Admission Control for Latency-Critical Remote Procedure Calls in Datacenters

    公开(公告)号:US20220239598A1

    公开(公告)日:2022-07-28

    申请号:US17579989

    申请日:2022-01-20

    Applicant: Google LLC

    Abstract: A distributed sender driven Admission Control System (ACS) is described herein, leveraging Weighted-Fair Quality of Service (QoS) queues, found in standard NICs and switches, to guarantee RPC level latency service level objectives (SLOs) by a judicious selection of QoS weights and traffic-mix across QoS queues. ACS installs cluster-wide RPC latency SLOs by mapping LS RPCs to higher weight QoS queues, and coping with overloads by adaptively apportioning LS RPCs amongst QoS queues based on measured completion times for each queue. When the network demand spikes unexpectedly to predetermined threshold percentage of provisioned capacity, ACS achieves a latency SLO that is significantly lower than the state-of-art congestion control at the 99.9th-p and admits significantly more RPCs meeting SLO target when RPC sizes are not aligned with priorities.

    Network congestion control in sub-round trip time

    公开(公告)号:US12250157B2

    公开(公告)日:2025-03-11

    申请号:US18136551

    申请日:2023-04-19

    Applicant: Google LLC

    Abstract: Aspects of the disclosure provide for congestion control mechanisms to reduce data transmission queues and to increase link utilization through precise congestion signals and reduction of control loop delay. A congestion control system (CC) system can utilize Back-To-Sender (BTS) packets over (round trip time) RTT control loop delay to react to congestion faster. The CC system can apply Proactive Ramp-up (PRU) to identify flow completions to occupy released bandwidth right on time, e.g., as bandwidth is made available. The CC system can perform supply matching (SM) through network calculus concepts to increase link utilization. The CC system can apply some or all of the use of BTS packets, PRU, and/or SM to reduce network latency and improve data flow completion time as compared with other approaches.

    Admission control for latency-critical remote procedure calls in datacenters

    公开(公告)号:US12081442B2

    公开(公告)日:2024-09-03

    申请号:US17579989

    申请日:2022-01-20

    Applicant: Google LLC

    CPC classification number: H04L47/2433 H04L43/0852 H04L47/629 H04L67/133

    Abstract: A distributed sender driven Admission Control System (ACS) is described herein, leveraging Weighted-Fair Quality of Service (QoS) queues, found in standard NICs and switches, to guarantee RPC level latency service level objectives (SLOs) by a judicious selection of QoS weights and traffic-mix across QoS queues. ACS installs cluster-wide RPC latency SLOs by mapping LS RPCs to higher weight QoS queues, and coping with overloads by adaptively apportioning LS RPCs amongst QoS queues based on measured completion times for each queue. When the network demand spikes unexpectedly to predetermined threshold percentage of provisioned capacity, ACS achieves a latency SLO that is significantly lower than the state-of-art congestion control at the 99.9th-p and admits significantly more RPCs meeting SLO target when RPC sizes are not aligned with priorities.

    Congestion control for low latency datacenter networks

    公开(公告)号:US11509593B2

    公开(公告)日:2022-11-22

    申请号:US17185020

    申请日:2021-02-25

    Applicant: Google LLC

    Abstract: Systems and methods for controlling congestion of a data network are provided. An engine round-trip time (RTT) and a fabric RTT for a network flow are determined. An engine-based congestion window size for the flow is determined based on the engine RTT and a target engine RTT. A fabric-based congestion window size for the flow is determined based on the fabric RTT and a target fabric RTT. The smaller of the engine-based congestion window size and the fabric-based window size is selected for use in transmitting a future packet associated with the flow. The target engine RTT is determined based in part on the current congestion window used to transmit packets for the flow and/or the target fabric RTT is determined based on a number of hops packets associated with the flow traverse from a source to a destination associated with the flow.

    Congestion Control For Low Latency Datacenter Networks

    公开(公告)号:US20210184981A1

    公开(公告)日:2021-06-17

    申请号:US17185020

    申请日:2021-02-25

    Applicant: Google LLC

    Abstract: Systems and methods for controlling congestion of a data network are provided. An engine round-trip time (RTT) and a fabric RTT for a network flow are determined. An engine-based congestion window size for the flow is determined based on the engine RTT and a target engine RTT. A fabric-based congestion window size for the flow is determined based on the fabric RTT and a target fabric RTT. The smaller of the engine-based congestion window size and the fabric-based window size is selected for use in transmitting a future packet associated with the flow. The target engine RTT is determined based in part on the current congestion window used to transmit packets for the flow and/or the target fabric RTT is determined based on a number of hops packets associated with the flow traverse from a source to a destination associated with the flow.

    Congestion control for low latency datacenter networks

    公开(公告)号:US10999206B2

    公开(公告)日:2021-05-04

    申请号:US16455134

    申请日:2019-06-27

    Applicant: Google LLC

    Abstract: Systems and methods for controlling congestion of a data network are provided. An engine round-trip time (RTT) and a fabric RTT for a network flow are determined. An engine-based congestion window size for the flow is determined based on the engine RTT and a target engine RTT. A fabric-based congestion window size for the flow is determined based on the fabric RTT and a target fabric RTT. The smaller of the engine-based congestion window size and the fabric-based window size is selected for use in transmitting a future packet associated with the flow. The target engine RTT is determined based in part on the current congestion window used to transmit packets for the flow and/or the target fabric RTT is determined based on a number of hops packets associated with the flow traverse from a source to a destination associated with the flow.

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