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Hai Xue
Department of Electronic, Electrical and Computer Engineering, Sungkyunkwan University, (16419) 2066, Seobu-Ro, Jangan-Gu, Suwon-Si, Gyeonggi-Do, Korea.

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Journal article
Published: 14 January 2019 in Sensors
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Load Balancing (LB) is one of the most important tasks required to maximize network performance, scalability and robustness. Nowadays, with the emergence of Software-Defined Networking (SDN), LB for SDN has become a very important issue. SDN decouples the control plane from the data forwarding plane to implement centralized control of the whole network. LB assigns the network traffic to the resources in such a way that no one resource is overloaded and therefore the overall performance is maximized. The Ant Colony Optimization (ACO) algorithm has been recognized to be effective for LB of SDN among several existing optimization algorithms. The convergence latency and searching optimal solution are the key criteria of ACO. In this paper, a novel dynamic LB scheme that integrates genetic algorithm (GA) with ACO for further enhancing the performance of SDN is proposed. It capitalizes the merit of fast global search of GA and efficient search of an optimal solution of ACO. Computer simulation results show that the proposed scheme substantially improves the Round Robin and ACO algorithm in terms of the rate of searching optimal path, round trip time, and packet loss rate.

ACS Style

Hai Xue; Kyung Tae Kim; Hee Yong Youn. Dynamic Load Balancing of Software-Defined Networking Based on Genetic-Ant Colony Optimization. Sensors 2019, 19, 311 .

AMA Style

Hai Xue, Kyung Tae Kim, Hee Yong Youn. Dynamic Load Balancing of Software-Defined Networking Based on Genetic-Ant Colony Optimization. Sensors. 2019; 19 (2):311.

Chicago/Turabian Style

Hai Xue; Kyung Tae Kim; Hee Yong Youn. 2019. "Dynamic Load Balancing of Software-Defined Networking Based on Genetic-Ant Colony Optimization." Sensors 19, no. 2: 311.

Research article
Published: 18 November 2018 in Wireless Communications and Mobile Computing
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Software-defined networking (SDN) decouples the control plane and data forwarding plane to overcome the limitations of traditional networking infrastructure. Among several communication protocols employed for SDN, OpenFlow is most widely used for the communication between the controller and switch. In this paper two packet scheduling schemes, FCFS-Pushout (FCFS-PO) and FCFS-Pushout-Priority (FCFS-PO-P), are proposed to effectively handle the overload issue of multiple-switch SDN targeting the edge computing environment. Analytical models on their operations are developed, and extensive experiment based on a testbed is carried out to evaluate the schemes. They reveal that both of them are better than the typical FCFS-Block (FCFS-BL) scheduling algorithm in terms of packet wait time. Furthermore, FCFS-PO-P is found to be more effective than FCFS-PO in the edge computing environment.

ACS Style

Hai Xue; Kyung Tae Kim; Hee Yong Youn. Packet Scheduling for Multiple-Switch Software-Defined Networking in Edge Computing Environment. Wireless Communications and Mobile Computing 2018, 2018, 1 -11.

AMA Style

Hai Xue, Kyung Tae Kim, Hee Yong Youn. Packet Scheduling for Multiple-Switch Software-Defined Networking in Edge Computing Environment. Wireless Communications and Mobile Computing. 2018; 2018 ():1-11.

Chicago/Turabian Style

Hai Xue; Kyung Tae Kim; Hee Yong Youn. 2018. "Packet Scheduling for Multiple-Switch Software-Defined Networking in Edge Computing Environment." Wireless Communications and Mobile Computing 2018, no. : 1-11.