Figure - available from: Telecommunication Systems
This content is subject to copyright. Terms and conditions apply.
The illustration of Single Point of Failure (SPOF) problem where (a) is the controller overload and (b) is the device isolation

The illustration of Single Point of Failure (SPOF) problem where (a) is the controller overload and (b) is the device isolation

Source publication
Article
Full-text available
Software-defined networking (SDN) has become the technology of choice for designing the next-generation network infrastructure that is featured with high-volume traffics, rapidly increased scale, and dynamic nature. Furthermore, to deploy multiple controllers in the control plane of SDN is widely considered with the aim of improving the stability a...

Citations

... Tzeng and Shen [23] propounded an integrated approach for multi-controller management in SDN. Here, the Maximal Neighbors Controller Placement (MNCP) algorithm was used, which addressed the issues of device isolation and controller overload, and improved the control plane's reliability and stability. ...
... The proposed controller selection and resource allocation has been evaluated against several existing methods, including those by Javadpour and Wang [26], Ali et al. [17], Tzeng and Shen [23]. Each phase has been meticulously compared with various techniques. ...
Article
Full-text available
Software Defined Networking (SDN) has emerged as a promising paradigm for network management. However, in energy-effective task scheduling and security, the centralized control architecture of SDN brings challenges. This research proposes a new approach for blockchain-based secure resource allocation with controller selection in SDN, utilizing the Entropy Oppositional Based Learning-Interpolation Blue Monkey Optimization Algorithm (EOBL-IBMOA). By establishing a blockchain-centric secure resource allocation with controller selection, the proposed technique addresses challenges in SDN. Here, user registration, load balancing, attack detection, controller selection, and resource allocation phases are included. Utilizing XOR Left Shift (XORLS), the user details are secured by IP traceback and hash codes are generated using the Mid Square-based KECCAK 512 (MS-KECCAK 512) algorithm. For effective traffic balancing, the load balancer uses the Minshev-KMeans algorithm. Attack classification is attained through the Quantile Transformer Scaling based SoftmaxGELU Gated Recurrent Units (QTS-SGGRU) approach. EOBL-IBMOA is used by controller selection and resource allocation for optimal Virtual Machine (VM) selection. The proposed technique’s superiority is described by experimental comparisons. The proposed approach attains effective resource allocation with reduced response time and high throughput, outperforming the prevailing works.