Presented by Rich Goyette Using AHP/TOPSIS with Cost and Robustness Criteria for Virtual Network Node Assignment Rich Goyette Presented by Rich Goyette 22/09/2018

Overview Virtual Networking Context; Motivation; InP Selection Criteria; Using AHP/TOPSIS to Rank InPs Simulation Results Conclusions Future Work 22/09/2018

4Ward Virtual Networking Service Provider (SP) Logical Plane Physical Plane Requirements Virtual Network Provider (VNP) Infrastructure Provider 1 (InP 1) Provider 2 (InP 2) Provider 3 (InP 3) Attribute Search and Comparison 22/09/2018

Motivation: Choosing InPs 1 2 3 4 InP 4 1 2 3 InP 2 3 1 2 4 5 2 3 5 2 3 4 5 MapQuest Who gets the SP’s Business? 22/09/2018

InP Selection Criteria We select the best VNet based on: Cost (less is better) Robustness (more is better) Robustness: the product of Security and Assurance Value of an InP’s offered VNet: VAS and VSEC can be computed using attributes reported by each InP... 22/09/2018

InP Selection Criteria Preference Model based on security relevant attributes of the InP. Weight of each dimension of security (FIPS 199). 22/09/2018

InP Selection Criteria In this presentation we consider nodes only. Therefore: We assume nC=0.5, nI=0.25, nA=0.25 We assume VAS is a random variable on [0,1] 22/09/2018

Overview of Selection Process 22/09/2018

Overview of Selection Process 22/09/2018

Overview of Selection Process 22/09/2018

Overview of Selection Process 22/09/2018

AHP/TOPSIS How do we select “best” when you must: Minimize some criteria; Maximize some criteria; Analytic Hierarchy Process Technique for Order Preference by Similarity to Ideal Solution 22/09/2018

InP Ranking with AHP/TOPSIS Bid 1 Bid 2 (Composite) 22/09/2018

InP Ranking with AHP/TOPSIS ❶ Construct Decision Matrix Bi -> one of k bids; Cj -> one of m criteria; fkm -> performance R C 22/09/2018

InP Ranking with AHP/TOPSIS ❷ Normalize the Decision Matrix R C 22/09/2018

InP Ranking with AHP/TOPSIS ❸ Weight the decision Matrix R C 22/09/2018

InP Ranking with AHP/TOPSIS ❹ Positive Ideal Solution -> Max security, min cost. R C PIS=[0.43 0.31] ❺ Negative Ideal Solution -> Min security, max cost. NIS=[0.26 0.40] R C ❻Separation -> Distance from PIS, NIS 22/09/2018

InP Ranking with AHP/TOPSIS ❼Closeness -> Smallest distance from best, largest distance from worst. Choose Bid 2 even though it costs more! 22/09/2018

InP Ranking with AHP/TOPSIS Composite Bid Evaluation... Who gets each disputed node? 22/09/2018

InP Ranking with AHP/TOPSIS Composite Bid Evaluation... ❶ Perform TOPSIS on each disputed node and select Best InP. ❷ Compute composite cost and robustness. Participation 1/5 1/5 3/5 22/09/2018

Simulation TOPSIS selection versus Greedy (cost only). 60X60 grid with 30 substrate nodes. Variable sized InPs with random robustness profiles distributed over substrate. 10,000 simulation runs per robustness weight point. 22/09/2018

Conclusions VNet robustness considers security and assurance dimensions; AHP/TOPSIS provides an efficient way of ranking InPs when criteria optimize in different directions: Robustness Cost AHP/TOPSIS can scale to other criteria: QoS Etc. 22/09/2018

Future Work Our work focussed on offering lowest compliant value of zero-delta security attributes (e.g. encryption key length). To what extent could aggressive business policies increase average security using these attributes? How many InPs in a composite bid? 22/09/2018

Questions 22/09/2018