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
Evaluation of Voyager, Aglets and Concordia
Our Prototype of e-commerce application
using mobile agents
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
e-commerce applications

Involve
–
–
–

Characterized by
–
–

Product search
Order Placement and confirmations
Negotiations
Large amount of data exchange
Client specific services
Require
–
–
Real time interactions
Disconnected (or low bandwidth) shopping
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
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
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Mobility patterns and
Implementation strategies
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Implementation strategies
2
3
C
2
1
4
3
5
6
Client
4
1
Server
C
C
(a) Sequential Client Server
(b) Sequential Mobile Agent
Mobile Agent
Message exchange
123456
2
2
1
2
1
2
1
2
1
(c) Parallel Client Server
16th January 2001
2
1
1
C
Numbers along the arrows
indicate the sequence of
messages./ MA movement.
C
(d) Parallel Mobile Agent
M.Tech Presentation
KReSIT, IIT Bombay
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

16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Static Itinerary Static Order
H1
H2
H3
H4
H1
H2
H3
H4
Order
Itinerary
C
H1
H2
H3
Applicable Implementation Strategies
16th January 2001
M.Tech Presentation
H4
•
•
•
•
Sequential CS
Sequential MA
Parallel CS
Parallel MA
KReSIT, IIT Bombay
Static Itinerary Dynamic Order
H1
H2
H3
H4
H1
Order
Itinerary
?
C
H1
H2
H3
Applicable Implementation Strategies
16th January 2001
M.Tech Presentation
H4
•
•
•
•
Sequential CS
Sequential MA
Parallel CS
Parallel MA
KReSIT, IIT Bombay
H1
Itinerary
Dynamic Itinerary
H1
?
Order
?
C
H1
H2
H3
Applicable Implementation Strategies
16th January 2001
M.Tech Presentation
H4
•
•
•
•
Sequential CS
Sequential MA
Parallel CS
Parallel MA
KReSIT, IIT Bombay
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.
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
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
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Parameters
Parameters
Range
number of stores
size of catalog
size of client-server
messages
processing time for
servicing each request
network latencies on
different links
1 to 26
20 KB to 1 MB
~ catalog size
16th January 2001
10 ms to 1000 ms
assumed constant
(all workstations on
the same LAN)
M.Tech Presentation
KReSIT, IIT Bombay
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.

16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Effect of catalog size on
Turnaround Time
14
Turnaround time (sec)
12
10
MA
8
CS of catalog size 100K
6
CS of catalog size 200k
CS of catalog size 500K
4
CS of catalog size 1MB
2
0
0
2
4
6
8
10
12
14
16
18
20
22
24
26
No. of shops visited
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
processing = 20ms
16
Turn around time (sec)
14
12
Sequential MA
10
8
Parallel MA
6
Sequential CS
4
Parallel CS
2
0
0
2
4
6
8
10
12
14
16
18
20
22
24
26
No. of shops visited
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
processing = 500ms
30
Turnaround time (sec)
25
20
Sequential MA
15
Parallel MA
Sequential CS
10
Parallel CS
5
0
0
2
4
6
8
10
12
14
16
18
20
22
24
26
No. of shops visited
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
processing = 1000ms
45
40
Turn around time (sec)
35
30
Sequential MA
25
Parallell MA
20
Sequential CS
15
Parallel CS
10
5
0
0
2
4
6
8
10
12
14
16
18
20
22
24
26
No. of shops visited
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
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.
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
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
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Evaluation of Voyager, Aglets
and Concordia
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Qualitative Comparison
Voyager
Aglets
Concordia
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
Garbage collection
Yes
Features
Category
16th January 2001
Physical
No
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Physical
No
KReSIT, IIT Bombay
Quantitative Evaluation Experiments




Mobility pattern : Product discovery
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)
Experimental setup : Same as that for
previous experiments.
Performance metric : User turnaround time
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Cost of message exchange
User turm around time in
sec
Message exchange cost for different mobile agent
frameworks
25
20
Concordia
15
Voyager
10
Aglets
5
0
1
2
10
50
100
200
300
400
500
Number of message packets
Numner
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Cost of code shipment
Code shipment cost for different mobile agent framework
2500
Time in ms
2000
Concordia
1500
Aglets
1000
Voyager
500
0
0
2
4
6
8
10
12 14
16
18
20 22
24
26
No of shops
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
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
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Our Prototype of e-commerce
application using mobile
agents
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Architecture of Our Prototype Model
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
16th January 2001
DB
DB
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Salesman agent
Salesman agent
Salesman agent
Local
services
Product Catalog
KReSIT, IIT Bombay
Interaction among
Components
Filtered Result
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
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
16th January 2001
M.Tech Presentation
KReSIT, IIT Bombay
Thank You