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Declarative Routing: Extensible Routing with Declarative Queries Boon Thau Loo 1 Joseph M. Hellerstein 1,2, Ion Stoica 1, Raghu Ramakrishnan 3, 1 University.

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Presentation on theme: "Declarative Routing: Extensible Routing with Declarative Queries Boon Thau Loo 1 Joseph M. Hellerstein 1,2, Ion Stoica 1, Raghu Ramakrishnan 3, 1 University."— Presentation transcript:

1 Declarative Routing: Extensible Routing with Declarative Queries Boon Thau Loo 1 Joseph M. Hellerstein 1,2, Ion Stoica 1, Raghu Ramakrishnan 3, 1 University of California at Berkeley, 2 Intel Research Berkeley, 3 University of Wisconsin-Madison Smchoi 2011.04.23

2 Motivation Lack of extensibility and flexibility in today’s Internet routing Hard to add/improve/update routing protocols

3 Two “Extremes”: “Hard-coded” protocols: - Efficiency, safety - Flexibility, evolvability - + Active Networks - Flexibility, evolvability - Safety, efficiency - + Declarative Routing: + Flexibility, evolvability, safety Our Goal Restricted instantiation of Active Networks for the control plane

4 Key Idea Recursive query language for expressing routing protocols: Datalog: a declarative recursive query language Well-researched in the database community Well-suited for querying properties of graphs

5 Advantages Expressiveness: Compact and clean representation of protocols Safety: Datalog has desirable safety properties on termination Efficiency: No fundamental overhead when executing standard protocols.

6 Usage Scenarios ISP administrators Run different protocols for different nodes Modify existing protocols in routers End-hosts Set up customized routes for different quality-of-service and policy requirements of applications

7 Roadmap Execution Model Introduction to Datalog Path-Vector Protocol Example Advantages: Expressiveness Safety Efficiency Evaluation

8 Centralized Execution Model Store entire network state into a centralized database Issue Datalog queries on the centralized database for customized routes Fully distributed implementation To explore the limits of our design

9 Distributed Execution Model Declarative RoutingTraditional Routers Input Tables Output Tables Datalog Queries Query Processor Routing Protocol Neighbor Table updates Forwarding Table updates

10 Introduction to Datalog ,, …,. Datalog rule syntax:

11 All-Pairs Reachability R2: reachable(S,D)  link(S,Z), reachable(Z,D) R1: reachable(S,D)  link(S,D) Input: link(source, destination) Output: reachable(source, destination) “For all S,D, If link(S,D) exists, generate reachable(S,D)” “For all nodes S,D, If there is a link from S to D, then S can reach D”. link(a,b) – “there is a link from node a to node b” reachable(a,b) – “node a can reach node b”

12 All-Pairs Reachability R2: reachable(S,D)  link(S,Z), reachable(Z,D) R1: reachable(S,D)  link(S,D) Input: link(source, destination) Output: reachable(source, destination) “For all nodes S,D and Z, If there is a link from S to Z, AND Z can reach D, then S can reach D”. “For all S, D and Z, If link(S,Z) exists AND reachable(Z,D) exists, generate reachable(S,D).”

13 All-Pairs Reachability R2: reachable(S,D)  link(S,Z), reachable(Z,D) R1: reachable(S,D)  link(S,D) Query: reachable(M,N) bdca SD ab reachable Output table (Round 1): SD bc reachable SD cd Input table: SD cd link SD bc SD ab E.g. R1: reachable(b,c)  link(b,c) All-Pairs

14 All-Pairs Reachability R2: reachable(S,D)  link(S,Z), reachable(Z,D) R1: reachable(S,D)  link(S,D) Query: reachable(M,N) bdca SD ab ac reachable Output table (Round 2): SD bc bd reachable SD cd Input table: SD cd link SD bc SD ab R2: reachable(b,d)  link(b,c), reachable(c,d)

15 R2: reachable(S,D)  link(S,Z), reachable(Z,D) R1: reachable(S,D)  link(S,D) Query: reachable(M,N) bdca SD ab ac ad reachable Output table (Round 3): SD bc bd reachable SD cd Input table: SD cd link SD bc SD ab All-Pairs Reachability Recursive queries are natural for querying graph topologies

16 Roadmap Execution Model Introduction to Datalog Path-Vector Protocol Example Distributed Datalog  Execution Plan  Protocol Advantages: Expressiveness Safety Efficiency Evaluation

17 R1: reachable(S,D)  link(S,D) R2: reachable(S,D)  link(S,D), reachable(Z,D) Distributed Datalog Query: reachable(M,N) bdca SD ab ac ad reachable Output table: SD bc bd reachable SD cd Input table: SD cd link SD bc SD ab

18 Path Vector Protocol Example Input: link(source, destination) Query output: path(source, destination, pathVector) R1: path(S,D,P)  link(S,D), P=(S,D). R2: link(Z,S), path(S,D,P) P=S+P 2. path(Z,D,P 2 ),  Query: path(S,D,P)

19 Datalog  Execution Plan R1: path(S,D,P)  link(S,D), P=(S,D). R2: link(S,D)path(S,D,P) R1 Recursion link(Z,S), path(S,D,P) P=S+P 2. link.S=path.S R2 while (receive )) { for each neighbor S { newpath = path(S,D,S+P 2 ) send newpath to neighbor S } path(Z,D,P 2 ),  Send path. S Matching variable Z = “Join” Pseudocode at node Z: while (receive )) { for each neighbor S { newpath = path(S,D,S+P2) send newpath to neighbor S }

20 R1: path(S,D,P)  link(S,D), P=(S,D). R2: path(S,D,P)  link(Z,S), path(Z,D,P 2 ), P=S+P 2. b dca SDP ab(a,b) SDP bc(b,c) SDP cd(c,d) Forwarding table: Query Execution link(S,D) path(S,D,P) Send path.S link.S=path.S R2 R1 SDPSDP SDP path Neighbor table: SD cb cd link SD bc ba SD ab SD dc Query: path(S,D,P,C)

21 R1: path(S,D,P)  link(S,D), P=(S,D). R2: path(S,D,P)  link(S,Z), path(Z,D,P 2 ), P=S+P 2. SDP ab(a,b) SDP bc(b,c) path SDP cd(c,d) Query Execution Forwarding table: SDP ab(a,b) ac(a,b,c) SDP bc(b,c) bd(b,c,d) bdc a p(b,d,[b,c,d])p(a,c,[a,b,c]) link(S,D) path(S,D,P) path.S link.S=path.S R2 R1 Neighbor table: SD cb cd link SD bc ba SD ab SD dc Query: path(S,D,P,C)

22 R1: path(S,D,P)  link(S,D), P=(S,D). R2: path(S,D,P)  link(S,Z), path(Z,D,P 2 ), P=S+P 2. b d c a path SDP cd(c,d) Query Execution Forwarding table: p(a,d,[a,b,c,d]) SDP ab(a,b) ac(a,b,c) SDP bc(b,c) bd(b,c,d) SDP ab(a,b) ac(a,b,c) ad(a,b,c,d) link(S,D) path(S,D,P) path.S link.S=path.S R2 R1 Neighbor table: SD cb cd link SD bc ba SD ab SD dc Query: path(S,D,P,C) Communication patterns are identical to those in the actual path vector protocol

23 Roadmap Execution Model Introduction to Datalog Path-Vector Protocol Example Distributed Datalog  Execution Plan  Protocol Advantages: Expressiveness Safety Efficiency Evaluation

24 Expressiveness Best-Path Routing Distance Vector Dynamic Source Routing Policy Decisions QoS-based Routing Link-state Multicast Overlays (Single-Source & CBT) Minor variants give many options!

25 R1: path(S,D,,C)  link(S,D,C) R2: path(S,D,,C)  C=C 1 +C 2, Query: path(S,D,,C) All-pairs all-paths: link(S,Z,C 1 ), path(Z,D,,C 2 ), Expressiveness, P=(S,D). P P P2P2 P=S+P 2. P

26 R1: path(S,D,P,C)  link(S,D,C), P= (S,D). R2: path(S,D,P,C)  link(S,Z,C 1 ), path(Z,D,P 2,C 2 ), C=C 1 +C 2, P= S+P 2. Query: bestPath(S,D,P,C) R3: bestPathCost(S,D,min )  path(S,D,Z,C) R4: bestPath(S,D,Z,C)  bestPathCost(S,D,C), path(S,D,P,C) Expressiveness Best-Path Routing:

27 R1: path(S,D,P,C)  link(S,D,C), P= (S,D). R2: path(S,D,P,C)  link(S,Z,C 1 ), path(Z,D,P 2,C 2 ), C=FN(C 1,C 2 ), P=S+P 2. Query: bestPath(S,D,P,C) R3: bestPathCost(S,D,AGG )  path(S,D,Z,C) R4: bestPath(S,D,Z,C)  bestPathCost(S,D,C), path(S,D,P,C) Expressiveness Best-Path Routing: Customizing C, AGG and FN: lowest RTT, lowest loss rate, highest available bandwidth, best-k

28 R1: path(S,D,,C)  link(S,D,C) R2: path(S,D,,C)  C=C 1 +C 2, Query: path(S,D,,C) All-pairs all-paths: link(S,Z,C 1 ), path(Z,D,,C 2 ), Expressiveness, P=(S,D). P P P2P2 P=S+P 2. P

29 R1: path(S,D,,C)  link(S,D,C) R2: path(S,D,,C)  link(S,Z,C 1 ), path(Z,D,,C 2 ), C=C 1 +C 2 Query: (S,D,,C) Distance Vector: Expressiveness D Z W R3: shortestLength(S,D,min )  path(S,D,Z,C) R4: nextHop(S,D,Z,C)  nextHop(S,D,Z,C), shortestLength(S,D,C) ZnextHop Count to Infinity problem?

30 R1: path(S,D,D,C)  link(S,D,C) R2: path(S,D,Z,C)  link(S,Z,C 1 ), path(Z,D,W,C 2 ), C=C 1 +C 2 R3: shortestLength(S,D,min )  path(S,D,Z,C) R4: nextHop(S,D,Z,C)  nextHop(S,D,Z,C), shortestLength(S,D,C) Query: nextHop(S,D,Z,C) Distance Vector with Split Horizon: Expressiveness, W!=S

31 R1: path(S,D,D,C)  link(S,D,C) R2: path(S,D,Z,C)  link(S,Z,C 1 ), path(Z,D,W,C 2 ), C=C 1 +C 2, W!=S R4: shortestLength(S,D,min )  path(S,D,Z,C) R5: nextHop(S,D,Z,C)  nextHop(S,D,Z,C), shortestLength(S,D,C) Query: nextHop(S,D,Z,C) Distance Vector with Poisoned Reverse: Expressiveness R3: path(S,D,Z,C)  link(S,Z,C 1 ), path(Z,D,W,C 2 ), C= , W=S

32 R1: path(S,D,P,C)  link(S,D,C), P= (S,D). R2: path(S,D,P,C)  C=C 1 +C 2, P=S+P 2. Query: path(S,D,P,C) All-pairs all-paths: link(S,Z,C 1 ), path(Z,D,P 2,C 2 ), Expressiveness

33 Switching Right-recursion to Left-recursion execution => Path vector protocol to DSR. Dynamic Source Routing (DSR): R1: path(S,D,P,C)  link(S,D,C), P= (S,D). R2: path(S,D,P,C)  C=C 1 +C 2, P= P 1 +D. Query: path(S,D,P,C) path(S,Z,P 1,C 1 ), link(Z,D,C 2 ),

34 Expressiveness Best-Path routing Distance Vector Dynamic Source Routing Policy-based routing QoS-based routing Link-state Multicast Overlays (Single-Source & CBT)

35 Safety Queries are sand-boxed within query engine Queries use input tables to produce output tables No side-effects on existing input tables Pure Datalog guarantees termination: Natural bound on resource consumption of queries Static termination checks for our extended Datalog: Identify recursive definitions and check for termination E.g., monotonically increasing/decreasing cost fields whose values are upper/lower bounded Orthogonal security issues: Denial-of-service attacks, compromised routers

36 Efficiency Explore well-known database techniques Aggregate selections: avoid sending unnecessary paths to neighbors Limit computation to portion of network  Few sources and destinations  Magic sets + left-right recursion rewrite Multi-query sharing:  Identify “similar” queries, share their computations  Reuse previously computed paths

37 Queries under Churn Long-running continuous queries Maintain all intermediate derived tuples for query duration Incremental updates: Link failures are treated as link updates with cost=infinity. Paths invalidated (cost=infinity), and new paths are incrementally recomputed.

38 Evaluation Setup PIER: Distributed relational query processor Each node runs the query engine of PIER Initialized neighbor table directly accessible by PIER. Simulation: Bandwidth and latency bottlenecks Transit-stub topologies PlanetLab 72 PIER nodes Random, location-aware topologies Long-running queries

39 Summary of Results Simulations: When all nodes issue the same query,  Scalability properties show similar trends as traditional DV/PV protocols When few nodes issue the same query,  Overhead is reduced using standard query optimizations PlanetLab experiments: Long-running all-pairs shortest RTT paths query Ability to handle link RTT changes Induced failures (up to 20% of nodes)  Recovery time: <1s (median), <3.6s (average)

40 Conclusion Declarative routing: Express routing protocols using a recursive query language Better balance between routing extensibility and safety Future work: Expressing policies as declarative rules Run-time query optimizations:  Cost-based decisions on query rewrites  Multi-query sharing Static checker for routing protocols Run-time monitoring of routing protocols Declarative Networks Research agenda: Specify and construct networks declaratively P2: “Implementing Declarative Overlays” (SOSP 2005)

41 Current Customizable Routing with Declarative Queries. (2004) Declarative Routing: Extensible Routing with Declarative Queries. (2005) Implementing Declarative Overlays. (2005) Declarative Networking: Language, Execution and Optimization. (2006) The Design and Implementation of Declarative Networks. (2006) Towards a Declarative Language and System for Secure Networking. (2007) A Declarative Perspective on Adaptive MANET Routing. (2008) MOSAIC: Unified Declarative Platform for Dynamic Overlay Composition. (2008) Declarative Network Verification. (2009) Declarative Reconfigurable Trust Management. (2009) Unified Declarative Platform for Secure Networked Information Systems. (2009) Declarative Toolkit for Rapid Network Protocol Simulation and Experimentation. (2009) A Theorem Proving Approach towards Declarative Networking. (2009) RapidMesh: Declarative Toolkit for Rapid Experimentation of Wireless Mesh Networks. (2009) Declarative Policy-based Adaptive MANET Routing. (2009) Declarative Networking. (2009) An Open-source and Declarative Approach Towards Teaching Large-scale Networked Systems Programming. (2011) NetTrails: A Declarative Platform for Provenance Maintenance and Querying in Distributed Systems. (2011)

42 Thank You

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