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  • Expiration a duration or timestamp? VOCe equation at the bottom Explain subscript
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    1. 1. 16 th International World Wide Web Conference Speeding up Adaptation of Web Service Compositions Using Expiration Times John Harney , Prashant Doshi LSDIS Lab, Dept. of Computer Science, University of Georgia
    2. 2. Web Process Adaptation <ul><li>Most Web service compositions assume static environments </li></ul><ul><ul><li>Service providers’ QoS parameters remain constant </li></ul></ul><ul><li>Many environments are dynamic </li></ul><ul><ul><li>Examples: </li></ul></ul><ul><ul><ul><li>Supply Chain service provider’s rate of order satisfaction may decrease </li></ul></ul></ul><ul><ul><ul><li>Cost of using a service increases due to increase in price </li></ul></ul></ul><ul><ul><ul><li>Service response time increases due to network difficulties </li></ul></ul></ul>
    3. 3. Optimal Web Service Composition <ul><li>“ Optimality” – minimization of cost of using all services to complete process </li></ul><ul><li>Underlying objective – maintain Web process optimality </li></ul><ul><ul><ul><li>Depends on how accurately the QoS parameters are captured </li></ul></ul></ul><ul><ul><ul><li>Requires knowing any changes in QoS that may have occurred </li></ul></ul></ul>
    4. 4. Motivating Scenario – Supply Chain Manufacturer needs to order parts from a series of suppliers Supply Chain Process Start Finish Invoke Response Spot Market Service Rate of Order Satisfaction Preferred Supplier Service Rate of Order Satisfaction Other Supplier Service Rate of Order Satisfaction Inventory Service Rate of Order Satisfaction  Response Invoke Inventory satisfaction rate decreases Preferred Supplier may be better choice
    5. 5. Web Process Composition Using MDPs <ul><li>We use Markov Decision Processes (MDP) to model our Web process (JWSR 05) </li></ul><ul><ul><li>Components (states, actions, transition, cost) represent different aspects of the process </li></ul></ul><ul><ul><li>We solve the MDP to get the optimal policy </li></ul></ul><ul><ul><ul><li>Policy determines the optimal decision to make at a particular state of the process </li></ul></ul></ul><ul><ul><ul><li> n : S  A </li></ul></ul></ul>
    6. 6. Overview of Previous Approach <ul><li>VOC – Value of Changed Information (ICSOC ’06) </li></ul><ul><ul><li>Decides if obtaining information is: </li></ul></ul><ul><ul><ul><li>Useful </li></ul></ul></ul><ul><ul><ul><ul><li>Will it induce a change in optimality of Web process? </li></ul></ul></ul></ul><ul><ul><ul><li>Cost-efficient </li></ul></ul></ul><ul><ul><ul><ul><li>Is the information worth the cost of obtaining it? </li></ul></ul></ul></ul><ul><li>Extension of Value of Information </li></ul>
    7. 7. Overview of Previous Approach <ul><li>VOC </li></ul><ul><ul><li>Measures how “badly” the current process is performing in changed environment </li></ul></ul><ul><ul><li>Defined as the difference between: </li></ul></ul><ul><ul><ul><li>Expected performance of the old process in the changed environment </li></ul></ul></ul><ul><ul><ul><li>Expected performance of the best process in the changed environment </li></ul></ul></ul>
    8. 8. Overview of Previous Approach <ul><li>We find and use the maximum VOC value </li></ul><ul><li>VOC*(s) = max a€A VOC(s) </li></ul><ul><li>Adaptation Procedure: </li></ul>… Provider 1 VOC VOC* Keep current policy Query Provider Re-solve policy if needed VOC* < Cost of Querying VOC* > Cost of Querying Provider 2 Provider n VOC Candidate Processes
    9. 9. Expiration Times <ul><li>VOC*: Must compute VOC for EVERY Web service at every state of the process </li></ul><ul><li>Focus on services whose QoS parameters may change </li></ul><ul><ul><li>Many services give guarantees of QoS parameters </li></ul></ul><ul><ul><li>Period of guarantee is the expiration time </li></ul></ul>
    10. 10. VOC ε - VOC with Expiration Times <ul><li>VOC ε allows us to find the max VOC using a smaller set of services </li></ul><ul><li>Theorem </li></ul><ul><ul><li>Given identical policies and start states, adaptation using VOC ε and VOC* generate identical Web processes </li></ul></ul>
    11. 11. Specification of Expiration Times <ul><li>Expiration times could be specified using a WS-Agreement </li></ul>GPU Provider guarantees “ 40% availability” Expires on 27 Jan 2007
    12. 12. VOC ε - VOC with Expiration Times <ul><li>How do we know which services have not expired? </li></ul><ul><ul><li>Maintain a time counter t a for each service during composition and execution of the process </li></ul></ul><ul><ul><li>Increment the time counters of the services as the composition algorithm progresses </li></ul></ul><ul><ul><li>If t a > expiration time, the service is added to VOC ε set </li></ul></ul>Query for information t a ← t a + t Qlag t a ← t a + t response t a ← t a + t VOC ε Find VOC ε Wait for provider’s response
    13. 13. VOC ε - VOC with Expiration Times <ul><li>Query Lag Time – time needed for the process to receive QoS information from service provider </li></ul>
    14. 14. VOC ε - VOC with Expiration Times <ul><li>Response Time - time needed for the process to receive service provider response </li></ul>
    15. 15. Adaptive Web Process Composition Using VOC ε <ul><li>Revised Adaptation procedure for VOC </li></ul>… Provider 1 VOC VOC ε Keep current policy Query Provider Re-solve policy if needed VOC ε < Cost of Querying VOC ε < Cost of Querying Provider 2 Provider n VOC Candidate Processes First eliminate non-expired services Then proceed in the same manner
    16. 16. VOC ε - VOC with Expiration Times <ul><li>In the worst case, the complexity of VOC ε is the same as VOC* </li></ul><ul><ul><li>Occurs when all services have expired </li></ul></ul><ul><li>In the best case, VOC ε is not needed </li></ul><ul><ul><li>Occurs when no services have expired </li></ul></ul><ul><li>In the average case, VOC ε performs in between </li></ul><ul><ul><li>Shown empirically </li></ul></ul>
    17. 17. Empirical Results <ul><li>Measured the average process cost over different costs of querying </li></ul><ul><ul><li>Query random strategy – randomly pick a service to query </li></ul></ul><ul><ul><li>Do nothing strategy – do no adaptation </li></ul></ul><ul><ul><li>VOC ε strategy </li></ul></ul>Supply Chain Scenario Patient Transfer Clinical Pathway
    18. 18. Empirical Results <ul><li>Computational Time Savings </li></ul><ul><ul><li>Measured the average process execution time over a range of expiration times </li></ul></ul><ul><ul><ul><li>VOC* is the upper bound - VOC ε does no worse </li></ul></ul></ul><ul><ul><ul><li>Do nothing is the lower bound </li></ul></ul></ul><ul><ul><ul><li>VOC ε process execution times occur between the two bounds </li></ul></ul></ul>Supply Chain Scenario Patient Transfer Clinical Pathway
    19. 19. Discussion <ul><li>Intelligent adaptation mechanisms (eg VOC) are expensive </li></ul><ul><ul><li>VOC computational overhead </li></ul></ul><ul><ul><li>Compute VOC for all services </li></ul></ul><ul><li>VOC ε approach </li></ul><ul><ul><li>Uses expiration times to reduce the set of candidate services </li></ul></ul><ul><li>Future work </li></ul><ul><ul><li>Address VOC computational overhead </li></ul></ul>
    20. 20. <ul><li>Thank you </li></ul><ul><li>Questions </li></ul>

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