According to one embodiment ( ) a ternary CAM can include rules stored in CAM locations, where each rule includes match criteria. CAM locations determine priority among various rules. An input value can be matched against stored rules according to the match criteria. In an update operation ( ) the CAM can receive a new rule ( ). The new rule can be checked for overlap against currently stored rules ( ). Rules overlap if an input value exists that can match both rules. If the new rule does not overlap any other rules, it can be added to any free location in the CAM. If the rule overlaps one or more existing rules, the new rule can be stored in an available location that with the appropriate priority with respect to the stored overlapping rules. If no such available location exists, a new set of CAM locations can be randomly selected, and the new rule and all overlapping rules can be written into the selected locations according to priority value.
A statistically based counter increments a count value based on a random probability. As the count value increases, the probability of increasing the count value is decreased. The count value is stored as the combination of an exponent and a mantissa. In this manner, the count value can count up to a very large dynamic range while using a relatively small storage area for the count value.
Spencer Greene - Palo Alto CA, US James Washburn - Palo Alto CA, US Olaf Möller - Santa Clara CA, US
Assignee:
Juniper Networks, Inc. - Sunnyvale CA
International Classification:
G06F 12/00
US Classification:
711216
Abstract:
A system precomputes data for possible use by a processor. The system receives data units, and determines the types of the data units. The system then identifies one or more bit masks based on the types of the data units, where the one or more bit masks include bits corresponding to at least some portions of the data units. The system uses the one or more bit masks to select one or more portions of the data units and perform one or more functions using the one or more portions of the data units to generate function results. The system stores the function results in a first memory for subsequent selective use by the processor, and stores the data units in a second memory for subsequent retrieval by the processor.
Dennis C. Ferguson - Palo Alto CA, US Devereaux C. Chen - Cupertino CA, US James Washburn - Palo Alto CA, US Jeffrey R. Zimmer - Scotts Valley CA, US
Assignee:
Juniper Networks, Inc. - Sunnyvale CA
International Classification:
H04L 12/22 H04L 12/56
US Classification:
370230, 370389, 370391, 370392
Abstract:
A data flow rate policer enforces data flow policies for a number of data flows using a probabilistic policy enforcement mechanism. The policer includes a memory that stores the state of each data flow in a compact data structure. Additionally, the policer includes one or more policing engines that implement the actual data flow policies based on information derived from the data structures. The policing engines may be implemented in hardware to increase performance.
Hierarchical Policers For Enforcing Differentiated Traffic Behavior
James Washburn - Palo Alto CA, US Spencer Greene - Palo Alto CA, US Rami Rahim - Sunnyvale CA, US Stefan Dyckerhoff - Palo Alto CA, US Dennis C. Ferguson - Palo Alto CA, US Philippe Lacroute - Sunnyvale CA, US
Assignee:
Juniper Networks, Inc. - Sunnyvale CA
International Classification:
H04J 1/16
US Classification:
370230, 370411
Abstract:
A hierarchical traffic policer may include a first policer configured to pass first packets when a first condition is met. The first policer also may alter selection information within the passed first packets. A second policer may be configured to pass second packets when a second condition is met. The second policer may be further configured to pass all of the passed first packets from the first policer based on the altered selection information within the passed first packets.
Dennis C. Ferguson - Palo Alto CA, US Devereaux C. Chen - Cupertino CA, US James Washburn - Palo Alto CA, US Jeffrey R. Zimmer - Scotts Valley CA, US
Assignee:
Juniper Networks, Inc. - Sunnyvale CA
International Classification:
H04L 12/26 H04L 12/56
US Classification:
370230, 370233, 370238, 370389, 370392, 370401
Abstract:
A data flow rate policer enforces data flow policies for a number of data flows using a probabilistic policy enforcement mechanism. The policer includes a memory that stores the state of each data flow in a compact data structure. Additionally, the policer includes one or more policing engines that implement the actual data flow policies based on information derived from the data structures. The policing engines may be implemented in hardware to increase performance.
Hierarchical Policers For Enforcing Differentiated Traffic Behavior
James Washburn - Palo Alto CA, US Spencer Greene - Palo Alto CA, US Rami Rahim - Sunnyvale CA, US Stefan Dyckerhoff - Palo Alto CA, US Dennis C. Ferguson - Palo Alto CA, US Philippe Lacroute - Sunnyvale CA, US
Assignee:
Juniper Networks, Inc. - Sunnyvale CA
International Classification:
H04L 12/28
US Classification:
37039542, 370389
Abstract:
A hierarchical traffic policer may include a first policer configured to pass first packets when a first condition is met. The first policer also may alter selection information within the passed first packets. A second policer may be configured to pass second packets when a second condition is met. The second policer may be further configured to pass all of the passed first packets from the first policer based on the altered selection information within the passed first packets.
Filtering Traffic Based On Associated Forwarding Equivalence Classes
Ina Minei - Santa Clara CA, US James Washburn - Palo Alto CA, US Shivani Aggarwal - San Francisco CA, US
Assignee:
Juniper Networks, Inc. - Sunnyvale CA
International Classification:
H04L 12/28
US Classification:
370351
Abstract:
Filters are selectively applied to packets depending on forwarding equivalence classes (FECs) of the packets. A FEC filter is defined within the network device and qualified by incoming interface information that identifies source sites of the packets. A label distribution protocol (LDP) FEC is configured such that packets of the given FEC are associated with the FEC filter. The FEC identifies a destination site of the packets received by the router and is automatically combined with incoming interface information. In this way, packet flows may be filtered based on FECs of the packets. FEC filters may be further refined to operate at forwarding class granularity. The techniques allow accurate billing of packets traveling between specific source and destination sites regardless of the number of interfaces of the network device the packets utilize. In addition, the filtering can be used to provide anti-spoofing capabilities.
Name / Title
Company / Classification
Phones & Addresses
James Washburn Manager
Anne M Pachciarek Lawyer Security Brokers, Dealers, and Flotation Comp...