1 Inter-Domain Routing: Stability, Policies, and Incentives Vijay Ramachandran Supported by the DoD URI program under ONR grant N
2 Overview of Results: Two SPYCE-Sponsored Collaborations Aaron Jaggard - Framework for design and analysis of inter-domain routing protocols - Expanded to include more complex policies NEW Joan Feigenbaum and Michael Schapira NEW - New class of policies for BGP-based, incentive-compatible routing; partially answers goal for option period
3 Inter-Domain Routing Establish routes between autonomous systems (ASes). UUNET AT&T Comcast Qwest Currently done with the Border Gateway Protocol (BGP).
4 Why is Inter-Domain Routing Hard? Route choices are based on local policies. Autonomy: Policies are uncoordinated. Expressiveness: Policies are complex. Load-balance my outgoing traffic. UUNET Always choose shortest paths. AT&T Comcast My link to UUNET is for backup purposes only. Qwest Avoid routes through AT&T if at all possible.
5 Three Desiderata Incentive Compatibility Lowest-Cost Routing Backward Compatibility Policy Routing Realistic Routing Model BGP Can get 2 out of 3 2 are SPYCE achievements Open question for option: Can we satisfy all 3?
6 Yes! Realistic Routing Model Next-hop routing with today s Internet business relationships. Incentive Compatibility Backward Compatibility Optimal routing tree given nodes valuations; incentivize nodes to report truthful valuations using VCG payments. Compute routes and payments in a BGP-compatible way.
7 BGP Route Processing Receive routes from neighbors Store routes Choose best route Send updates to neighbors Pros: - Route choices depend on neighbors choices. => enforces consistency - Best-route choices are made locally. => allows autonomy & expressiveness. - Routes are loop free and can change with topology, without any node s knowing the whole network. Cons: - Policy-induced routing anomalies => Routes may not be stable.
8 SPYCE Contributions: Policy Constraints for Stability Local constraint (equivalent to per-path lowest-cost routing) + No global constraint or No Expressiveness No Autonomy Stability Policies compatible with generalizations of Internet hierarchy + Global constraint Expressiveness Autonomy Stability Generation algorithm Enforcement algorithms (centralized or distributed)
9 Expanding the Model Update Messages Import Policy Route Selection Export P 1 P 2 rank 1 rank 2 rank 2 is lowest => choose P 2 P 2 P 3 rank 3 Rank is determined independently for each path based on attributes SPP/PVPS Update Messages Generalized Route Selection Export P 1 P 2 P 3 P 1 P 2 selection function P 3 P 2 Each node has a selection function mapping sets of routes to a single best route P 2 GSPP/GPVPS
10 Results about GSPP / GPVPS Ability to model ibgp and complex BGP features, e.g., MED Analogous sufficient conditions for stability in the general case, e.g., the absence of generalized dispute wheels Improved space efficiency for methods to fix oscillations in BGP
11 Welfare-Maximizing Routing Private information: Route valuations Strategies v 1 (.) v n (.) AS 1 AS n a 1 a n p 1 p n Mechanism Routes R 1,, R n Maximize sum of nodes valuations = i v i (R i ). A confluent routing tree and payments are computed in parallel for each destination. Source nodes are paid for their contribution to the routing tree. We want a BGP-style algorithm that computes routes and payments.
12 SPYCE Results: Welfare Maximization and Inter-Domain Routing Routing-Policy Class LCP General Policy Next Hop Subjective Cost Forbidden Set Good Centralized Algorithm? (and hard to approximate) (incl. some special cases) Good Distributed Algorithm? (and hard to approximate) (approx. is easy if >1 tree)
13 General Approach Find a class of policies for which BGP converges to an optimal tree T (i.e., one that maximizes the sum of the valuations of all source nodes). Use VCG payment formula to ensure truthfulness, i.e., payment to node k is p k = i k v i (T) h k ( ) where h k is a function that does not depend on node k s valuation.
14 Gao-Rexford Framework (1) Neighboring pairs of ASes have one of: - a customer-provider relationship (One node is purchasing connectivity from the other node.) - a peering relationship (Nodes have offered to carry each other s transit traffic, often to shortcut a longer route.) peer peer providers customers
15 Gao-Rexford Framework (2) Global constraint: no customer-provider cycles Local preference and scoping constraints, which are consistent with Internet economics: Preference Constraints i k 1 k 2 R R If k 1 and k 2 are both customers, peers, or providers of i, then either ik 1 R 1 or ik 2 R 2 can be more valued at i. If one is a customer, prefer the route through it. If not, prefer the peer route. d Scoping Constraints provider i customer j k peer m Export customer routes to all neighbors and export all routes to customers. Export peer and provider routes to all customers only. d Gao-Rexford conditions => no dispute [GR01, GGR01]
16 Realistic Policies for Incentive-Compatible Routing Next-hop valuations: The valuation of a route depends only on its next hop. Theorem: If ASes obey Gao-Rexford conditions and next-hop valuations: - BGP computes the optimal (welfaremaximizing) routing tree. - VCG payments can be computed along with routes, with only small increase in routingtable size (like LCP).
17 Summary of Sufficient Conditions No assumptions No dispute cycle No dispute cycle and policy consistency No dispute cycle and next-hop valuations (special case of policy consistency) Hard (BGP may not converge) Non-optimal (BGP will converge, but the solution may be arbitrarily far from optimal.) Optimal convergence (but payment computation might be highly space-consuming) Optimal convergence and good BGP-style algorithm (Requires O(1) additional space per transit node.)