{"title":"数据中心中软件定义的任务级截止日期感知抢占式流调度","authors":"Lili Liu, Dan Li, Jianping Wu","doi":"10.1109/ICPP.2015.75","DOIUrl":null,"url":null,"abstract":"Many data center applications have deadline requirements, which pose a requirement of deadline-awareness in network transport. Completing within deadlines is a necessary requirement for flows to be completed. Transport protocols in current data centers try to share the network resources fairly and are deadline-agnostic. Recently several works try to address the problem by making as many flows meet deadlines as possible. However, for many data center applications, a task cannot be completed until the last flow finishes, which indicates the bandwidths consumed by completed flows are wasted if some flows in the task cannot meet deadlines. In this paper we design a task-level deadline-aware preemptive flow scheduling(TAPS), which aims to make more tasks meet deadlines. We leverage software defined networking (SDN) technology and generalize SDN from flow-level awareness to task-level awareness. The scheduling algorithm runs on the SDN controller, which decides whether a flow should be accepted or discarded, pre-allocates the transmission time slices and computes the routing paths for accepted flows. Extensive flow-level simulations demonstrate TAPS outperforms Varys, Bara at, PDQ (Preemptive Distributed Quick flow scheduling), D3 (Deadline-Driven Delivery control protocol) and Fair Sharing transport protocols in deadline sensitive data center environment. A simple implementation on real systems also proves that TAPS makes high effective utilization of the network bandwidth in data centers.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"TAPS: Software Defined Task-Level Deadline-Aware Preemptive Flow Scheduling in Data Centers\",\"authors\":\"Lili Liu, Dan Li, Jianping Wu\",\"doi\":\"10.1109/ICPP.2015.75\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many data center applications have deadline requirements, which pose a requirement of deadline-awareness in network transport. Completing within deadlines is a necessary requirement for flows to be completed. Transport protocols in current data centers try to share the network resources fairly and are deadline-agnostic. Recently several works try to address the problem by making as many flows meet deadlines as possible. However, for many data center applications, a task cannot be completed until the last flow finishes, which indicates the bandwidths consumed by completed flows are wasted if some flows in the task cannot meet deadlines. In this paper we design a task-level deadline-aware preemptive flow scheduling(TAPS), which aims to make more tasks meet deadlines. We leverage software defined networking (SDN) technology and generalize SDN from flow-level awareness to task-level awareness. The scheduling algorithm runs on the SDN controller, which decides whether a flow should be accepted or discarded, pre-allocates the transmission time slices and computes the routing paths for accepted flows. Extensive flow-level simulations demonstrate TAPS outperforms Varys, Bara at, PDQ (Preemptive Distributed Quick flow scheduling), D3 (Deadline-Driven Delivery control protocol) and Fair Sharing transport protocols in deadline sensitive data center environment. A simple implementation on real systems also proves that TAPS makes high effective utilization of the network bandwidth in data centers.\",\"PeriodicalId\":423007,\"journal\":{\"name\":\"2015 44th International Conference on Parallel Processing\",\"volume\":\"147 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 44th International Conference on Parallel Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPP.2015.75\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 44th International Conference on Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.2015.75","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TAPS: Software Defined Task-Level Deadline-Aware Preemptive Flow Scheduling in Data Centers
Many data center applications have deadline requirements, which pose a requirement of deadline-awareness in network transport. Completing within deadlines is a necessary requirement for flows to be completed. Transport protocols in current data centers try to share the network resources fairly and are deadline-agnostic. Recently several works try to address the problem by making as many flows meet deadlines as possible. However, for many data center applications, a task cannot be completed until the last flow finishes, which indicates the bandwidths consumed by completed flows are wasted if some flows in the task cannot meet deadlines. In this paper we design a task-level deadline-aware preemptive flow scheduling(TAPS), which aims to make more tasks meet deadlines. We leverage software defined networking (SDN) technology and generalize SDN from flow-level awareness to task-level awareness. The scheduling algorithm runs on the SDN controller, which decides whether a flow should be accepted or discarded, pre-allocates the transmission time slices and computes the routing paths for accepted flows. Extensive flow-level simulations demonstrate TAPS outperforms Varys, Bara at, PDQ (Preemptive Distributed Quick flow scheduling), D3 (Deadline-Driven Delivery control protocol) and Fair Sharing transport protocols in deadline sensitive data center environment. A simple implementation on real systems also proves that TAPS makes high effective utilization of the network bandwidth in data centers.