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11th International Conference on Computer and Knowledge Engineering
Hybrid Flow-Rule Placement Method of Proactive and Reactive in SDNs
Authors :
Mohammadreza Khoobbakht
1
Mohammadreza Noei
2
Mohammadreza Parvizimosaed
3
1- Khajeh Nasir Toosi University of Technology
2- Tarbiat Modares University
3- Khajeh Nasir Toosi University of Technology
Keywords :
Software-Defined Network (SDN); Flow Table, Proactive Network, Reactive Network, Controller Load formatting
Abstract :
In a software-defined network, the controller is an important element based on its effect on the entire network performance. The centralized controller property will lead to flexibility and reliability in network management; however, limitations in network resources such as switches’ limited flow table size and controller processing capacity may reduce network performance and increase controller response time. In this paper, we present a hybrid rule placement model for reducing the load on the controller. The proposed method solves the load problem by formulating the table size limitation and then combining the reactive and proactive methods in flow-rule placement algorithm. The main idea of this method is to make optimal use of switches’ limited flow table to reduce the signaling overhead on the controller, which leads to reduces the network reaction time to changes and the load on the controller. To achieve this goal, the proposed method prevents the sending of packets to the controller by installing Star rules on the switches. Finally, the proposed method implements and tests on a real network, and the results of simulation and evaluation of network performance have reduced the amount of load on the controller by 20 to 50%, which indicates the effectiveness of the proposed method.
Papers List
List of archived papers
Hybrid Flow-Rule Placement Method of Proactive and Reactive in SDNs
Mohammadreza Khoobbakht - Mohammadreza Noei - Mohammadreza Parvizimosaed
Bridging the Synthetic-to-Real Gap (BSRG): Creating Simulated Datasets for Domain Adaptation to Enhance Vehicle Detection
Behnaz Sadeghigol - Mohammad Ali Keyvanrad
DFIG-WECS Renewable Integration to the Grid and Stability Improvement through Optimal Damping Controller Design
Theophilus Ebuka Odoh - Aliyu Sabo - Hossien Shahinzadeh - Noor Izzri Abdul Wahab - Farshad Ebrahimi
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm
Zaniar Sharifi - Khabat Soltanian - Ali Amiri
Optimization Resource Allocation in NOMA-based Fog Computing with a Hybrid Algorithm
Zohreh Torki - S.Mojtaba Matinkhah
FAHP-OF: A New Method for Load Balancing in RPL-based Internet of Things (IoT)
Mohammad Koosha - Behnam Farzaneh - Emad Alizadeh - Shahin Farzaneh
Blind image quality assessment based on Multi-resolution Local Structures
Seyed Majid Khorashadizadeh - Mehdi Sadeghi Bakhi - Fatemeh Seifishahpar - AliMohammad Latif
Effect of Tissue Excitation in Breast Cancer Detection from Ultrasound RF Time Series: Phantom studies
Elaheh Norouzi Ghehi - Ali Fallah - Saeid Rashidi - Maryam Mehdizadeh Dastjerdi
Optimal PMU Placement Considering Reliability of Measurement System in Smart Grids
Mohammad Shahraeini - Shahla Khormali - Ahad Alvandi
ROCT-Net: A new ensemble deep convolutional model with improved spatial resolution learning for detecting common diseases from retinal OCT images
Mohammad Rahimzadeh - Mahmoud Reza Mohammadi
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