{"title":"队列比例抽样:一种更好的输入排队交换机交叉排程方法","authors":"Long Gong, Paul Tune, Liang Liu, Sen Yang, Jun Xu","doi":"10.1145/3078505.3078509","DOIUrl":null,"url":null,"abstract":"Most present day switching systems, in Internet routers and data-center switches, employ a single input-queued crossbar to interconnect input ports with output ports. Such switches need to compute a matching, between input and output ports, for each switching cycle (time slot). The main challenge in designing such matching algorithms is to deal with the unfortunate tradeoff between the quality of the computed matching and the computational complexity of the algorithm. In this paper, we propose a general approach that can significantly boost the performance of both SERENA and iSLIP, yet incurs only O(1) additional computational complexity at each input/output port. Our approach is a novel proposing strategy, called Queue-Proportional Sampling (QPS), that generates an excellent starter matching. We show, through rigorous simulations, that when starting with this starter matching, iSLIP and SERENA can output much better final matching decisions, as measured by the resulting throughput and delay performance, than they otherwise can.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Queue-Proportional Sampling: A Better Approach to Crossbar Scheduling for Input-Queued Switches\",\"authors\":\"Long Gong, Paul Tune, Liang Liu, Sen Yang, Jun Xu\",\"doi\":\"10.1145/3078505.3078509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most present day switching systems, in Internet routers and data-center switches, employ a single input-queued crossbar to interconnect input ports with output ports. Such switches need to compute a matching, between input and output ports, for each switching cycle (time slot). The main challenge in designing such matching algorithms is to deal with the unfortunate tradeoff between the quality of the computed matching and the computational complexity of the algorithm. In this paper, we propose a general approach that can significantly boost the performance of both SERENA and iSLIP, yet incurs only O(1) additional computational complexity at each input/output port. Our approach is a novel proposing strategy, called Queue-Proportional Sampling (QPS), that generates an excellent starter matching. We show, through rigorous simulations, that when starting with this starter matching, iSLIP and SERENA can output much better final matching decisions, as measured by the resulting throughput and delay performance, than they otherwise can.\",\"PeriodicalId\":133673,\"journal\":{\"name\":\"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3078505.3078509\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3078505.3078509","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Queue-Proportional Sampling: A Better Approach to Crossbar Scheduling for Input-Queued Switches
Most present day switching systems, in Internet routers and data-center switches, employ a single input-queued crossbar to interconnect input ports with output ports. Such switches need to compute a matching, between input and output ports, for each switching cycle (time slot). The main challenge in designing such matching algorithms is to deal with the unfortunate tradeoff between the quality of the computed matching and the computational complexity of the algorithm. In this paper, we propose a general approach that can significantly boost the performance of both SERENA and iSLIP, yet incurs only O(1) additional computational complexity at each input/output port. Our approach is a novel proposing strategy, called Queue-Proportional Sampling (QPS), that generates an excellent starter matching. We show, through rigorous simulations, that when starting with this starter matching, iSLIP and SERENA can output much better final matching decisions, as measured by the resulting throughput and delay performance, than they otherwise can.