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Internet Routers

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Presentation on theme: "Internet Routers"— Presentation transcript:

1 Internet Routers http://www.windowsecurity.com/whitepapers/Excerpts_from_The_Encyclopedia_of_Networking_.html

2 Sample Routers

3 Router Functionality INPUTPORTSINPUTPORTS OUTPUTPORTSOUTPUTPORTS

4 Rule Table Used to decide where to send a packet next (next hop).  Destination address.  Can get as large as ~1M rules

5 Router Rule Table USA  Output port 1 Illinois  Port 2 Chicago  Port 3 Europe  Port 4 Asia  Port 5 Etc.

6 Router Rules Range  [35, 2096] Address/mask pair  101100/011101  Matches 101100, 101110, 001100, 001110. Prefix filter.  Mask has 1s at left and 0s at right.  101100/110000 = 10* = [32, 47].  Special case of a range filter.

7 Example Router Table P1 = 10* P2 = 111* P3 = 11001* P4 = 1* P5 = 0* P6 = 1000* P7 = 100000* P8 = 1000000* P1 matches all addresses that begin with 10.

8 Tie Breakers First matching rule. Highest-priority rule. Most-specific rule.  [2,4] is more specific than [1,6].  [4,14] and [6,16] are not comparable. Longest-prefix rule.  Longest matching-prefix.

9 Longest-Prefix Matching P1 = 10* P2 = 111* P3 = 11001* P4 = 1* P5 = 0* P6 = 1000* P7 = 100000* P8 = 1000000* Destination = 100000000 P1, P4, P6, P7, P8 match this destination P8 is longest matching prefix

10 Table Size 1M+ rules Prefix up to 32 bits in IPv4 Prefix up to 128 bits in IPv6 OC192, 10Gbps  32 mpps (40-byte packets) Log 2 n schemes make too many memory accesses. 50,000 updates/sec

11 Handling Updates Batch Data Plane Lookups Control Plane Updates No lookup delay Rebuild time Time to switch Double resource

12 Handling Updates Incremental Data Plane Lookups Control Plane Updates Minimize lookup lockout

13 Ternary CAMs 011* 000* 11* 01* 00* 0* * H7 H6 H5 H4 H3 H2 H1 TCAMSRAM d = 011001 Longest prefix matching Highest priority matching Insert/Delete     Priority Encoder

14 Ternary CAMs Capacity Cost Power Board space Scalability to IPv6? Ranges? Multidimensional filters?

15 1-Bit Trie P1 = 10* P2 = 111* P3 = 11001* P4 = 1* P5 = 0* P6 = 1000* P7 = 100000* P8 = 1000000* P5P4 P1 P2 P6 P3 P7 P8

16 Complexity O(W)/operation P5P4 P1 P2 P6 P3 P7 P8

17 Batch Updates Reduce number of memory accesses for a lookup.  Multibit trie.

18 Multibit Tries Branching at a node is done using >= 1 bit (rather than exactly 1 bit)  Fixed stride Nodes on same level use same number of bits  Variable stride

19 Fixed-Stride Tries Number of levels = number of distinct prefix lengths. Use prefix expansion to reduce number of distinct lengths.

20 Prefix Expansion P1 = 10* P2 = 111* P3 = 11001* P4 = 1* P5 = 0* P6 = 1000* P7 = 100000* P8 = 1000000* #lengths = 7 P1 = 10* P2a = 11100* P2b = 11101* P2c = 11110* P2d = 11111* P3 = 11001* P4a = 11* P5a = 00* P5b= 01* P6a = 10000* P6b = 10001* P7a = 1000001* P8 = 1000000* #lengths = 3

21 Fixed-Stride Trie P5 P1P4 P6 P3 P2 P8P7 2 3 3 2

22 Optimization Problem Find least memory fixed-stride trie whose height is at most k. P5 P1P4 P6 P3 P2 P8P7

23 Covering and Expansion Levels P5 P1P4 P6 P3 P2 P8P7 P5P4 P1 P2 P6 P3 P7 P8

24 Dynamic Programming C(j,r) = cost of best FST whose height is at most r and which covers levels 0 through j of the 1-bit trie Want C(root,k) C(-1,r) = 0 C(j,1) = 2 j+1, j >= 0 P5P4 P1 P2 P6 P3 P7 P8

25 Dynamic Programming nodes(i) = #nodes at level i of 1-bit trie nodes(0) = 1 nodes(3) = 2 P5P4 P1 P2 P6 P3 P7 P8

26 Dynamic Programming C(j,r) = min -1 = 0, r > 1 P5P4 P1 P2 P6 P3 P7 P8 Compute C(W,k) Complexity = O(kW 2 )

27 Alternative Formulation C(j,r) = min{C(j,r-1), U(j,r)} U(j,r) = min r-2 = 0, r > 1 Let M(j,r), be smallest m that minimizes right side of equation for U(j,r). M(j,r) >= max{M(j-1,r), M(j,r-1)}, r > 2. Faster by factor of between 2 and 4.

28 Variable-Stride Tries P5 P1P4 P8P7P6 P3 P2... 2 3 5 P5P4 P1 P2 P6 P3 P7 P8

29 Dynamic Programming r-VST = VST with <= r levels Opt(N,r) = cost of best r-VST for 1-bit trie rooted at node N Want to compute Opt(root,k) D s (N) = all level s descendents of N D 1 (N) = children of N

30 Dynamic Programming Opt(N,s,r) =  M in Ds(N) Opt(M,r) = Opt(LeftChild(N),s-1,r) + Opt(RightChild(N),s-1,r), s > 0 Opt(null,*,*) = 0 Opt(N,0,r) = Opt(N,r) Opt(N,0,1) = 2 1+height(N) Optimal k-VST in O(mWk) ~ O(nWk)

31 Faster k = 2 Algorithm Opt(root,2) = min s {2 s + C(s)} C(s) =  M in Ds(root) 2 1+height(M) 1 <= s <= 1+height(root) Complexity is O(m) = O(n) on practical router data P5P4 P1 P2 P6 P3 P7 P8

32 Faster k = 3 Algorithm Opt(root,3) = min s {2 s + T(s)} T(s) =  M in Ds(root) Opt(M,2) 1 <= s <= 1+height(root) Complexity is O(m) = O(n) on practical router data that have non- skewed tries. Otherwise, complexity is O(mW), where W is trie height. P5P4 P1 P2 P6 P3 P7 P8

33 Binary Tries 011* 000* 11* 01* 00* 0* * H7 H6 H5 H4 H3 H2 H1 H2 H3 H4 H5 H6 H7

34 Succinct Representation of Tries 4 bytes/ptr  8 bytes+ per node 48+ bytes

35 Succinct Representation of Tries d c b a d c b a Internal Bit Map (IBM) = 101001001000000 Next Hop List = abcd 15 bits for IBM vs 48 bytes for child pointers Popcount

36 Succinct Representation of Tries Shape Bit Map (SBM) = 111101001 Internal Bit Map (IBM) = 101011 Next Hop List = abcd 15 bits for SBM & IBM vs 48 bytes for child pointers d c b a

37 Binary Trie P1 = * P2 = 0* P3 = 000* P4 = 10* P5 = 11* (a) prefixes

38 Tree Bitmap

39 Shape Shifting Trie

40 Hybrid Shape Shifting Trie

41 Ternary CAMs and Tries 011* 000* 11* 01* 00* 0* * H7 H6 H5 H4 H3 H2 H1 TCAMSRAM * 0* 00* 01* 11* 000* 011*

42 Ternary CAMs and Tries 000* 00* DTCAM 011* 01* 0* 11* * H6 H3 H7 H4 H2 H5 H1 00* 0* * 0,2 2,3 5,2 ITCAMISRAM DSRAM * 0* 00* 01* 11* 000* 011*

43 Two-Dimensional Filters Destination-Source pairs. (0*, 1100*)  Dest address begins with 0 and source with 1100 Least-cost tie breaker  (0*, 11*, 4) and (00*, 1*, 2)  Packet (00…, 11…)  Use second rule.

44 2D 1-Bit Tries F1 = (0*, 1100*, 1) F2 = (0*, 1110*, 2) F3 = (0*, 1111*, 3) F4 = (000*, 10*, 4) F5 = (000*, 11*, 5) F6 = (0001*, 000*), 6) F7 = (0*, 1*, 7)

45 2D Multibit Tries F1 = (0*, 1100*, 1) F2 = (0*, 1110*, 2) F3 = (0*, 1111*, 3) F4 = (000*, 10*, 4) F5 = (000*, 11*, 5) F6 = (0001*, 000*), 6) F7 = (0*, 1*, 7)

46 Space-Optimal 2D Multibit Tries Given k. Find 2DMT that can be searched with <= k memory accesses and has minimum memory requirement.

47 2D Binary Tries Succinct representations 2D hybrid shape shifting tries with minimal memory and specified bound on number of memory accesses to do a lookup

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