Hash Table Generation Based on Prefix Length Distribution
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Solution Overview
Problem
As the size of routing tables increases with the growth of the Internet, existing mechanisms for IP address lookup, such as tree search algorithms and ternary content addressable memory (TCAM), become inefficient, leading to latency and high power consumption, especially when storing large routing tables.
Innovation Solution
Building a hash table based on the most popular prefix length from the routing table, which corresponds to the largest distribution of address entries, and storing it in RAM, while storing less popular prefix lengths in TCAM, reduces the physical size of the routing table and increases lookup efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If tree search algorithms or TCAM are used for IP address lookup, then routing table lookup capability is provided, but latency increases and power consumption increases
Solution Approach 1:
The routing table is segmented into multiple hash tables based on prefix length categories (e.g., /8, /16, /24, /32). Each hash table stores routing entries for a specific prefix length range, allowing the lookup process to be divided into multiple targeted searches rather than a single exhaustive search through the entire routing table.
Solution Approach 2:
The invention changes the lookup parameter from exhaustive prefix matching to hash-based direct access. By applying hash functions to the destination IP address and using the hash result to directly access the appropriate hash table, the system transforms the lookup process from a sequential search to a direct access operation, significantly reducing latency.
2Reliability
If tree search algorithms or TCAM are used for IP address lookup, then routing table lookup capability is provided, but power consumption increases
Solution Approach 1:
The routing table is segmented into multiple hash tables based on prefix length categories (e.g., /8, /16, /24, /32). Each hash table stores routing entries for a specific prefix length range, allowing the lookup process to be divided into multiple targeted searches rather than a single exhaustive search through the entire routing table.
Solution Approach 2:
The invention changes the lookup parameter from exhaustive prefix matching to hash-based direct access. By applying hash functions to the destination IP address and using the hash result to directly access the appropriate hash table, the system transforms the lookup process from a sequential search to a direct access operation, significantly reducing latency.
3Adaptability or versatility
If routing table size increases to accommodate Internet growth, then routing coverage is improved, but lookup efficiency decreases
Solution Approach 1:
The routing table is segmented into multiple hash tables based on prefix length categories (e.g., /8, /16, /24, /32). Each hash table stores routing entries for a specific prefix length range, allowing the lookup process to be divided into multiple targeted searches rather than a single exhaustive search through the entire routing table.
Solution Approach 2:
The invention introduces a new dimension to the routing table structure by organizing entries into a two-dimensional hierarchy: hash tables (indexed by hash function results) and prefix length categories. This dimensional transformation allows efficient access to routing entries even as the overall table size grows to accommodate Internet expansion.
Data Source
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AI summary
Examples herein disclose a generation of a hash table. The examples identify a prefix length from a routing table of various prefix lengths and corresponding distribution of entries. The identified prefix length corresponds to a larger distribution of entries in the routing table. The examples generate the hash table in accordance with the identified prefix length.