QoS-Based Web service Selection and Agreement Marco Comuzzi Dipartimento di Elettronica e Informazione Politecnico di Milano

2 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work QoS negotiation in SOA: goals  Introducing negotiation of QoS profile  Goals:  Improve matchmaking and service ranking  Dynamic generation of contracts on QoS  How:  Consider partial overlap of service offer and requirements  Automated Negotiation for contract Generation

3 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work QoS-Based service selection: Quality model  Scenario: 1 requestor, M (functionally equivalent) Web services j  Quality model  N (independent) QoS dimensions q i  K i ordered discrete QoS levels for each qi (ranges or single values) S i =(s i1,…,s iKi )  Response time K i =3 S resptime ={(0s,2s],(2s,3s], (3s,10s]}  Availability K i =2 S availability ={0.99,0.9999}  Service publication PUB j =  Service offer offer i  S i,  i  Additive pricing model price(s ik ) = s ik  (exploited in service ranking)  Service request REQ R =  QoS requirements reqs i  S i,  i  Importance of QoS dimensions priority={w 1,…,w N }  Strategy to be used in the negotiation  Available budget B

4 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work Service ranking  Matchmaking  Considering also Partial overlap of service offers and reqs  Intersection of service offer and reqs I ij  Service ranking  Scoring function:  Minimize price while maximizing overlap  penalize partial overlap offers (when I ij  reqs i ) with pen ij  Scoring mechanism equivalent to a multiattribute, reverse, sealed-bid auction  The lowest scoring WS provider sp is selected for service provisioning  Pricing models are adaptive:   s ik  =( sel j ( t )) s ik   t: counts the number of time a service is requested  sel j (t)  Provider j is selected (wins the auction). sel j (t)++  Provider j is not selected: sel j (t)--  Adaptation (at time t)  Increase applied price if selected in previous rounds  Decrease applied price when not selected  Objective: avoid winner’s curse and create market equilibrium

5 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work Exp. Results: Selection and Adaptive pricing  D is experiencing the winner’s curse (t<4)  A,B,D converge to the actual market valuation of the offered service  C starts from a too high initial evaluation (330% higher than A)

6 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work QoS profile Negotiation and Agreement  Negotiation with the selected provider sp  Extra budget EB = B – price sp (X min )  Two strategies to allocate EB (in the service request)  Horizontal: split EB proportionally to the service requestor’s priorities w i  Vertical: improve the QoS dimension of the highest priority until saturation, than try with the second highest priority QoS dimension….  The outcome is written in an electronic contract (WS-Agreement) Requestor’s priorities w i (5,1,1,3) Providers cost functions: QoS i=1  =1 β=1 QoS i=2  =1 β=1 QoS i=3  =0.1 β=1 QoS i=4  =0.1 β=1 HORIZONTAL VERTICAL

7 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work Exp. Results: Contract Efficiency  Only for the Horizontal strategy  Contracts remain close to the Pareto Frontier  Higher utility for increased extra budget and Quadratic pricing models  “Leaving money on the table” in case of Quadratic pricing models EB=20 EB=60 EB=20 EB=60

8 Outline QoS in SOA Modelling QoS and negotiation QoS-Based WS selection and agreement Data QoS syndication Network QoS negotiation Conclusion and future work Technological Overview  JBOSS (Servlet Container, WS deployment)  OraBPEL (Oracle WS-BPEL Process Engine)  MySQL (storing the service categorization)