1. ViNE_Yard (Virtual Network Embedding with Coordinated Node and Link Mapping)

2. What is VN Embedding? Given: Task :
Single substrate network: Gs=(Ns,Es)
Online VN request : GV=(NV,EV)
Requirements and Constraints of virtual nodes and virtual links.
Task :
Assign virtual nodes and links to substrate nodes and links.
Allocate resources
CPU, bandwidth

3. VN Embedding Objectives
Maximize
Acceptance ratio
Percentage of request accepted
Revenue
Based on resources requested for a VN
Minimize
Cost
Based on substrate network resource allocated for embedding VN request.

4. ViNE Algorithm D_ViNE (Deterministic Virtual Network Embedding)
R_ViNE (Random Virtual Network)

5. Virtual Network Embedding problem
Substrate Network : Gs=(Ns,Es)
Ns : the set of substrate nodes
Es : the set of substrate links
ns € Ns :substrate node
c(ns) : CPU capacity
loc(ns): geographic location of ns.
es(i,j) € Es : substrate link between node i và j
b(es): total amount of bandwidth.
Ps(s,t) : substrate path from source node s to destination node t.

6. Virtual Network Embedding problem

7. Virtual Network Embedding problem
2. Virtual Network Request
Gv=(Nv,Ev)
Nv : the set of virtual node
Ev : the set of virtual link
Dv > 0 :expressing how far a virtual node nv€Nv can be placed from the location specified by loc(nv).

8. Virtual Network Embedding problem
3. Residual Capacity of substrate Resources
A substrate node stress
SN(ns) : the total amount of CPU capacity allocated to virtual nodes hosted on the substrate node.
A substrate link stress
SE(es) : the total amount of bandwidth reserved for the virtual links

9. Virtual Network Embedding problem
Residual of substrate node:
Residual of substrate link
Total amount of bandwidth on substrate path

10. Virtual Network Embedding problem
4. Virtual Network Assignment
Node assignment
Subject to

11. Virtual Network Embedding problem
Link assignment
Subject to

12. Virtual Network Embedding problem
4. MIP formulation for optimal Embedding VN.
4.1. Substrate Graph Augmentation

13. Virtual Network Embedding problem
4.2 MIP formulation
Variable
A flow variable denoting the total amount of the flow in the on the substrate edge(u,v) for the i’th virtual edge
A binary variable, which has the value =‘1’ if
else =‘0’

14. Virtual Network Embedding problem
Objective
Parameter to control the importance of load balancing while embedding request.

15. Virtual Network Embedding problem
Contraints
Capacity Contraints:
The node and edge capacity bound
To ensure summation of flows on both direction remain within available bandwidth.

16. Virtual Network Embedding problem
Flow Related Contraints:

17. Virtual Network Embedding problem
Meta and Binary Constraints:
Related to the augmented portition of substrate graph
Make sure that only one substrate node is selected for each meta-node.
Domain Constraints:

18. D-ViNE:Deterministic Rounding-based Virtual Network Embedding Algorithm

19. D-ViNE:Deterministic Rounding-based Virtual Network Embedding Algorithm
Creating an augmented substrate graph GS’=(NS’,ES’)
Solve MIP formulation to get fractional solution
Checking where there are any unmapped substrate nodes within its feasible region

20. Virtual Network Embedding problem