Invention Grant
- Patent Title: Systems and methods for scalable network modeling
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Application No.: US15789887Application Date: 2017-10-20
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Publication No.: US10911317B2Publication Date: 2021-02-02
- Inventor: Peyman Kazemian , Yasser Ganjisaffar , Sivasankar Radhakrishnan , Nikhil Handigol
- Applicant: Forward Networks, Inc.
- Applicant Address: US CA Palo Alto
- Assignee: Forward Networks, Inc.
- Current Assignee: Forward Networks, Inc.
- Current Assignee Address: US CA Palo Alto
- Agency: Hogan Lovells US LLP
- Main IPC: H04L12/24
- IPC: H04L12/24 ; H04L12/721 ; H04L12/26 ; H04L12/751 ; H04L12/715

Abstract:
Embodiments of the present invention can use a protocol-independent, vendor-independent, efficient and scalable abstraction model for representing the forwarding functionality of networks. Such a model can be used for systematic analysis and verification of networks. Packet header values may be represented as groups of one or more wildcarded bit strings, where unspecified header values are assumed to be fully wildcarded. This representation can describe many combinations of packets in a space-efficient way, enables more efficient tracing and transformation operations, and can even represent traffic from large internet routing tables efficiently. As a result of the scalability benefits of this more effective way to store and operate on packet collections, network modeling can scale to some of the largest, most complicated networks—those where the benefits are the greatest.
Public/Granted literature
- US20180115466A1 SYSTEMS AND METHODS FOR SCALABLE NETWORK MODELING Public/Granted day:2018-04-26
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