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Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang Zhang, Huichen Dai and Bin Liu Publisher: IEEE ICDCS, 2012 Presenter: Kai-Yang, Liu Date: 2013/3/13
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Page 1: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup withReduced Dynamic Redundancy

Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang Zhang, Huichen Dai and Bin LiuPublisher: IEEE ICDCS, 2012

Presenter: Kai-Yang, Liu

Date: 2013/3/13

Page 2: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

INTRODUCTION

•To achieve high performance, backbone routers must gracefully handle the three problems: routing table Compression, fast routing Lookup, and fast incremental UpdatE (CLUE).

•CLUE consists of three parts: a routing table compression algorithm, an improved parallel lookup mechanism, and a new fast incremental update mechanism.

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Page 3: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Compression Algorithm• ONRTC compresses the routing table size to 70%

of its original size. • Prefix overlap is eliminated.

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Page 4: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

ONRTC Algorithm

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Page 5: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Partition Algorithm•In order to achieve parallel lookup, the

prefixes should be split into partitions firstly.

•Step 1: compute the partition size. Suppose the size of routing table is M and the partition count is n, then the size of each partition is M/n.

•Step 2: traverse the trie by inorder, then put every M/n prefixes to each bucket.

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Page 6: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Improved Parallel Lookup Mechanism

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Page 7: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

The DRed update process of CLPL’s mechanism

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Page 8: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

The DRed update process of CLUE’s mechanism

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Page 9: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

The Incremental Update Mechanism

• The whole update process is divided into three steps :

1) trie update; 2) TCAM update; 3) DRed update.

• Time to Fresh (TTF) is defined in this paper, including TTF1 (TTF-trie), TTF2 (TTF-TCAM), and TTF3 (TTF-DRed).

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Page 10: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Experiments on Compression by ONRTC

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Page 11: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Partition comparison among the three algorithms

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Page 12: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

TTF1 comparison between CLPL and CLUE

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Page 13: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

TTF2 comparison between CLPL and CLUE

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Page 14: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

TTF3 comparison between CLPL and CLUE

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Page 15: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

TTF1+TTF2+TT3 comparison between CLPL and CLUE

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Page 16: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

WORKLOAD ON DIFFERENT PARTITIONS AND TCAM CHIPS.

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Page 17: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Load balance of workload distribution by CLUE

• Each TCAM takes 4 clocks to process a packet, while a packet arrives per clock. The FIFO is set to 256 and redundancy size is set to 1024 prefixes.

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Page 18: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Speedup factor comparison between CLPL and CLUE

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Page 19: CLUE: Achieving Fast Update over Compressed Table for Parallel Lookup with Reduced Dynamic Redundancy Author: Tong Yang, Ruian Duan, Jianyuan Lu, Shenjiang.

Hit rate comparison between CLPL and CLUE

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