Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651986
Yiran Lei, Yu Zhou, Yunsenxiao Lin, Mingwei Xu, Yangyang Wang
Service-level objectives (SLOs), as network performance requirements for delay and packet loss typically, should be guaranteed for increasing high-performance applications, e.g., telesurgery and cloud gaming. However, SLO violations are common and destructive in today’s network operation. Detection and diagnosis, meaning monitoring performance to discover anomalies and analyzing causality of SLO violations respectively, are crucial for fast recovery. Unfortunately, existing diagnosis approaches require exhaustive causal information to function. Meanwhile, existing detection tools incur large overhead or are only able to provide limited information for diagnosis. This paper presents DOVE, a diagnosis-driven SLO detection system with high accuracy and low overhead. The key idea is to identify and report the information needed by diagnosis along with SLO violation alerts from the data plane selectively and efficiently. Network segmentation is introduced to balance scalability and accuracy. Novel algorithms to measure packet loss and percentile delay are implemented completely on the data plane without the involvement of the control plane for fine-grained SLO detection. We implement and deploy DOVE on Tofino and P4 software switch (BMv2) and show the effectiveness of DOVE with a use case. The reported SLO violation alerts and diagnosis-needing information are compared with ground truth and show high accuracy (>97%). Our evaluation also shows that DOVE introduces up to two orders of magnitude less traffic overhead than NetSight. In addition, memory utilization and required processing ability are low to be deployable in real network topologies.
{"title":"DOVE: Diagnosis-driven SLO Violation Detection","authors":"Yiran Lei, Yu Zhou, Yunsenxiao Lin, Mingwei Xu, Yangyang Wang","doi":"10.1109/ICNP52444.2021.9651986","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651986","url":null,"abstract":"Service-level objectives (SLOs), as network performance requirements for delay and packet loss typically, should be guaranteed for increasing high-performance applications, e.g., telesurgery and cloud gaming. However, SLO violations are common and destructive in today’s network operation. Detection and diagnosis, meaning monitoring performance to discover anomalies and analyzing causality of SLO violations respectively, are crucial for fast recovery. Unfortunately, existing diagnosis approaches require exhaustive causal information to function. Meanwhile, existing detection tools incur large overhead or are only able to provide limited information for diagnosis. This paper presents DOVE, a diagnosis-driven SLO detection system with high accuracy and low overhead. The key idea is to identify and report the information needed by diagnosis along with SLO violation alerts from the data plane selectively and efficiently. Network segmentation is introduced to balance scalability and accuracy. Novel algorithms to measure packet loss and percentile delay are implemented completely on the data plane without the involvement of the control plane for fine-grained SLO detection. We implement and deploy DOVE on Tofino and P4 software switch (BMv2) and show the effectiveness of DOVE with a use case. The reported SLO violation alerts and diagnosis-needing information are compared with ground truth and show high accuracy (>97%). Our evaluation also shows that DOVE introduces up to two orders of magnitude less traffic overhead than NetSight. In addition, memory utilization and required processing ability are low to be deployable in real network topologies.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125869293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/icnp52444.2021.9651933
{"title":"Welcome Message from the ICNP 2021 TPC Chairs","authors":"","doi":"10.1109/icnp52444.2021.9651933","DOIUrl":"https://doi.org/10.1109/icnp52444.2021.9651933","url":null,"abstract":"","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130147487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651964
Yunzhi Lin, Shouxi Luo
To achieve efficient model multicast for cross-device Federated Learning (FL) over shared wireless channels, we propose SRMP, a transport protocol that performs semi-reliable model multicast over the air by leveraging existing PHY-aided wireless multicast techniques. The preliminary study shows that, with novel designs, SRMP could reduce the communication time involved in each round of training significantly.
{"title":"Poster: Accelerate Cross-Device Federated Learning With Semi-Reliable Model Multicast Over The Air","authors":"Yunzhi Lin, Shouxi Luo","doi":"10.1109/ICNP52444.2021.9651964","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651964","url":null,"abstract":"To achieve efficient model multicast for cross-device Federated Learning (FL) over shared wireless channels, we propose SRMP, a transport protocol that performs semi-reliable model multicast over the air by leveraging existing PHY-aided wireless multicast techniques. The preliminary study shows that, with novel designs, SRMP could reduce the communication time involved in each round of training significantly.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116490447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651954
Radhika Sukapuram, Ranjan Patowary, G. Barua
Network Functions (NFs) provide security and optimization services to networks by examining and modifying packets and by collecting information. When NFs need to be scaled out to manage higher load or scaled in to conserve energy, flows need to be migrated from one instance of an NF, called the source instance, to another, called the destination instance, or from one chain of instances to another chain of instances. Before flows are migrated, the state information associated with the source instance needs to be migrated to the destination instance. Packets that arrive at the destination instance meanwhile need to be either buffered or dropped until the state information is migrated, for correct functioning of some stateful NFs, while for some others, the destination NF may continue to function. We define the properties of Loss-freedom, where the flow migration system does not drop packets, No-buffering, where it does not buffer packets, and Order-preservation, where it processes packets in the same manner as the source NF, if there was no flow migration. We formalize these properties, for the first time, and prove that it is impossible for a flow migration algorithm in stateful NFs to guarantee satisfying all three of the properties of Loss-freedom (L), Order-preservation (O) and No-buffering (N) during flow migration, even if messages or packets are not lost. We demonstrate how existing algorithms operate with regard to these properties and prove that these properties are compositional.
{"title":"Loss-freedom, Order-preservation and No-buffering: Pick Any Two During Flow Migration in Network Functions","authors":"Radhika Sukapuram, Ranjan Patowary, G. Barua","doi":"10.1109/ICNP52444.2021.9651954","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651954","url":null,"abstract":"Network Functions (NFs) provide security and optimization services to networks by examining and modifying packets and by collecting information. When NFs need to be scaled out to manage higher load or scaled in to conserve energy, flows need to be migrated from one instance of an NF, called the source instance, to another, called the destination instance, or from one chain of instances to another chain of instances. Before flows are migrated, the state information associated with the source instance needs to be migrated to the destination instance. Packets that arrive at the destination instance meanwhile need to be either buffered or dropped until the state information is migrated, for correct functioning of some stateful NFs, while for some others, the destination NF may continue to function. We define the properties of Loss-freedom, where the flow migration system does not drop packets, No-buffering, where it does not buffer packets, and Order-preservation, where it processes packets in the same manner as the source NF, if there was no flow migration. We formalize these properties, for the first time, and prove that it is impossible for a flow migration algorithm in stateful NFs to guarantee satisfying all three of the properties of Loss-freedom (L), Order-preservation (O) and No-buffering (N) during flow migration, even if messages or packets are not lost. We demonstrate how existing algorithms operate with regard to these properties and prove that these properties are compositional.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126714577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651973
Sahil Gupta, D. Gosain, Garegin Grigoryan, Minseok Kwon, H. B. Acharya
The P4 language allows "protocol-independent packet parsing" in network switches, and makes many operations possible in the data plane. But P4 is not built for Deep Packet Inspection – it can only "parse" well-defined packet headers, not free-form headers as seen in HTTPS etc. Thus some very important use cases, such as application-layer firewalls, are considered impossible for P4. This demonstration shows that this limitation is not strictly true: switches, that support only standard P4, are able to independently perform tasks such as blocking specific URLs (without using non-standard "extern" components, help from the SDN controller, or rerouting to a firewall). As more Internet infrastructure becomes SDN-compatible, in future, switches may perform simple application-layer firewall tasks.
{"title":"Demo: Simple Deep Packet Inspection with P4","authors":"Sahil Gupta, D. Gosain, Garegin Grigoryan, Minseok Kwon, H. B. Acharya","doi":"10.1109/ICNP52444.2021.9651973","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651973","url":null,"abstract":"The P4 language allows \"protocol-independent packet parsing\" in network switches, and makes many operations possible in the data plane. But P4 is not built for Deep Packet Inspection – it can only \"parse\" well-defined packet headers, not free-form headers as seen in HTTPS etc. Thus some very important use cases, such as application-layer firewalls, are considered impossible for P4. This demonstration shows that this limitation is not strictly true: switches, that support only standard P4, are able to independently perform tasks such as blocking specific URLs (without using non-standard \"extern\" components, help from the SDN controller, or rerouting to a firewall). As more Internet infrastructure becomes SDN-compatible, in future, switches may perform simple application-layer firewall tasks.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127752279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651935
Xizheng Wang, Guo Chen, Xijin Yin, Huichen Dai, Bojie Li, Binzhang Fu, Kun Tan
Due to its superior performance, Remote Direct Memory Access (RDMA) has been widely deployed in data center networks. It provides applications with ultra-high throughput, ultra-low latency, and far lower CPU utilization than TCP/IP software network stack. However, the connection states that must be stored on the RDMA NIC (RNIC) and the small NIC memory result in poor scalability. The performance drops significantly when the RNIC needs to maintain a large number of concurrent connections.We propose StaR (Stateless RDMA), which solves the scalability problem of RDMA by transferring states to the other communication end. Leveraging the asymmetric communication pattern in data center applications, StaR lets the communication end with low concurrency save states for the other end with high concurrency, thus making the RNIC on the bottleneck side to be stateless. We have implemented StaR on an FPGA board with 10Gbps network port and evaluated its performance on a testbed with 9 machines all equipped with StaR NICs. The experimental results show that in high concurrency scenarios, the throughput of StaR can reach up to 4.13x and 1.35x of the original RNIC and the latest software-based solution, respectively.
RDMA (Remote Direct Memory Access)由于其优越的性能，在数据中心网络中得到了广泛的应用。它为应用程序提供了比TCP/IP软件网络堆栈更高的吞吐量、更低的延迟和更低的CPU利用率。但是，必须存储在RDMA网卡(RNIC)上的连接状态和较小的网卡内存导致可扩展性较差。当RNIC需要维护大量并发连接时，性能会明显下降。我们提出了StaR(无状态RDMA)，它通过向另一端传输状态来解决RDMA的可扩展性问题。利用数据中心应用程序中的非对称通信模式，StaR允许具有低并发性的通信端为具有高并发性的另一端保存状态，从而使瓶颈端的RNIC处于无状态状态。我们在带有10Gbps网络端口的FPGA板上实现了StaR，并在配备StaR网卡的9台机器的测试台上对其性能进行了评估。实验结果表明，在高并发场景下，StaR的吞吐量分别可以达到原始RNIC和最新基于软件的解决方案的4.13倍和1.35倍。
{"title":"StaR: Breaking the Scalability Limit for RDMA","authors":"Xizheng Wang, Guo Chen, Xijin Yin, Huichen Dai, Bojie Li, Binzhang Fu, Kun Tan","doi":"10.1109/ICNP52444.2021.9651935","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651935","url":null,"abstract":"Due to its superior performance, Remote Direct Memory Access (RDMA) has been widely deployed in data center networks. It provides applications with ultra-high throughput, ultra-low latency, and far lower CPU utilization than TCP/IP software network stack. However, the connection states that must be stored on the RDMA NIC (RNIC) and the small NIC memory result in poor scalability. The performance drops significantly when the RNIC needs to maintain a large number of concurrent connections.We propose StaR (Stateless RDMA), which solves the scalability problem of RDMA by transferring states to the other communication end. Leveraging the asymmetric communication pattern in data center applications, StaR lets the communication end with low concurrency save states for the other end with high concurrency, thus making the RNIC on the bottleneck side to be stateless. We have implemented StaR on an FPGA board with 10Gbps network port and evaluated its performance on a testbed with 9 machines all equipped with StaR NICs. The experimental results show that in high concurrency scenarios, the throughput of StaR can reach up to 4.13x and 1.35x of the original RNIC and the latest software-based solution, respectively.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"66 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133609501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651921
Haibo Wang, Tao Gao, Weizhen Dang, Jing’an Xue, Jiahao Cao, Fenghua Li, Jilong Wang
In recent years, more and more wireless networks support both 2.4GHz and 5GHz bands. However, in large-scale dual-band wireless networks, lack of understanding on the behavior and performance makes the network diagnosis and optimization extremely challenging. In this paper, we conduct a comprehensive measurement to characterize the behavior and performance in a large-scale dual-band wireless network (TD WLAN). We make several meaningful observations. (1) Although the 5GHz band outperforms the 2.4GHz band, 60% of devices tend to be associated with the 2.4GHz band. The device association behavior has a large impact on the performance. (2) Rogue and non-WiFi devices are prevalent, wherein hidden terminal interference increases the average loss rate by 8%, carrier sense interference increases the average WiFi latency by 45%, and RF interference further aggravates both packet loss and channel contention. (3) The dynamic channel assignment strategy is not always effective. On this basis, we propose a novel and easy-to-implement strategy to improve the wireless performance by intelligent band navigation and heuristic channel optimization. The actual deployment in TD WLAN shows the packet loss reduces by 40% on average and the WiFi latency for more than 60% of devices is below 5ms.
{"title":"Hopping on Spectrum: Measuring and Boosting a Large-scale Dual-band Wireless Network","authors":"Haibo Wang, Tao Gao, Weizhen Dang, Jing’an Xue, Jiahao Cao, Fenghua Li, Jilong Wang","doi":"10.1109/ICNP52444.2021.9651921","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651921","url":null,"abstract":"In recent years, more and more wireless networks support both 2.4GHz and 5GHz bands. However, in large-scale dual-band wireless networks, lack of understanding on the behavior and performance makes the network diagnosis and optimization extremely challenging. In this paper, we conduct a comprehensive measurement to characterize the behavior and performance in a large-scale dual-band wireless network (TD WLAN). We make several meaningful observations. (1) Although the 5GHz band outperforms the 2.4GHz band, 60% of devices tend to be associated with the 2.4GHz band. The device association behavior has a large impact on the performance. (2) Rogue and non-WiFi devices are prevalent, wherein hidden terminal interference increases the average loss rate by 8%, carrier sense interference increases the average WiFi latency by 45%, and RF interference further aggravates both packet loss and channel contention. (3) The dynamic channel assignment strategy is not always effective. On this basis, we propose a novel and easy-to-implement strategy to improve the wireless performance by intelligent band navigation and heuristic channel optimization. The actual deployment in TD WLAN shows the packet loss reduces by 40% on average and the WiFi latency for more than 60% of devices is below 5ms.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133279193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651965
Ruyi Yao, Cong Luo, Xuandong Liu, Ying Wan, B. Liu, Wen J. Li, Yang Xu
Ternary Content-Addressable Memory (TCAM) is a popular solution for high-speed flow table lookup in Software-Defined Networking (SDN). Rule insertion in TCAM is a time-consuming operation. To ensure semantic correctness, rules overlapped must be stored in TCAM with decreasing priority order and many rule movements may be needed to make space for a single inserted rule. When a rule insertion is in progress, the regular flow table lookup will be suspended, which could lead to a degraded user experience for SDN applications. In this paper, we propose a multiple-TCAM framework named MagicTCAM to reduce the rule movements during a rule insertion. The core of MagicTCAM lies in three operations: layering, partitioning and rotating. By layering, rules with the least overlapping will be grouped (i.e., layered) into a sub-ruleset. The number of rule movements is therefore greatly reduced as most of rules in a sub-ruleset are non-overlapped. To achieve balanced load in TCAMs, rules in each sub-ruleset are further partitioned and dispatched into different TCAMs in a rotating manner. In addition, an inter-TCAM movement algorithm is proposed to allow rules to be moved between TCAMs for reduced rule movement. Experiment results show that with two half-sized TCAMs, MagicTCAM reduces the rule movements by 39% on average compared with the state-of-the-art work while the computation time is shortened by half as well.
{"title":"MagicTCAM: A Multiple-TCAM Scheme for Fast TCAM Update","authors":"Ruyi Yao, Cong Luo, Xuandong Liu, Ying Wan, B. Liu, Wen J. Li, Yang Xu","doi":"10.1109/ICNP52444.2021.9651965","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651965","url":null,"abstract":"Ternary Content-Addressable Memory (TCAM) is a popular solution for high-speed flow table lookup in Software-Defined Networking (SDN). Rule insertion in TCAM is a time-consuming operation. To ensure semantic correctness, rules overlapped must be stored in TCAM with decreasing priority order and many rule movements may be needed to make space for a single inserted rule. When a rule insertion is in progress, the regular flow table lookup will be suspended, which could lead to a degraded user experience for SDN applications. In this paper, we propose a multiple-TCAM framework named MagicTCAM to reduce the rule movements during a rule insertion. The core of MagicTCAM lies in three operations: layering, partitioning and rotating. By layering, rules with the least overlapping will be grouped (i.e., layered) into a sub-ruleset. The number of rule movements is therefore greatly reduced as most of rules in a sub-ruleset are non-overlapped. To achieve balanced load in TCAMs, rules in each sub-ruleset are further partitioned and dispatched into different TCAMs in a rotating manner. In addition, an inter-TCAM movement algorithm is proposed to allow rules to be moved between TCAMs for reduced rule movement. Experiment results show that with two half-sized TCAMs, MagicTCAM reduces the rule movements by 39% on average compared with the state-of-the-art work while the computation time is shortened by half as well.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124765052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of datacenter applications leads to the need for end-to-end communication with microsecond latency. As a result, RDMA is becoming prevalent in datacenter networks to mitigate the latency caused by the slow processing speed of the traditional software network stack. However, existing RDMA congestion control mechanisms are either far from optimal in simultaneously achieving high throughput and low latency or in need of additional in-network function support. In this paper, by leveraging the observation that most congestion occurs at the last hop in datacenter networks, we propose RCC, a receiver-driven rapid congestion control mechanism for RDMA networks that combines explicit assignment and iterative window adjustment. Firstly, we propose a network congestion distinguish method to classify congestions into two types, last-hop congestion and innetwork congestion. Then, an Explicit Window Assignment mechanism is proposed to solve the last-hop congestion, which enables senders to converge to a proper sending rate in one-RTT. For in-network congestion, a PID-based iterative delay-based window adjustment scheme is proposed to achieve fast convergence and near-zero queuing latency. RCC does not need additional innetwork support and is friendly to hardware implementation. In our evaluation, the overall average FCT (Flow Completion Time) of RCC is 4~79% better than Homa, ExpressPass, DCQCN, TIMELY, and HPCC.
{"title":"Receiver-Driven RDMA Congestion Control by Differentiating Congestion Types in Datacenter Networks","authors":"Jiao Zhang, Jiaming Shi, Xiaolong Zhong, Zirui Wan, Yuxing Tian, Tian Pan, Tao Huang","doi":"10.1109/ICNP52444.2021.9651938","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651938","url":null,"abstract":"The development of datacenter applications leads to the need for end-to-end communication with microsecond latency. As a result, RDMA is becoming prevalent in datacenter networks to mitigate the latency caused by the slow processing speed of the traditional software network stack. However, existing RDMA congestion control mechanisms are either far from optimal in simultaneously achieving high throughput and low latency or in need of additional in-network function support. In this paper, by leveraging the observation that most congestion occurs at the last hop in datacenter networks, we propose RCC, a receiver-driven rapid congestion control mechanism for RDMA networks that combines explicit assignment and iterative window adjustment. Firstly, we propose a network congestion distinguish method to classify congestions into two types, last-hop congestion and innetwork congestion. Then, an Explicit Window Assignment mechanism is proposed to solve the last-hop congestion, which enables senders to converge to a proper sending rate in one-RTT. For in-network congestion, a PID-based iterative delay-based window adjustment scheme is proposed to achieve fast convergence and near-zero queuing latency. RCC does not need additional innetwork support and is friendly to hardware implementation. In our evaluation, the overall average FCT (Flow Completion Time) of RCC is 4~79% better than Homa, ExpressPass, DCQCN, TIMELY, and HPCC.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124553827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-01DOI: 10.1109/ICNP52444.2021.9651987
Hebin Yu, Jiaqi Zheng, Zhuoxuan Du, Guihai Chen
Multipath TCP (MPTCP) is a burgeoning transport protocol which enables the server to split the traffic across multiple network interfaces. Classic MPTCPs have good friendliness and practicality such as relatively low overhead, but are hard to achieve consistent high-throughput and adaptability, especially for the ability of flexibly balancing congestion among different paths. In contrast, learning-based MPTCPs can essentially achieve consistent high-throughput and adaptability, but have poor friendliness and practicality. In this paper, we proposed MPLibra, a combined multipath congestion control framework that can complement the advantages of classic MPTCPs and learning-based MPTCPs. Extensive simulations on NS3 show that MPLibra can achieve good performance and outperform state-of-the-art MPTCPs under different network conditions. MPLibra improves the throughput by 40.5% and reduces the file download time by 47.7% compared with LIA, achieves good friendliness and balances congestion timely.
{"title":"MPLibra: Complementing the Benefits of Classic and Learning-based Multipath Congestion Control","authors":"Hebin Yu, Jiaqi Zheng, Zhuoxuan Du, Guihai Chen","doi":"10.1109/ICNP52444.2021.9651987","DOIUrl":"https://doi.org/10.1109/ICNP52444.2021.9651987","url":null,"abstract":"Multipath TCP (MPTCP) is a burgeoning transport protocol which enables the server to split the traffic across multiple network interfaces. Classic MPTCPs have good friendliness and practicality such as relatively low overhead, but are hard to achieve consistent high-throughput and adaptability, especially for the ability of flexibly balancing congestion among different paths. In contrast, learning-based MPTCPs can essentially achieve consistent high-throughput and adaptability, but have poor friendliness and practicality. In this paper, we proposed MPLibra, a combined multipath congestion control framework that can complement the advantages of classic MPTCPs and learning-based MPTCPs. Extensive simulations on NS3 show that MPLibra can achieve good performance and outperform state-of-the-art MPTCPs under different network conditions. MPLibra improves the throughput by 40.5% and reduces the file download time by 47.7% compared with LIA, achieves good friendliness and balances congestion timely.","PeriodicalId":343813,"journal":{"name":"2021 IEEE 29th International Conference on Network Protocols (ICNP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117119809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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