Reservoir Labs, Inc.

Significs and Elements, LLC

Qualcomm Incorporated

Qualcomm Technologies, Inc.

Jordi Ros-Giralt

Richard A Lethin

Alan Commike

Noah Amsel

Aditya Gudibanda

Peter Szilagyi

Sruthi Yellamraju

Peter Cullen

James Ezick

David E Wohlford

Techniques are presented for designing a network based on its topology and the expected flow patterns in the network. The use of the latter can lead to efficient use of network resources and can minimize waster. Non-interference property of the expected flows can yield an optimal design.

Data center networks using bottleneck structures

A technique is described for quantifying the effect of a perturbation on a property of a network link or flow, and to manipulate the network based on a quantitative estimation of the perturbation.

Network analysis and management based on a quantitative theory of bottleneck structures

In a system for efficiently detecting large/elephant flows in a network, the rate at which the received packets are sampled is adjusted according to the measured heavy tailedness of the arriving traffic, such that the measured heavy tailedness reaches a specified target level. The heavy tailedness is measured using the estimated sizes of different flows associated with the arriving packets. When the measured heavy tailedness reaches and remains at the specified target level, the flows having the largest estimated sizes are likely to be the largest/elephant flows in the network.

Systems and methods for detecting large network flows

A multiresolution parser (MRP) can selectively extract one or more information units from a dataset based on the available processing capacity and/or the arrival rate of the dataset. Should any of these parameters change, the MRP can adaptively change the information units to be extracted such that the benefit or value of the extracted information is maximized while minimizing the cost of extraction. This tradeoff is facilitated, at least in part, by an analysis of the spectral energy of the datasets expected to be processed by the MRP. The MRP can also determine its state after a processing iteration and use that state information in subsequent iterations to minimize the required computations in such subsequent iterations, so as to improve processing efficiency.

Systems and methods for multiresolution parsing

A system for storing and extracting elements according to their priority takes into account not only the priorities of the elements but also three additional parameters, namely, a priority resolution pand two priority limits pand p. By allowing an ordering error if the difference in the priorities of elements are within the priority resolution, an improvement in performance is achieved.

Systems and methods for multiresolution priority queues

In a network system, an application receiving packets can consume one or more packets in two or more stages, where the second and the later stages can selectively consume some but not all of the packets consumed by the preceding stage. Packets are transferred between two consecutive stages, called producer and consumer, via a fixed-size storage. Both the producer and the consumer can access the storage without locking it and, to facilitate selective consumption of the packets by the consumer, the consumer can transition between awake and sleep modes, where the packets are consumed in the awake mode only. The producer may also switch between awake and sleep modes. Lockless access is made possible by controlling the operation of the storage by the producer and the consumer both according to the mode of the consumer, which is communicated via a shared memory location.

Systems and methods for providing lockless bimodal queues for selective packet capture

A technique is described for quantifying a change in a system parameter in response to a perturbation of another system parameter. The technique identifies a region of influence of the perturbation and limits the propagation of the perturbation to the identified region.

Computationally efficient analysis and management of systems modeled as networks

A technique is described for quantifying the effect of a perturbation on a property of a network link or flow, and to add a new flow, reroute an existing flow, or to reshape a flow, based on a quantitative estimation of the perturbation.

Manipulating bottlenecks in systems modeled as networks

Techniques based on the Theory of Bottleneck Ordering can reveal the bottleneck structure of a network, and the Theory of Flow ordering can take advantage of the revealed bottleneck structure to manage and configure network flows so as to improve the overall network performance. These two techniques provide insights into the inherent topological properties of a network at least in three areas: (1) identification of the regions of influence of each bottleneck; (2) the order in which bottlenecks (and flows traversing them) may converge to their steady state transmission rates in distributed congestion control algorithms; and (3) the design of optimized traffic engineering policies.

Systems and methods for quality of service (QoS) based management of bottlenecks and flows in networks

In a system for efficiently detecting large/elephant flows in a network, the rate at which the received packets are sampled is adjusted according to a top flow detection likelihood computed for a cache of flows identified in the arriving network traffic. After observing packets sampled from the network, Dirichlet-Categorical inference is employed to calculate a posterior distribution that captures uncertainty about the sizes of each flow, yielding a top flow detection likelihood. The posterior distribution is used to find the most likely subset of elephant flows. The technique rapidly converges to the optimal sampling rate at a speed O(1/n), where n is the number of packet samples received, and the only hyperparameter required is the targeted detection likelihood.

Systems and methods for fast detection of elephant flows in network traffic

For balancing load, a forwarder can selectively direct data from the forwarder to a processor according to a loading parameter. The selective direction includes forwarding the data to the processor for processing, transforming and/or forwarding the data to another node, and dropping the data. The forwarder can also adjust the loading parameter based on, at least in part, feedback received from the processor. One or more processing elements can store values associated with one or more flows into a structure without locking the structure. The stored values can be used to determine how to direct the flows, e.g., whether to process a flow or to drop it. The structure can be used within an information channel providing feedback to a processor.

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Newport Beach, CA, United States of America

Jordi Ros-Giralt