International Business Machines Corporation

Microsoft Technology Licensing, LLC

Jeffrey Thomas Rasley

Kanak Behari Agarwal

John Bruce Carter

Colin Kimm Dixon

Srikanth Kandula

Sriram S Rao

Milan Vojnovic

Konstantinos Karanasos

Rodrigo Lopes Cancado Fonseca

Embodiments for efficient queue management for cluster scheduling and managing task queues for tasks which are to be executed in a distributed computing environment. Both centralized and distributed scheduling is provided. Task queues may be bound by length-based bounding or delay-based bounding. Tasks may be prioritized and task queues may be dynamically reordered based on task priorities. Job completion times and cluster resource utilization may both be improved.

Efficient queue management for cluster scheduling

Mechanisms are provided for determining an event rate. The mechanisms sample a sequence of events to generate a set of sampled events. At least a subset of the sampled events have associated event sequence values indicating a position of the sampled event within the sequence of events. The mechanisms group the sampled events into a plurality of event groups based on a common characteristic of the events. The mechanisms determine, for each event group, sequence values of sampled events associated with the event group. The mechanisms calculate, for each event group, an estimated event rate based on the sequence values of the sampled events associated with the event group and the total number of events in the sequence of events.

Determining sampling rate from randomly sampled events

Mechanisms are provided for analyzing data traffic through a network. The mechanisms sample data packets of a data flow through a normal port of a network forwarding device of the network. The sampling is performed at least by configuring the network forwarding device to implement port mirroring of the normal port to a designated mirror port of the network forwarding device. The mechanisms forward sampled data packets, copied to the mirror port by virtue of the port mirroring, to a collector computing device. The mechanisms process, by the collector computing device, the sampled data packets to analyze the data flow through the normal port of the network forwarding device. The mechanisms perform, by the collector computing device, an operation based on results of the analysis.

Port mirroring for sampling measurement of network flows

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Providence, RI, United States of America

Jeffrey Thomas Rasley