Google Inc.

Gautam Kumar

Nandita Dukkipati

Prashant R Chandra

Amin Vahdat

Yuliang Li

Hassan Wassel

Keon Jang

Inho Cho

Weihuang Wang

Michael Roger Marty

Xiaoming Wang

Nicholas McDonald

Neelesh Bansod

Serhat Arslan

Yiwen Zhang

Xian Wu

Nicholas Mcdonald

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.

Network congestion control in sub-round trip time

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.

Admission control for latency-critical remote procedure calls in datacenters

A system includes a first processor configured to analyze packets received over a communication protocol system and determine one or more congestion indicators from the analysis of the data packets, the one or more congestion indicators being indicative of network congestion for data packets transmitted over a reliable transport protocol layer of the communication protocol system. The system also includes a rate update engine separate from the packet datapath and configured to operate a second processor to receive the determined one or more congestion indicators, determine one or more congestion control parameters for controlling transmission of data packets based on the received one or more congestion indicators, and output a congestion control result based on the determined one or more congestion control parameters.

Rate update engine for reliable transport protocol

A system is provided for synchronizing clocks. The system includes a plurality of devices in a network, each device having a local clock. The system is configured to synchronize the local clocks according to a primary spanning tree, where the primary spanning tree has a plurality of nodes connected through a plurality of primary links, each node of the plurality of nodes representing a respective device of the plurality of devices. The system is also configured to compute a backup spanning tree before a failure is detected in the primary spanning tree, wherein the backup spanning tree includes one or more backup links that are different from the primary links. As such, upon detection of a failure in the primary spanning tree, the system reconfigures the plurality of devices such that clock synchronization is performed according to the backup spanning tree.

Fault tolerant design for clock-synchronization systems

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

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Mountain View, CA, United States of America

Gautam Kumar