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Mobile Agents for e-commerce

Mobile Agents for e-commerce . Rahul Jha Under the guidance of Prof. Sridhar Iyer. KR School of Information Technology , IIT Bombay. Overview. Mobile Agent applications in e-commerce Mobility Patterns and implementation strategies Quantitative performance evaluation of Voyager

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Mobile Agents for e-commerce

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  1. Mobile Agents for e-commerce Rahul Jha Under the guidance of Prof. Sridhar Iyer KR School of Information Technology , IIT Bombay

  2. Overview • Mobile Agent applications in e-commerce • Mobility Patterns and implementation strategies • Quantitative performance evaluation of Voyager • Evaluation of Voyager, Aglets and Concordia • Our Prototype of e-commerce application using mobile agents M.Tech Presentation

  3. e-commerce applications • Involve • Product search • Order Placement and confirmations • Negotiations • Characterized by • Large amount of data exchange • Client specific services • Require • Real time interactions • Disconnected (or low bandwidth) shopping M.Tech Presentation

  4. Mobile Agent advantages • Mobile agents (MA) • “A mobile agent is a program that can autonomously migrate between the various nodes of a network and perform computations on behalf of the user” • MA advantages • reduce network usage • faster response times • add client-specified functionality to servers • increase asynchrony between clients and servers • introduce concurrency M.Tech Presentation

  5. Mobility patterns and Implementation strategies M.Tech Presentation

  6. Implementation strategies 2 3 C Client 4 5 6 2 3 1 4 1 Server C C Mobile Agent (a) Sequential Client Server (b) Sequential Mobile Agent Message exchange Numbers along the arrows indicate the sequence of messages./ MA movement. 1 2 3 4 5 6 2 2 2 2 1 2 1 2 1 1 1 1 C C (c) Parallel Client Server (d) Parallel Mobile Agent M.Tech Presentation

  7. Mobility Pattern Parameters Definitions Itinerary the set of sites that an MA has to visit • static • dynamic Order the order in which an MA visits sites in its itinerary. • static • dynamic M.Tech Presentation

  8. Static Itinerary Static Order H1 H2 H3 H4 H1 H2 H3 H4 Order Itinerary C H1 H2 H3 H4 • Sequential CS • Sequential MA • Parallel CS • Parallel MA Applicable Implementation Strategies M.Tech Presentation

  9. Static Itinerary Dynamic Order ? H1 H2 H3 H4 H1 Order Itinerary C H1 H2 H3 H4 • Sequential CS • Sequential MA • Parallel CS • Parallel MA Applicable Implementation Strategies M.Tech Presentation

  10. Dynamic Itinerary ? ? H1 H1 Order Itinerary C H1 H2 H3 H4 • Sequential CS • Sequential MA • Parallel CS • Parallel MA Applicable Implementation Strategies M.Tech Presentation

  11. Experimentation and results • The e-commerce application • A single client searching for information about a particular product from the catalog of several on-line stores • We assume that the client requires a highly customized search which the on-line store does not support. M.Tech Presentation

  12. Experimentation • Experimental setup • Voyager™ Framework for MA implementations • Java™ socket based implementation for client server interaction • On Pentium-III, 450 MHz workstations connected through a 10 Mbps LAN with typical student load M.Tech Presentation

  13. Parameters Range number of stores 1 to 26 size of catalog 20 KB to 1 MB size of client-server messages ~ catalog size processing time for servicing each request 10 ms to 1000 ms network latencies on different links assumed constant (all workstations on the same LAN) Parameters M.Tech Presentation

  14. Performance metricUser Turnaround Time • time elapsed between • a user initiating a request and receiving the results. • equals time taken for • agent creation + • visit / collect catalogs + • processing time to extract information. M.Tech Presentation

  15. Effect of catalog size on Turnaround Time M.Tech Presentation

  16. processing = 20ms M.Tech Presentation

  17. processing = 500ms M.Tech Presentation

  18. processing = 1000ms M.Tech Presentation

  19. Observations • Mobility patterns determine the implementation strategies • Sequential CS most suitable where • a small amount of information has to be retrieved from few remote information sources. • Parallel implementations effective when • processing information contributes significantly to the turnaround time. M.Tech Presentation

  20. Observations • Mobile agents out perform traditional approaches when • When the cost of shipping MAs < message exchange size. • MAs scale effectively across the parameters of E-commerce application M.Tech Presentation

  21. Evaluation of Voyager, Aglets and Concordia M.Tech Presentation

  22. Qualitative Comparison Features Voyager Aglets Concordia Category ORB MA based framework MA based framework Java messaging Transparent No No Multicast Yes No No Publish/Subscribe Yes No No Scalability Space No No Authentication and security Strong implementation Weak implementation Strong implementation Agent persistence Yes No Yes Naming service Federated No No Remote agent creation Yes No No Grouping / Collective Logical Physical Physical Garbage collection Yes No No M.Tech Presentation

  23. Parameters Range number of stores 1 to 26 size of catalog 1 MB Message packet size Kept constant for all 3 frameworks processing time for servicing each request 20 ms network latencies on different links assumed constant (all workstations on the same LAN) Quantitative Evaluation Experiments • Mobility pattern : Product discovery • Experimental setup : Same as that for previous experiments. • Performance metric : User turnaround time M.Tech Presentation

  24. Cost of message exchange Number M.Tech Presentation

  25. Cost of code shipment M.Tech Presentation

  26. Observations • Voyager supports almost the super set of functionalities and features as compared to Aglets and Concordia. • Voyager being an ORB has advanced messaging support and hence performs much better than Aglets and Concordia. • Cost of code shipment for Voyager is more than Concordia (both user RMI) • Voyager is an ORB with mobility support • Large set of functionalities supported by Voyager M.Tech Presentation

  27. Our Prototype of e-commerce application using mobile agents M.Tech Presentation

  28. Buyer Buyer's agent Buyers GUI Product Request Template as XML List of shops to visit and dockyards SHOP SHOP SHOP Shopkeepers GUI Shops agent Sales Transaction Log DB Product Catalog Local services DB Salesman agent Salesman agent Salesman agent Architecture of Our Prototype Model M.Tech Presentation

  29. Interaction among Components Filtered Result M.Tech Presentation

  30. M.Tech Presentation

  31. Conclusion • Helps user with tedious repetitive job and time consuming activities. • Faster and real time interacting at shops • Reducing network load • Support for disconnected operation. • Introduce concurrency of operations • Client specific functionalities at the shops M.Tech Presentation

  32. Thank You

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