Transcript Design and Modeling of the E-Learning using

Modeling and Analysis of e-Learning
Advisor: Dr. Nandana Rajatheva
Surya Bahadur Kathayat
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E-Learning
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dicole.org
moodle.org
OurWeb (Kurhila, 2006)
EDUCO (Kurhila et al. 2003)
WebCT.com
APPLE (Jin et al., 2004)
LL2 (Brue et al., 2005)
Edutella (Nilsson et al., 2005)
ALM for group communication (Scribe,
Bayeux, Brog)
E-Learning
GROUPING OF
LEARNERS
TECHNOLOGIES
MANAGEMENT
MECHANISMS
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E-LEARNING
CONTENTS &
SERVICES
E-Learning - technologies
Client-Server based e-Learning
model
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Peer-to-Peer based e-Learning model
E-Learning - technologies
• Limitations of C/S based systems:
content/infrastructure based; overhead, scalability,
interactivity, collaboration; resource sharing
• Lack of efficient use of P2P technologies in e-Learning,
lack of consideration of the Interest of users in the elearning environment, almost all the present day groups
require apriori planning.
• Existing grouping mechanism in structured P2P are
either based on tree or mesh. No existing models for
group merging, group splitting. Existing mechanisms
are having limited fault tolerance level. No group
adaptation mechanisms for e-Learning
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(ResourceNet, USA., 2005; Keegan et al., 2005; Kurhila et al., 2003, Paulsen, 2003,
Fernando, 2005; Rowstronand and Druschel, 2001; Nowell et al., 2003; Clarke, 2000;
Clarke, 2001. Jin et al., 2004; Brue et al., 2005; Nilsson et al., 2005)
Objective
MVRING BASED GROUP
COMMUNICATION PROTOCOL (design,
implementation and evaluation)
CONSISTING OF GROUP ADAPTATION
ALGORITHMS (interest based grouping,
number of virtual groups formation,
merging/splitting of common interest groups,
group maintenance etc) FOR THE ELEARNING DESIGN USING STRUCTURED
PEER-TO-PEER TECHNOLOGIES
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E-Learning – Abstract Model
LEARNERS
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TECHNOLOGIES
MANAGEMENT
E-LEARNING
CONTENTS &
SERVICES
Technological Infrastructure
File
Sharing
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Network
storage
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P2P application layer
Pastry
Structured P2P Protocol
(overlay network)
TCP/IP
Internet/Network Layer
 No need to change any
infrastructure, just implement on the
top of the application layer
Technological Infrastructure
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Structured P2P platform - Pastry
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Programming Languages used
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Each peer (on Internet or Application
identified by IP address+Port in local
machine) will run a application software and
specify its interest
Facilitates efficient routing
Java – JDK 1.4.2
NS-2 for simulation considering large
number of nodes
MVRing based application
layer multicasting protocol
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ALM protocol with group adaptation
algorithms
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Ring formation mechanism
MVRing formation mechanism
Data delivery mechanism with node
heterogeneity
Merge/Split mechanism
Group maintenance mechanisms
Duplicate data detection mechanism
Quantitative analysis
Quantitative analysis
Definitions
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Definitions
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Propositions
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Propositions
Theorems
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Summary
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Tree, Ring, Chordal Ring, MVRing, Fault
tolerance level, Hop count
Using TDP, delivery of packet from
source node to destinations traveling
across ‘E’ links takes ‘2E-1’ Time Frames
(TFs)
Network delay bound (NDB) of a ring
having N number of nodes is of the order
of O(N)
Network delay bound (NDB) of a tree
having N number of nodes is of the order
of O(logN)
Quantitative analysis
Quantitative analysis
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Theorems
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Definitions
Propositions
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Theorems
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Summary
Higher fault tolerance level
and Comparable latency
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NDB of MVRing is comparable with that
of general tree (with proposed data
delivery mechanism with duplicate data
rejection)
Data delivery mechanism proposed
MVRing is twice fault tolerant than that of
general Tree
Routing delay in MVRing scheme will be
improved by ‘X’ times (no of MVR
neighbors) compared to original single
ring provided that all single-hop path
length are equal.
Performance Evaluation
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CASE A: Internet Environment (Tested In Tc LAB)
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CASE B: Network simulator (Large Number of
Nodes) - 50 Routers
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1 to 35 Users in a group having internet connection
50, 150, 500 nodes as hosts in groups
T-S Topology for Internet Modeling (GT-ITM)
Concentrate on
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latency, fault tolerance, node degree, node stress/traffic
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Comparison of the result with the traditional group
communication models (if applicable) - Tree Based
protocol in the Structured P2P Network
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latency (msec)
Results – Latency, group size 15
src n2 MVRing
180
160
140
120
100
src n2 Scribe
src n3 MVRing
src n3 Scribe
src n4 MVRing
src n4 Scribe
80
60
40
20
0
src n5 MVRing
src n5 Scribe
src n6 MVRing
src n6 Scribe
1
2
3
4
5
6
7
8
9 10 11 12 13 14
receiving node sequence
src n7 MVRing
src n7 Scribe
Latency in MVRing and Scribe based 15-member multicast group with one of
nodes 2 to 7 as source node at a time and other remaining 14 nodes as receiving
nodes
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Results – Latency, group size 15
src n8 MVRing
250
src n8 Scribe
src n9 MVRing
latency (msec)
200
src n9 Scribe
150
src n10 MVRing
src n10 Scribe
100
src n11 MVRing
50
src n11 Scribe
src n12 MVRing
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14
receiving node sequence
src n12 Scribe
src n13 MVRing
src n13 Scribe
Latency in MVRing and Scribe based 15-member multicast group with one of
nodes 8 to 13 as source node at a time and other remaining 14 nodes as
receiving nodes
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Results – latency summary
MVRing
Scribe
120
100
80
60
40
20
0
average latency
(msec)
average latency
(msec)
MVRing
1
2
3
4
5
6
7
8
150
100
50
0
9
1
2
3
4
5
6
7
nodes
average latency
(msec)
average latency
(msec)
MVRing
200
150
100
50
0
3
5
7
9
11
9
10 11 12 13 14
Average group multicast latency in a
MVRing and Scribe based group of size n=15
Scribe
250
1
8
nodes
Average group multicast latency in a
MVRing and Scribe based group of size n=10
MVRing
Scribe
13
15
17
19
nodes
37 Average group multicast latency in a
MVRing and Scribe based group of size n=20
Scribe
1500
1000
500
0
1
3
5
7
9
11
13 15 17 19
21 23 25
nodes
Average group multicast latency in a
MVRing and Scribe based group of size n=25
Results - standard deviation of latency
60
30
MVRing
20
Scribe
10
std.deviation
std. deviation
40
0
50
40
MVRing
30
Scribe
20
10
0
1
2
3
4
5
6
7
8
9
1 2 3
4 5 6 7
nodes
nodes
80
70
60
50
40
30
20
10
0
MVRing
Scribe
Standard deviation of latency in a MVRing
and Scribe based group of size n=15
Std. Deviation
Standard deviation of latency in a MVRing
and Scribe based group of size n=10
std. deviation
8 9 10 11 12 13 14
350
300
250
200
150
100
MVRing
Scribe
50
0
1
3
5
7
9
11
13
15
17
19
nodes
Standard deviation of latency in a MVRing
38and Scribe based group of size n=20
1
3
5
7
9 11 13 15 17 19 21 23 25
nodes
Standard deviation of latency in a MVRing
and Scribe based group of size n=25
Host Nodes
Router Nodes
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Configuration
 2 Mbps Duplex Link
 Random link delay up to 450 ms
 Drop tail queue
 no. of CBR traffic sources and sinks
 Distance Vector unicast routing
protocol
Stub Domain
Transit Domain
T-S Internet Model
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Kruskal Algorithm for Minimum
spanning tree
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Greedy Algorithm for Optimal Ring
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MVRing on the top of optimal ring
Results – Latency,
using NS-2
 Group size 500, 150,50 (Appendix G)
 Source node 240th
 number of packets sent 10
Ring
MVRing
latency(msec)
6000
5000
4000
3000
2000
1000
0
1
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101
151
201
251
301
351
nodes
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MVRing and Optimal ring latency comparison
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Results - Latency,
latency (msec)
Mvring
using NS-2
Ring
MST
3000
2000
1000
0
for n=50
for n=150
for n=500
nodes
Latency comparison for ring, MVRing and MST (minimum spanning tree) for groups
size of 50, 150 and 500 nodes
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Results – Fault tolerance
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Node 1 is the source node and node 21 leave the group
unexpectedly in a group of size 25
packets received in recovered MVRing
packets received after tree recover
packets lost due to node failure
packets lost due to node failure
packets received before the effect of node failure
packets received before the effect of node failure
30
25
20
15
10
5
0
25
packet numbers
packet numbers
30
20
15
10
5
1
3
5
7
9 11 13 15 17 19 21 23 25
nodes numners
MVRing packets received/lost due
unexpected node failure in a group size of
25 nodes
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0
1
3
5
7
9
11
13
15
17
19
21
23
25
node numbers
Scribe packets received/lost due
unexpected node failure in a group size of
25 nodes
Results – Fault tolerance
Node 1 is the source node and node 11 leave the group
unexpectedly in a group of size 20
packet received after tree recover
packet received after MVRing recover
packet lost due to node failure
packets lost due to node failure
packets received before the effect of node failure
packets received before the effect of node failure
30
30
25
25
packet numbers
packet numbers
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20
15
10
5
20
15
10
5
0
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
node numbers
node numbers
MVRing packets received/lost due
unexpected node failure in a group size of
44 20 nodes
Scribe packets received/lost due
unexpected node failure in a group size of
20 nodes
Results – Node degree
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Interest based Group having size 15 is created and node
degree is noted down in MVRing and Scribe schemes
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node degree
12
10
8
MVRing
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Scribe
4
2
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15
nodes
Figure: Node degree profile in MVRing and Scribe based 15-member group for
same group Ids (“mytopic”).
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Results – Node degree
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Interest of the Group (i.e. groupId) is varied keeping the
group size identical (i.e. 30)
MVRing
Scribe with topic "hihi"
Scribe with topic "kk"
Scribe with topic "hi"
Scribe with topic "zoo"
Scribe with topic "lab"
30
node degree
25
20
15
10
5
0
-5
1
6
11
16
21
26
nodes
Figure: Node degree profile in MVRing and Scribe based group for
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group size 30.
Results – Joining traffic profile
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Two scenarios
1.
2.
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One node is made to join to already
existing group (of sizes 4, 9, 14 and 19)
and joining traffic is measured in case of
MVRing and Scribe
Numbers of users are made to join the
group having only a group creator as
existing user. Joining traffic profile is
measured for different groups of sizes 5,
10, 15 and 20
More results on Appendix J
Per node joining traffic
(K Bytes)
Results – Joining traffic profile
MVRing
Scribe
10
15
100
80
60
40
20
0
5
20
Group size
Per node joining traffic profile in MVRing and Scribe based group of different sizes.
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Results – Joining traffic profile
Avg. packets/sec 4.06
Avg. packet size 672 bytes
Packets received 1474
MVRing joining traffic profile in a group of
size 20 when 19 members join in a group
created by a creator
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Avg. packets/sec 1.66
Avg. packet size 751 bytes
Packets received 605
Scribe joining traffic profile in a group of size
20 when 19 members join in a group created
by a creator
Results – Multicast traffic profile
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Two scenarios for groups of size 5, 10, 15 and
20
1.
2.
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Firstly, multicast traffic on a node is measured
that sends the data to the multicast group
Secondly, any one source node is made to
multicast the data in to the group and traffic
profile at non-source nodes is observed and
measured
More results on Appendix K
Results – Multicast traffic profile
Multicast traffic on a source node is measured that sends
10 packets of data to a multicast group
Bytes Received
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MVRing
Scribe
10
15
600000
400000
200000
0
5
20
Group size
Per node multicast data traffic profile in MVRing and Scribe based group of
different sizes.
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MVRing data traffic in a node when a
node multicasts 10 packets to a group
of size 20
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Avg. packets/sec 7.64
Avg. packet size 624 bytes
Packets received 844
Packets
Avg. packets/sec 7.73
Avg. packet size 648 bytes
Packets received 853
Packets
Results – Multicast traffic profile
Scribe data traffic in a node when a
node multicasts 10 packets to a group
of size 20
Results – Multicast traffic profile
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Multicast traffic on a receiver node is measured when a
any other source node sends 10 packets of data to a
multicast group
Bytes received
MVRing
Scribe
600000
400000
200000
0
5
10
15
20
Group Size
Multicast data traffic profile received in MVRing and Scribe based groups of different
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sizes.
Results – Multicast traffic profile
Packets
MVRing data traffic in a node when a
node received 10 packets multicasted by
any other member in a group of size 20
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Packets
Avg. packets/sec 8.69
Avg. packet size 604 bytes
Packets 942
Avg. packets/sec 7.76
Avg. packet size 645 bytes
Packets 844
Scribe data traffic in a node when a node
received 10 packets multicasted by any
other member in a group of size 20
Results - Node heterogeneity
Allowing the node to mention whether it has sufficient
resources or not
Under the identical scenario (same groupId, same
number of users in a group, same amount of data
multicasting in a group, same source node in a group,
etc), traffic overhead on a node is measured in two
modes i.e. firstly node is considered to have
sufficient resources and secondly node is considered
as weak node and has insufficient resources.
Detail results on Appendix L
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Results - Node heterogeneity
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Multicast traffic on a node (considering weak and
powerful) with different sizes of MVRing and Scribe
based groups
Bytes received
Powerful node
Weak node
500000
400000
300000
200000
100000
0
5
15
25
Group Size
Comparison of node traffic when it is assumed to have sufficient resources and
insufficient resources; source node is multicasting 10 packets of data to a MVRing
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based groups
Node traffic when it is assumed to have
insufficient resources; source node is
multicasting 10 packets of data to a
MVRing based group of size 5
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Avg. packets/sec 3.127
Avg. packet size 681 bytes
Packets received 518
Node traffic when it is assumed to have
sufficient resources; source node is
multicasting 10 packets of data to a
MVRing based group of size 5
Packets
Avg. packets/sec 1.97
Avg. packet size 704 bytes
Packets received 326
Packets
Results - Node heterogeneity
Result - Implementations
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Group Merging
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Group Splitting
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Two groups at a time
Any member of group can initiate to split
Group Maintenance
Expected/unexpected node departure from
group
 RP shifting
 Merging/Splitting and etc
More results in Appendix M, example of group
merging implementation & validation process is
below.
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RP, new leader, updated neighbors, number of users
in a group etc are checked and verified
Conclusion
 E-Learning in P2P environment
 New MV Ring based Approach for ALM
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More fault tolerant
Better node degree distribution
Comparable latency
Comparable multicast traffic profile with high
joining traffic
 For synchronous, more interactive learning,
efficient resource utilization than traditional eLearning
 Strong Alternative to traditional class room
based learning…that current C/S based eLearning lacking to be.
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Conclusion
Limitations/Extension
 Consideration of Security and Privacy as major
issues
 Reducing the joining traffic cost
Future work : E-Learning GRID
 Modified MVRing based protocol to grid
environment will provide an extremely powerful
infrastructure allowing users to collaborate in
various learning contexts and to share learning
materials, learning processes, learning systems,
and experiences
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Papers/Presentations
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Published/Accepted/Submitted
 South Asian Network Operators Group –SANOG 7
(Accepted for workshop Presentation), Mumbai, India
 Published: International Conference On Distance Education
– ICODE 2006 Conference, Mascot, Oman
 Published: Web Information Systems and Technologies –
WEBIST 2006 Conference, Setúbal, Portugal
 IEEE Conference on Networks (ICON -2006), Singapore
(Submitted)
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Thank You
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