Is Information-Centric Multi-Tree Routing Feasible?
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1 Is Information-Centric Multi-Tree Routing Feasible? ICN workshop 2013 Michele Papalini (University of Lugano) joint work with: Antonio Carzaniga (University of Lugano) Koorosh Khazaei (University of Lugano) Alexander L. Wolf (Imperial College London)
2 Traditional Networking Information-Centric Networking
3 Traditional Networking addressing end-points addressing information Information-Centric Networking
4 Traditional Networking How do we address information? How do we obtain information? (Architectural questions) Information-Centric Networking
5 Traditional Networking How do we address information? Tags How do we obtain information? Push/Pull Information-Centric Networking
6 Traditional Networking How do we address information? Tags Scalable Routing How do we get information? Push/Pull (System/Evaluation questions) Information-Centric Networking
7 How do we address information?
8 Solution I: name the data
9 Solution I: name the data flat, not human readable identifiers 1DB76EB8DFD6B0B92A293AADC BDE73CB6 hierarchical, meaningful structured names /ch/usi/inf/papalini/picture.jpg
10 /ch/usi/inf/papalini/picture.jpg
11 /ch/usi/inf/papalini/picture.jpg /nytimes/sport/baseball/mets /cnn/us/sport/baseball/mets
12 /ch/usi/inf/papalini/picture.jpg /nytimes/sport/baseball/mets /cnn/us/sport/baseball/mets /youtube/la dolce vita/hd
13 baseball scores for NY Mets
14 baseball scores for NY Mets la dolce vita in HD with english subtitles
15 Solution II: describe the data
16 Solution II: describe the data with set of tags baseball, new york, mets la dolce vita, HD, en-sub
17 Tags
18 Tags more expressivity /ch/usi/inf/papalini/picture.jpg 1#ch, 2#usi, 3#inf, 4#papalini, 5#picture.jpg
19 Tags more expressivity /ch/usi/inf/papalini/picture.jpg 1#ch, 2#usi, 3#inf, 4#papalini, 5#picture.jpg more aggregation sport, new, football Lugano, sport, activities sport
20 Tags more expressivity /ch/usi/inf/papalini/picture.jpg 1#ch, 2#usi, 3#inf, 4#papalini, 5#picture.jpg more aggregation sport, new, football Lugano, sport, activities sport sport
21
22 How do we obtain information?
23 PULL
24 PULL producer consumer
25 PULL producer register(descriptors) forwarding tables consumer
26 PULL producer register(descriptors) forwarding tables consumer interest: content-descriptor
27 PULL producer register(descriptors) data:content forwarding tables consumer interest: content-descriptor
28 PUSH
29 PUSH producer consumer
30 PUSH producer forwarding tables consumer subscribe(descriptors)
31 PUSH producer notification:descriptor forwarding tables consumer subscribe(descriptors)
32 PU LL SH
33 PU LL SH Node A Node B
34 PU LL SH Node A register(descriptors) forwarding tables Node B
35 PU LL SH Node A register(descriptors) forwarding tables Node B message: content-descriptor +data request: content-descriptor
36 PU LL SH Node A register(descriptors) reply:data forwarding tables Node B message: content-descriptor +data request: content-descriptor
37 Node A register(descriptors) reply:data forwarding tables PU LL SH Node B message: content-descriptor +data request: content-descriptor ICN 2011: Content-Based Publish/Subscribe Networking and Information-Centric Networking
38 Node A forwarding tables PU LL SH Node B register(descriptors) How do we route? message: content-descriptor +data reply:data request: content-descriptor
39 Routing schema based on multiple trees Main contribution
40 Main contribution Routing schema based on multiple trees Scalability analysis Additional cost (hops/state) using multiple trees FIBs size using a realistic workload
41 Routing
42 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c d e f g h i j k
43 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c d e f g h i j k
44 router b: tree T,next-hop w predicate P T,w (FIB) T 1, router c p c b: next-hop p g p h w predicate P w T 1,(FIB) f p f cp j p kc p g p h T 1, e p a fp d p ef p ij p k T 2, c p c ep h p ga p d p e p i T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
45 router b: tree T,next-hop w predicate P T,w (FIB) T 1, router c p c b: next-hop p g p h w predicate P w T 1,(FIB) f p f cp j p kc p g p h T 1, e p a fp d p ef p ij p k T 2, c p c ep h p ga p d p e p i T 2, e p a p d p e p f p i p j p k a b c d e f g h i j k
46 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c d e f g h i j k
47 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k Stretched Paths a b c d e f g h i j k
48 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p Load k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c d e f g h i j k
49 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p Multiple k T 1, etrees p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c d e f g h i j k
50 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
51 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p Memory k T 1, ecomplexity p a p d p e p i Problem T 2, c p c p hg p gh T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
52 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
53 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
54 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
55 router b: tree,next-hop predicate T,w router b: tree T,next-hop w predicate P T,w (FIB) T 1, c c g (FIB) c p h 1 c p f h p j g T k 1, f p 1 f p a j p d k e T i 1, e p 2 c a p c d p h e p i T g 2, e p 2 a p a d p d e p e f p f i p i j p j k k a b c b d e f g h i j k
56 router b: tree T,next-hop w predicate P T,w (FIB) T 1, c p c p g p h T 1, f p f p j p k T 1, e p a p d p e p i T 2, c p c p h p g T 2, e p a p d p e p f p i p j p k a b c b d e f g h i j k
57 router b: tree T,next-hop w predicate P T,w router b: next-hop w predicate P (FIB) T 1, c c g T,w (FIB) c p h 1 c p f h p j g T k 1, f p 1 f p a j p d k e T i 1, e p 2 c a p c d p h e p i T g 2, e p 2 a p a d p d e p e f p f i p i j p j k k a b c b d e f g h i j k
58 router router b: next-hop b: tree T w,next-hop predicate w predicate P T,w P T,w (FIB) (FIB) c pt c 1, cp h p gc p g p h f (TT 1, f p f ) p f (T 1 p j pp j ) k (T 1 p k ) e (TT 1, e p a ) p a (T 1 p d p d p) e (T p i 1 p e ) (T 1 p i ) (TT 2, c p a ) p c (T 2 p h p d p) g (T 2 p e ) (T 2 p i ) (TT 2, e p f ) p a (T 2 p d p j p) e (T p f2 p i k ) p j p k a b c b d e f g h i j k
59 router router b: next-hop b: tree T w,next-hop predicate w predicate P T,w P T,w (FIB) (FIB) c pt c 1, cp h p gc p g p h f (TT 1, f p f ) p f (T 1 p j pp j ) k (T 1 p k ) e (TT 1, e p a ) p a (T 1 p d p d p) e (T p i 1 p e ) (T 1 p i ) (TT 2, c p a ) p c (T 2 p h p d p) g (T 2 p e ) (T 2 p i ) (TT 2, e p f ) p a (T 2 p d p j p) e (T p f2 p i k ) p j p k a b c b d e f g h i j k
60 router b: tree T,next-hop w predicate P T,w router b: next-hop w predicate P (FIB) T 1, c p c p g p T,w (FIB) c p h T 1, f c p p f h p p j g p f (T k T 1, e 1 p p a f ) (T p d p 1 p e j ) (T 1 p k ) e p i T 2, c a p p c d p p h e p p i (T g T 2, e 2 p p a f ) (T p d p 2 p e j ) (T f p i 2 p p j k ) p k a b c b d e f g h i j k
61 router b: tree T,next-hop w predicate P T,w router b: next-hop w predicate P (FIB) T 1, c p c p g p T,w (FIB) c p h T 1, f c p p f h p p j g p f (T k T 1, e 1 p p a f ) (T p d p 1 p e j ) (T 1 p k ) e p i T 2, c a p p c d p p h e p p i (T g T 2, e 2 p p a f ) (T p d p 2 p e j ) (T f p i 2 p p j k ) p k a b c b d e f g h i j k
62 router b: tree T,next-hop w predicate P T,w router b: next-hop w predicate P (FIB) T 1, c p c p g p T,w (FIB) c p h T 1, f c p p f h p p j g p f (T k T 1, e 1 p p a f ) (T p d p 1 p e j ) (T 1 p k ) e p i T 2, c a p p c d p p h e p p i (T g T 2, e 2 p p a f ) (T p d p 2 p e j ) (T f p i 2 p p j k ) p k coming soon: new data structure a b c b d e f g h i j k
63 Evaluation
64 Evaluation Q 1: Is it possible to use trees to route traffic over the Internet?
65 Evaluation Q 1: Is it possible to use trees to route traffic over the Internet? Q 2: Do user-defined descriptor-based addresses aggregate?
66 Evaluation Q 1: Is it possible to use trees to route traffic over the Internet? Q 2: Do user-defined descriptor-based addresses aggregate? We need a workload
67 Topology What do we need?
68 What do we need? Topology Distribute users on the nodes
69 What do we need? Topology Distribute users on the nodes Assign applications to users
70 What do we need? Topology Distribute users on the nodes Assign applications to users Create the registrations
71 What do we need? Topology AS-level Internet topology Distribute users on the nodes Assign applications to users Create the registrations
72 What do we need? Topology Distribute users on the nodes assigned to each AS according to the estimated population Assign applications to users Create the registrations
73 What do we need? Topology Distribute users on the nodes Assign applications to users selected according to the real number of users Create the registrations
74 What do we need? Topology Distribute users on the nodes Assign applications to users Create the registrations???
75 Imagine the future Internet study the users behavior on different applications define registrations with actual tags used by users
76 Imagine the future Internet study the users behavior on different applications define registrations with actual tags used by users Push content web content and blog posts short messages (tweets)
77 Imagine the future Internet study the users behavior on different applications define registrations with actual tags used by users Push content web content and blog posts short messages (tweets) Pull content videos
78 Goal: Understand users interests Web Content
79 Web Content Goal: Understand users interests Users Bookmarks (Delicious) bookmarks = subscription
80 Application User Registration Delicious 1M 124M Blogs 60K 180K Video 1K 10K Twitter Graph 41M 1B Twitter Messages 400K 500K
81 Data Amplification
82 Data Amplification Multiple languages replicate the data for the 25 most spoken languages language is chosen according to the popularity
83 Data Amplification Multiple languages replicate the data for the 25 most spoken languages language is chosen according to the popularity Synonyms for each word we define synonyms synonyms are randomly chosen
84 Evaluation Q 1: Is it possible to use trees to route traffic over the Internet? Q 2: Do user-defined descriptor-based addresses aggregate?
85 Additional cost in using k trees on the actual AS-level topology with k = 8, 16, 32, 64, 128 trees 6 Avg/Max Additional Path Length (Hops)
86 Additional cost in using k trees on the actual AS-level topology with k = 8, 16, 32, 64, 128 trees 6 Avg/Max Additional Path Length (Hops)
87 Additional cost in using k trees on the actual AS-level topology with k = 8, 16, 32, 64, 128 trees 6 Avg/Max Additional Path Length (Hops)
88 Tree aggregation in FIBs with k = 8, 16, 32, 64, 128 trees Distinct Trees per Interface
89 Tree aggregation in FIBs with k = 8, 16, 32, 64, 128 trees Distinct Trees per Interface
90 Aggregation of tag-based addresses in FIBs memory requirements in a central node for a single tree 2.5M users All Interfaces Largest Interfaces Destinations 42,112 6,559 Tags 276,501,173 35,814,399 Original Descriptors 85,504,514 10,727,593 Actual Descriptors 10,880,657 1,145,713 Size (MB)
91 Aggregation of tag-based addresses in FIBs memory requirements in a central node for a single tree 2.5M users All Interfaces Largest Interfaces Destinations 42,112 6,559 Tags 276,501,173 35,814,399 Original Descriptors 85,504,514 10,727,593 Actual Descriptors 10,880,657 1,145,713 Size (MB)
92 Aggregation of tag-based addresses in FIBs memory requirements in a central node for a single tree 2.5M users All Interfaces Largest Interfaces Destinations 42,112 6,559 Tags 276,501,173 35,814,399 Original Descriptors 85,504,514 10,727,593 Actual Descriptors 10,880,657 1,145,713 Size (MB)
93 Aggregation of tag-based addresses in FIBs memory requirements in a central node for a single tree 2.5M users All Interfaces Largest Interfaces Destinations 42,112 6,559 Tags 276,501,173 35,814,399 Original Descriptors 85,504,514 10,727,593 Actual Descriptors 10,880,657 1,145,713 Size (MB)
94 Aggregation of tag-based addresses in FIBs memory requirements in a central node for a single tree 2.5M users All Interfaces Largest Interfaces Destinations 42,112 6,559 Tags 276,501,173 35,814,399 Original Descriptors 85,504,514 10,727,593 Actual Descriptors 10,880,657 1,145,713 Size (MB) Aggregation Factor
95 Aggregation of tag-based addresses in FIBs memory requirements in a central node for a single tree 2.5M users All Interfaces Largest Interfaces Destinations 42,112 6,559 Tags 276,501,173 35,814,399 Original Descriptors 85,504,514 10,727,593 Actual Descriptors 10,880,657 1,145,713 Size (MB) Bloom Filter size = 400 bits
96 Workload: 25M users, 513M descriptors, 8 trees Total descriptors: 4.1 billion Current Work
97 Workload: 25M users, 513M descriptors, 8 trees Total descriptors: 4.1 billion Compressed Table: 300M descriptors Current Work
98 Workload: 25M users, 513M descriptors, 8 trees Total descriptors: 4.1 billion Compressed Table: 300M descriptors Update time (average): 6 µsec per descriptor Current Work
99 Workload: 25M users, 513M descriptors, 8 trees Total descriptors: 4.1 billion Compressed Table: 300M descriptors Update time (average): 6 µsec per descriptor Matching time Current Work Time (us) Tags
100 Conclusion Routing scheme: tag-based address push-pull communication
101 Conclusion Routing scheme: tag-based address push-pull communication Scalability: AS-topology can be cover with few trees FIB size is reasonable
102 Conclusion Routing scheme: tag-based address push-pull communication Scalability: AS-topology can be cover with few trees FIB size is reasonable Workload
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