Volume 32, Issue 16 e5222
SPECIAL ISSUE PAPER

LBBESA: An efficient software-defined networking load-balancing scheme based on elevator scheduling algorithm

Qiliang Li

Qiliang Li

School of Computer Science and Technology, Anhui University, Hefei, China

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Jie Cui

Corresponding Author

Jie Cui

School of Computer Science and Technology, Anhui University, Hefei, China

Jie Cui, School of Computer Science and Technology, Anhui University, Hefei 230039, China.

Email: [email protected]

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Hong Zhong

Hong Zhong

School of Computer Science and Technology, Anhui University, Hefei, China

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Yichao Du

Yichao Du

School of Computer Science and Technology, Anhui University, Hefei, China

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Yonglong Luo

Yonglong Luo

Anhui Provincial Key Laboratory of Network and Information Security, Wuhu, China

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Lu Liu

Lu Liu

School of Electronics, Computing and Mathematics, University of Derby, Derby DE22 1GB, UK

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First published: 18 March 2019
Citations: 4

Summary

Elevator scheduling algorithms generally denote methods used to calculate how to use the elevator. These algorithms can distribute elevators to various floors of a building, thereby achieving efficient transportation. From the perspective of the elevator scheduling problem, we address the load-balancing problem for software-defined networking (SDN) architecture and propose a load-balancing method based on the elevator scheduling algorithm, LBBESA. We take advantage of the flexibility of the SDN architecture, obtain the real-time load of the server through real-time statistical analyses of the SDN switch port traffic by the controller, and combine this with the idea of regional elevator allocation to coordinate the connection of the client's requests and realize the load balancing of each server in the cluster. Simulation experiments show that, compared with the round-robin algorithm, LBBESA is more effective in the load balancing of the server pool and can improve the throughput of the server pool to a certain extent. In addition, our scheme is easy to implement and has high scalability.

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