SCALABLE APPROACH TO LARGE SCALE QUEUING THROUGH DYNAMIC RESOURCE ALLOCATION

Patent №

US 8,199,764

Granted

2012-06-12

Filed 2003

Owner

ANDIAMO SYSTEMS, INC.

Lab

AI components

1

kr

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

10648624

Methods and devices are provided for the efficient allocation and deletion of virtual output queues. According to some implementations, incoming packets are classified according to a queue in which the packet (or classification information for the packet) will be stored, e.g., according to a “Q” value. For example, a Q value may be a Q number defined as {Egress port number∥Priority number∥Ingress port number}. Only a single physical queue is allocated for each classification. When a physical queue is empty, the physical queue is preferably de-allocated and added to a “free list” of available physical queues. Accordingly, the total number of allocated physical queues preferably does not exceed the total number of classified packets. Because the input buffering requirements of Fiber Channel (“FC”) and other protocols place limitations on the number of incoming packets, the dynamic allocation methods of the present invention result in a sparse allocation of physical queues.

Knowledge representationH04L 49/9047H04L 47/6215H04L 49/30H04L 49/3045H04L 49/90

AI classification

Knowledge representation0.66
AI hardware0.18
Planning0.13
Machine learning0.00
Natural language0.00
Vision0.00
Evolutionary computation0.00
Speech0.00

Ownership

ANDIAMO SYSTEMS, INC.

assignment · 144420251

Assignors

HOFFMAN, ROBERT, KLOTH, RAYMOND J., FULLI, ALESSANDRO

On an employer assignment, the assignors are typically the inventors.

© 2026 NYSGPT2525 LLC