Abstract
Load-balancing optimization in software-defined networking (SDN) has been researched for a long time. Researchers have proposed many solutions to the load-balancing problem but have rarely considered the impact of transmission delay between controllers and switches under high-load network conditions. In this paper, we propose an adaptive load-balancing architecture based on link-state prediction (ALBLP) in SDN that can solve the influence of transmission delay between controllers and switches on network load balancing. ALBLP constructs the prediction model of the network link status, adopts the long-term and short-term memory neural network (LSTM) algorithm to predict the network link-state value, and then uses the predicted value as the Dijkstra weight to calculate the optimal path between network hosts. The proposed architecture can adaptively optimize network load balancing and avoid the empty window period, in which the switch flow table does not exist by actively issuing the flow table. Under the network architecture, we collect the data set of the network link-state by simulating the GÉANT network, and we verify the effectiveness of the proposed algorithm. The experiment results show that the ALBLP proposed in this paper can optimize load balancing in SDN and solve the problem of transmission delay between controllers and switches. It has a maximum load-balancing improvement of 23.7% and 11.7% in comparison with the traditional Open Shortest Path First (OSPF) algorithm and the reinforcement learning method based on Q-Learning.
Highlights
In recent years, we have seen the rapid development of the Internet and an increasing growth in the prominence of its scale. e popularity of social media, high-definition movies, and online games has caused network traffic to grow rapidly
We propose an adaptive load-balancing architecture based on dynamic link-state prediction (ALBLP) in Softwaredefined networking (SDN) that can solve the influence on network load balancing of transmission delay between controllers and switches
In SDN, the load-balancing factor describes the relative degree of network link utilization. e forwarding of the same length of a data packet may cause a difference in network throughput due to the link bottleneck in the forwarding path [29]. erefore, we describe the network throughput as Network throughput (Nt)-shown in equation (10), where Hi is the amount of traffic received by host i in the data plane, and LH is the number of hosts. e network throughput is a measure of the carrying capacity of the data plane: LH
Summary
We have seen the rapid development of the Internet and an increasing growth in the prominence of its scale. e popularity of social media, high-definition movies, and online games has caused network traffic to grow rapidly. Wireless Communications and Mobile Computing between the network link status information acquired by the controller and the current After these delays, the current link-state value may have changed, causing the issued flow table not to use network resources effectively. The current link-state value may have changed, causing the issued flow table not to use network resources effectively It may increase network congestion under high-load conditions. We propose an adaptive load-balancing architecture based on dynamic link-state prediction (ALBLP) in SDN that can solve the influence on network load balancing of transmission delay between controllers and switches.
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