Presentation is loading. Please wait.

Presentation is loading. Please wait.

Policy-based Virtual Network Embedding across Multiple Domains

Similar presentations

Presentation on theme: "Policy-based Virtual Network Embedding across Multiple Domains"— Presentation transcript:

1 Policy-based Virtual Network Embedding across Multiple Domains
PolyViNE Policy-based Virtual Network Embedding across Multiple Domains Good afternoon everyone Mosharaf Chowdhury Fady Samuel, Raouf Boutaba UC Berkeley University of Waterloo

2 Virtual network embedding
is NP-hard 80 55 15 A B 10 22 a 12 c a a 90 50 10 12 10 20 C D E F b b c c 15 10 60 85 10 10 27 25 b VN Request (SP) G H 17 70 65 Substrate Network (InP)

3 Inter-domain ViNE D A C B

4 Bird’s-eye-view solution
Partitioning the VN request into K components Embedding individual components into K substrate networks Establishing inter-connection between them

5 Major challenges How do InPs and SPs find each other?
Framework for resource trading for rapid VN instantiation and fair value Without sacrificing local autonomy Tussles between contrasting utility functions InPs trying to maximize individual profits SPs trying to get the best price Secrecy and privacy concerns of the InPs Information on internal topology, resources etc. How do InPs and SPs find each other? How to ensure the best price? How to share information?

6 Approaches Full disclosure Third-party Minimal disclosure
Publicly available InP information Third-party InP information must be shared with the broker Possibility of monopoly (trust issues) Minimal disclosure No central entity Safest of the three, but the hardest as well

7 PolyViNE design choices
Decentralized embedding No central entity with knowledge of internal policies Local autonomy with global competition InPs are free to choose individual policies and embedding algorithms Competitive pricing at every stage of embedding Location assisted embedding Guided by the location constraints on virtual nodes and the location information of the substrate nodes

8 Workflow summary InP #1 InP #6 InP #4 InP #7 SP InP #2 InP #5 InP #3

9 Whether & how to embed locally?
InP workflow SP InP #1 InP #2 InP #3 InP #4 InP #5 InP #6 InP #7 Whether & how to embed locally? How to forward? Where to forward?

10 Location assisted forwarding
Informed request forwarding Minimize flooding Avoid unnecessary random forwarding Two components Hierarchical addressing scheme (COST) Location awareness protocol (LAP)

11 COST Hierarchical addressing scheme Continent.cOuntry.State.ciTy
Allows prefix aggregation Provides high flexibility in expressing virtual node location constraints Allows InPs to obfuscate topology information Continent.cOuntry.State.ciTy NA.CA.ON.Toronto: Node in Toronto NA.CA.ON.*: Node anywhere in Ontario

12 LAP: Location Awareness Protocol
InPs exchange LAP updates to build local policy compliant view of the InP network Each entry of an InP’s LAP database contains a mapping from a COST prefix to a set of paths to InPs with that prefix Each path has an associated estimated price

13 LAP Resource prices can rapidly fluctuate in a dynamic environment
Gossip is too slow to propagate price updates Staleness Use a hybrid of Gossip and Publish/Subscribe InPs can get direct and frequent updates

14 Simulation ViNE algorithms are hard to evaluate Simulation settings
What would be a representative input dataset? Which are the best metrics & how to measure them? Only look into simple convergence characteristics Simulation settings Based on settings used in existing intra-domain work 100 InPs with random links between them, each with nodes and links Max recursive probe depth set to 12

15 How many InPs must collaborate?

16 Summary PolyViNE is a policy-based inter-domain VN embedding framework
Local autonomy with global competition Decentralized location-assisted embedding using COST and LAP Possible future work (among many) Interaction between diverse local ViNE algorithm Game-theoretic analysis of the proposed scheme

17 Thanks! ? ? ?

18 Backup




Download ppt "Policy-based Virtual Network Embedding across Multiple Domains"

Similar presentations

Ads by Google