ISFO-CS: An Improved Sailfish Optimization Algorithm for Controller Selection in SDWSN

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...

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Bibliographic Details
Published in:Wireless personal communications Vol. 140; no. 1; pp. 299 - 331
Main Authors: Rajoriya, Manisha Kumari, Gupta, Chandra Prakash
Format: Journal Article
Language:English
Published: New York Springer US 01.01.2025
Springer Nature B.V
Subjects:
Algorithms
Clustering
Communications Engineering
Computer Communication Networks
Controllers
Data transmission
Energy consumption
Energy efficiency
Engineering
Internet of Things
Network latency
Networks
Nodes
Optimization
Optimization techniques
Residual energy
Sensors
Signal,Image and Speech Processing
Simulation
Software-defined networking
Wireless sensor networks
Software defined wireless sensor network (SDWSN)
Multi-objective fitness function
Controller nodes (CNs)
Data transmission
Controller selection problem (CSP)
Wireless sensor network (WSN)
Clustering algorithm
ISSN:0929-6212, 1572-834X
Online Access:Get full text
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Summary: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.
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ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-024-11710-2