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

Mobile Agents for e-Mobile Agents for e-commerce commerce

Rahul JhaUnder the guidance of Prof. Sridhar Iyer

KR School of Information Technology , IIT Bombay

16th January 2001 M.Tech PresentationKReSIT, IIT Bombay

OverviewOverview

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


e-commerce applicationse-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


Mobile Agent advantages 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


Mobility patterns and Mobility patterns and Implementation strategiesImplementation strategies


Implementation strategiesImplementation strategies

C

C

C

1

1 1

2

221

3 4 5 6

2

C

1 1

22

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


Mobility Pattern Mobility Pattern ParametersParameters

DefinitionsItinerary the set of sites that an MA has

to visit staticdynamic

Order the order in which an MA visits sites in its itinerary.

static dynamic


SStatitaticc I Itinerarytinerary S Statictatic O Orderrder

H1 H2 H3

C

Itinerary

H4

H1 H2 H3 H4 H1 H2 H3 H4

Order

• Sequential CS • Sequential MA • Parallel CS • Parallel MA

Applicable Implementation Strategies


H1 H2 H3

C

Itinerary

H4

H1 H2 H3 H4 H1

Order?

SStatitaticc I Itinerarytinerary D Dynamic ynamic OOrderrder




H1 H2 H3

C

Itinerary

H4

H1 H1

Order? ?



DDynamic ynamic IItinerarytinerary


Experimentation and Experimentation and resultsresults

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.


ExperimentationExperimentation

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


ParametersParameters

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


Performance metricPerformance metric User Turnaround TimeUser 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.


Effect of catalog size on Effect of catalog size on Turnaround Time Turnaround Time

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12 14 16 18 20 22 24 26

No. of shops visited

Tu

rna

rou

nd

tim

e (

sec

)

MA

CS of catalog size 100K

CS of catalog size 200k

CS of catalog size 500K

CS of catalog size 1MB


processing = 20msprocessing = 20ms

0

2

4

6

8

10

12

14

16

0 2 4 6 8 10 12 14 16 18 20 22 24 26


Tu

rn a

rou

nd

tim

e (

se

c)

Sequential MA

Parallel MA

Sequential CS

Parallel CS



0

5

10

15

20

25

30

0 2 4 6 8 10 12 14 16 18 20 22 24 26


Tu

rnar

ou

nd

tim

e (s

ec)

Sequential MA

Parallel MA

Sequential CS

Parallel CS



0

5

10

15

20

25

30

35

40

45

0 2 4 6 8 10 12 14 16 18 20 22 24 26


Tu

rn a

rou

nd

tim

e (s

ec) Sequential MA

Parallell MA

Sequential CS

Parallel CS


ObservationsObservations 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.


ObservationsObservations

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


Evaluation of Voyager, Evaluation of Voyager, Aglets and ConcordiaAglets and Concordia


Features Voyager Aglets Concordia

Category

ORBMA 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

QQualitativeualitative C Comparisonomparison


Mobility pattern : Product discovery

QQuantitative uantitative EEvaluationvaluation E Experimentsxperiments

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 frameworks

Message 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


Cost of message exchangeCost of message exchange

Message exchange cost for different mobile agent frameworks

0

5

10

15

20

25

1 2 10 50 100 200 300 400 500

Numner of message packets

User

turm

aro

un

d t

ime i

n

sec

Concordia

Voyager

Aglets

Number


Cost of code shipmentCost of code shipment

Code shipment cost for different mobile agent framework

0

500

1000

1500

2000

2500

0 2 4 6 8 10 12 14 16 18 20 22 24 26

No of shops

Tim

e in

ms

Concordia

Aglets

Voyager


ObservationsObservations

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


Our Prototype of e-Our Prototype of e-commerce application commerce application using mobile agentsusing mobile agents


Buyers GUI

List of shops to visit and dockyards

Product Request Template as

XML

Buyer's agent

Salesman agentSalesman agentSalesman agent

Product CatalogDBDB

Shops agent

Sales Transaction Log

Local services

ShopkeepersGUI

SHOP

Buyer

SHOP

SHOP

AArchitecture ofrchitecture of O Ourur P Prototype rototype

MModelodel


IInteraction nteraction among among

CComponentsomponents

Filtered Result



ConclusionConclusion

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

Thank You Thank You

Documents

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