Asset Details
Do you wish to reserve the book?
ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN
Do you wish to request the book?
ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN
2025
Overview
Software-defined wireless sensor networks (SDWSNs) have recently been added to networking, increasing scalability and performance. Choosing SDN controllers is a critical issue for network administrators in SDNs. The control plane in SDN is a separate procedure that operates on the control layer. In terms of applications and services, the controller provides a comprehensive view of the entire network. The three key factors examined when selecting a controller are open source, campus network, and productivity. An appropriate device for the prompt processing of all switch requests is required for SDN to function properly and the network to behave properly. To determine the optimum controller for the given parameters, decision logic that allows controller comparison must be developed. As a result, an improved Sailfish Optimization based controller selection (ISFO-CS) method is proposed in this study to ideally take the best controller node (CN) from a group of sensor nodes. The ISFO selects the best CN by considering a multi-objective fitness function incorporating distance, residual energy, node coverage, and sensor node communication cost. After selecting CN, the Fuzzy C-means (FCM) Clustering algorithm executes the subsequent data transmission process. The Matlab program is used to execute the simulation, and the performance of the proposed ISFO-CS methodology is assessed using several performance criteria. The proposed ISFO-CS model accomplishes a 95% packet delivery ratio for 500 rounds, consumes less energy of 0.13 mJ, and takes 1.8 s for 500 rounds of node to controller latency.
Publisher
Springer US,Springer Nature B.V
Subject
