Changhua Pei, Youjian Zhao, Yunxin Liu, Kun Tan, Jiansong Zhang, Yuan Meng, Dan Pei
{"title":"密集WiFi网络中基于延迟的空中WiFi拥塞控制","authors":"Changhua Pei, Youjian Zhao, Yunxin Liu, Kun Tan, Jiansong Zhang, Yuan Meng, Dan Pei","doi":"10.1109/IWQoS.2017.7969113","DOIUrl":null,"url":null,"abstract":"WiFi has become the primary method to access the Internet. However, the WiFi-hop latency, particularly in dense-WiFi environments, is far from satisfactory [1], to support delay-sensitive applications such as Web browsing and VoIP. The WiFi latency mainly comes from two kinds of queues: the host queue and the distributed queue, which is caused by CSMA/CA mechanism when multiple nodes contend for the channel. While the host queue can be easily bypassed using priority scheduling at end-host, the distributed queue is not. Previously, IEEE 802.11e tries to provide priorities in this distributed queue by adjusting the MAC layer parameters, but it does not scale when there are increasing number of delay-sensitive flows. In this paper, we propose and design QAir, a practical solution to reduce WiFi latency of delay-sensitive flows in dense WiFi networks. QAir takes a different approach to transfer this distributed queue to host queue. Consequently, the delay-sensitive flows can bypass the entire queue and their latency can be greatly reduced. QAir works in a distributed manner with no centralized scheduler. We have implemented QAir on commodity WiFi devices. Experimental results show that, compared to the 802.11 DCF baseline, QAir can reduce the average WiFi-hop latency of delay-sensitive flows by 50–75%.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Latency-based WiFi congestion control in the air for dense WiFi networks\",\"authors\":\"Changhua Pei, Youjian Zhao, Yunxin Liu, Kun Tan, Jiansong Zhang, Yuan Meng, Dan Pei\",\"doi\":\"10.1109/IWQoS.2017.7969113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"WiFi has become the primary method to access the Internet. However, the WiFi-hop latency, particularly in dense-WiFi environments, is far from satisfactory [1], to support delay-sensitive applications such as Web browsing and VoIP. The WiFi latency mainly comes from two kinds of queues: the host queue and the distributed queue, which is caused by CSMA/CA mechanism when multiple nodes contend for the channel. While the host queue can be easily bypassed using priority scheduling at end-host, the distributed queue is not. Previously, IEEE 802.11e tries to provide priorities in this distributed queue by adjusting the MAC layer parameters, but it does not scale when there are increasing number of delay-sensitive flows. In this paper, we propose and design QAir, a practical solution to reduce WiFi latency of delay-sensitive flows in dense WiFi networks. QAir takes a different approach to transfer this distributed queue to host queue. Consequently, the delay-sensitive flows can bypass the entire queue and their latency can be greatly reduced. QAir works in a distributed manner with no centralized scheduler. We have implemented QAir on commodity WiFi devices. Experimental results show that, compared to the 802.11 DCF baseline, QAir can reduce the average WiFi-hop latency of delay-sensitive flows by 50–75%.\",\"PeriodicalId\":422861,\"journal\":{\"name\":\"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWQoS.2017.7969113\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2017.7969113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Latency-based WiFi congestion control in the air for dense WiFi networks
WiFi has become the primary method to access the Internet. However, the WiFi-hop latency, particularly in dense-WiFi environments, is far from satisfactory [1], to support delay-sensitive applications such as Web browsing and VoIP. The WiFi latency mainly comes from two kinds of queues: the host queue and the distributed queue, which is caused by CSMA/CA mechanism when multiple nodes contend for the channel. While the host queue can be easily bypassed using priority scheduling at end-host, the distributed queue is not. Previously, IEEE 802.11e tries to provide priorities in this distributed queue by adjusting the MAC layer parameters, but it does not scale when there are increasing number of delay-sensitive flows. In this paper, we propose and design QAir, a practical solution to reduce WiFi latency of delay-sensitive flows in dense WiFi networks. QAir takes a different approach to transfer this distributed queue to host queue. Consequently, the delay-sensitive flows can bypass the entire queue and their latency can be greatly reduced. QAir works in a distributed manner with no centralized scheduler. We have implemented QAir on commodity WiFi devices. Experimental results show that, compared to the 802.11 DCF baseline, QAir can reduce the average WiFi-hop latency of delay-sensitive flows by 50–75%.