计算机科学
有状态防火墙
试验台
负载平衡(电力)
可扩展性
数据中心
网络数据包
云计算
分布式计算
计算机网络
前进飞机
提供的负载
GSM演进的增强数据速率
吞吐量
操作系统
网格
电信
数学
几何学
无线
作者
Ashkan Aghdai,Cing-Yu Chu,Yang Xu,David Dai,Jun Xu,H. Jonathan Chao
出处
期刊:IEEE Transactions on Cloud Computing
[Institute of Electrical and Electronics Engineers]
日期:2022-07-01
卷期号:10 (3): 2131-2145
被引量:9
标识
DOI:10.1109/tcc.2020.3024834
摘要
Load Balancing plays a vital role in cloud data centers to distribute traffic among instances of network functions or services. State-of-the-art load balancers dispatch traffic obliviously without considering the real-time utilization of service instances and therefore can lead to uneven load distribution and sub-optimal performance. In this article, we design and implement Spotlight, a scalable and distributed load balancing architecture that maintains connection-to-instance mapping consistency at the edge of data center networks. Spotlight uses a new stateful flow dispatcher which periodically polls instances’ load and dispatches incoming connections to instances in proportion to their available capacity. Our design utilizes a distributed control plane and in-band flow dispatching; thus, it scales horizontally in data center networks. Through extensive flow-level simulation and packet-level experiments on a testbed with HTTP traffic on unmodified Linux kernel, we demonstrate that compared to existing methods Spotlight distributes traffic more efficiently and has near-optimum performance in terms of overall service utilization. Compared to existing solutions, Spotlight improves aggregated throughput and average flow completion time by at least 20 percent with infrequent control plane updates. Moreover, we show that Spotlight scales horizontally as it updates the switches at O(100ms) and is resilient to lack of control plane convergence.
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