Load Balancing Oriented Predictive Routing Algorithm for Data Center Networks

Yazhi Liu, Jiye Zhang, Wei Li, Qianqian Wu and Pengmiao Li
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Yazhi Liu: Department of Computer Science and Technology, North China University of Science and Technology, Tangshan 063000, China
Jiye Zhang: Department of Computer Science and Technology, North China University of Science and Technology, Tangshan 063000, China
Wei Li: Department of Computer Science and Technology, North China University of Science and Technology, Tangshan 063000, China
Qianqian Wu: Department of Computer Science and Technology, North China University of Science and Technology, Tangshan 063000, China
Pengmiao Li: Department of Computer Science and Technology, North China University of Science and Technology, Tangshan 063000, China

Future Internet, 2021, vol. 13, issue 2, 1-13

Abstract: A data center undertakes increasing background services of various applications, and the data flows transmitted between the nodes in data center networks (DCNs) are consequently increased. At the same time, the traffic of each link in a DCN changes dynamically over time. Flow scheduling algorithms can improve the distribution of data flows among the network links so as to improve the balance of link loads in a DCN. However, most current load balancing works achieve flow scheduling decisions to the current links on the basis of past link flow conditions. This situation impedes the existing link scheduling methods from implementing optimal decisions for scheduling data flows among the network links in a DCN. This paper proposes a predictive link load balance routing algorithm for a DCN based on residual networks (ResNet), i.e., the link load balance route (LLBR) algorithm. The LLBR algorithm predicts the occupancy of the network links in the next duty cycle, according to the ResNet architecture, and then the optimal traffic route is selected according to the predictive network environment. The LLBR algorithm, round-robin scheduling (RRS), and weighted round-robin scheduling (WRRS) are used in the same experimental environment. Experimental results show that compared with the WRRS and RRS, the LLBR algorithm can reduce the transmission time by approximately 50%, reduce the packet loss rate from 0.05% to 0.02%, and improve the bandwidth utilization by 30%.

Keywords: ResNet; data center network; load balancing; traffic scheduling (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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