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

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Presentation on theme: "Mobile Agents for e-commerce Rahul Jha Under the guidance of Prof. Sridhar Iyer KR School of Information Technology, IIT Bombay."— Presentation transcript:

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

2 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

3 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

4 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

5 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Mobility patterns and Implementation strategies

6 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Implementation strategies C C C 1 11 2 22 1 3 456 2 C 1 1 2 2 1 2 1 2 3 4 (a) Sequential Client Server (b) Sequential Mobile Agent (c) Parallel Client Server (d) Parallel Mobile Agent C Client Server Mobile Agent Message exchange Numbers along the arrows indicate the sequence of messages./ MA movement. 1 2 3 4 5 6

7 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

8 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation S tati c I tinerary S tatic O rder H1 H2H3 C Itinerary H4 H1H2H3H4 H1H2H3H4 Order Sequential CS Sequential MA Parallel CS Parallel MA Applicable Implementation Strategies

9 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation H1 H2H3 C Itinerary H4 H1H2H3H4 H1 Order ? S tati c I tinerary D ynamic O rder Sequential CS Sequential MA Parallel CS Parallel MA Applicable Implementation Strategies

10 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation H1 H2H3 C Itinerary H4 H1 Order ?? Sequential CS Sequential MA Parallel CS Parallel MA Applicable Implementation Strategies D ynamic I tinerary

11 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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.

12 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

13 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Parameters assumed constant (all workstations on the same LAN) network latencies on different links 10 ms to 1000 msprocessing time for servicing each request ~ catalog sizesize of client-server messages 20 KB to 1 MBsize of catalog 1 to 26number of stores RangeParameters

14 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Performance metric User 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.

15 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Effect of catalog size on Turnaround Time

16 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation processing = 20ms

17 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation processing = 500ms

18 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation processing = 1000ms

19 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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.

20 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

21 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Evaluation of Voyager, Aglets and Concordia

22 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Features VoyagerAgletsConcordia Category ORBMA based framework Java messagingTransparentNo MulticastYesNo Publish/SubscribeYesNo ScalabilitySpace No Authentication and security Strong implementation Weak implementation Strong implementation Agent persistenceYesNoYes Naming serviceFederatedNo Remote agent creation YesNo Grouping / Collective Logical Physical Garbage collectionYesNo Q ualitative C omparison

23 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Mobility pattern : Product discovery Q uantitative E valuation E xperiments assumed constant (all workstations on the same LAN) network latencies on different links 20 msprocessing time for servicing each request Kept constant for all 3 frameworksMessage packet size 1 MBsize of catalog 1 to 26number of stores RangeParameters Experimental setup : Same as that for previous experiments. Performance metric : User turnaround time

24 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Cost of message exchange Number

25 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Cost of code shipment

26 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

27 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Our Prototype of e-commerce application using mobile agents

28 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation Buyers GUI List of shops to visit and dockyards Product Request Template as XML Buyer's agent Salesman agent Product Catalog DB Shops agent Sales Transaction Log Local services Shopkeepers GUI SHOP Buyer SHOP A rchitecture of O ur P rototype M odel

29 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation I nteraction among C omponents Filtered Result

30 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation

31 KReSIT, IIT Bombay 16 th January 2001M.Tech Presentation 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

32 Thank You


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