· Journal of Intelligent Decis...· 0 citations
Time-Window-Based Efficient Initial Mapping for Software-Defined Networks (TW-EIMSDN), an online VNE framework that separates immediate admission and initial embedding from deferred, gain-thresholded rule rewriting, is presented.
Amir Javadpour, Forough, Tarik Ja'fari et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.