DISTRIBUTED E-LEARNING SYSTEM USING P2P TECHNOLOGY

Shinichi Motomura, Ryosuke Nakatani, Takao Kawamura, Kazunori Sugahara

Tottori University

4–101, Koyama-Minami, Tottori 680–8552, JAPAN

Keywords:

P2P, e-Learning, Mobile Agent, Distributed hash table.

Abstract:

In this paper, we present a novel framework for asynchronous Web-based training. The proposed system has

two distinguishing features. Firstly, it is based on P2P architecture for scalability and robustness. Secondly,

all contents in the system are not only data but also agents so that they can mark user’s answers, can tell the

correct answers, and can show some extra information without human instruction. We also present a prototype

implementation of the proposed system on Maglog. Maglog is a Prolog-based framework for building mobile

multi-agent systems we have developed. Our system has methods for communications between learners and

for recordings of their score without server computers. The user interface program of the proposed system is

built on Squeak. Performance simulations demonstrate the effectiveness of the proposed system.

1 INTRODUCTION

The term e-learning covers a wide set of applications

and processes, such as Web-based training (hereafter

we abbreviate as WBT), computer-based training, vir-

tual classrooms, and digital collaboration. We are

concerned with asynchronous WBT that allows the

learner to complete the WBT on his own time and

schedule, without live interaction with the instructor.

Although a large number of studies have been made

on asynchronous WBT(Helic et al., 2003; Homma

and Aoki, 2003), all of them are based on the

client/server model. The client/server systems gen-

erally lack scalability and robustness. In the recent

years, P2P research has grown exponentially. In this

paper, we present a novel system for asynchronous

WBT.

We had proposed the system(Kawamura and Suga-

hara, 2005) has two distinguishing features. Firstly, it

was based on P2P architecture and every user’s com-

puter played the role of a client and a server. Namely,

while a user used the proposed e-Learning system,

his/her computer (hereafter we refer to such a com-

puter as a node) was a part of the system. It re-

ceived some number of contents from another node

when it joined the system and had responsibility to

send appropriate contents to requesting nodes. Sec-

ondly, each content in the system was not only data

but also an agent so that it could mark user’s answers,

tell the correct answers, and show some extra infor-

mation without human instruction.

In this paper, methods for communications be-

tween learners and for recordings of their score in the

proposed e-learning system are proposed. The meth-

ods are implemented in our proposed e-Learning sys-

tem. Many of e-learning systems including our pro-

posed e-Learning system are designed for learner’s

self-educations. In such systems, learners want to

ask for someone’s advices when they cannot solve

their exercises. To satisfy such demand many of ordi-

nary WBT systems have BBS (Bulletin Board Sys-

tem) functions. However BBS functions are effec-

tive in concentrated WBT systems, they require WBT

servers and as a result they are not well suited for our

proposed e-learning system. The method proposed in

this paper is for completely distributed systems and

does not require server computers. When one learner

needs someone’s advices, the system tries to ﬁnd good

scored person of the exercises. When time of the good

scored person permits, the learner can start communi-

cation with him/her and can get some good advices.

The method for recording learners scores in our pro-

posed e-learning system is also proposed in this pa-

per. In the ordinal system, this function is also imple-

mented with server computers. We tried to realize the

function by using P2P architectures and mobile agents

250

Motomura S., Nakatani R., Kawamura T. and Sugahara K. (2006).

DISTRIBUTED E-LEARNING SYSTEM USING P2P TECHNOLOGY.

In Proceedings of WEBIST 2006 - Second International Conference on Web Information Systems and Technologies - Internet Technology / Web

Interface and Applications, pages 250-255

DOI: 10.5220/0001251202500255

 SciTePress

technologies in order not to reduce the advantages of

our proposed e-learning system.

In this paper,we present a prototype of the proposed

system on Maglog (Motomura et al., 2006) that is

a Prolog-based framework for building mobile agent

systems we have developed.

2 PROPOSED SYSTEM

2.1 Overview

As mentioned in the previous section, we focus on

asynchronous WBT, that is to say, a user can connect

to the proposed e-Learning system anytime and any-

where he/she wants. Once connection is established,

the user can obtain exercises one after another through

specifying categories of the required exercises. User’s

answers for each exercise are marked as correct or

incorrect right away. Extra information may be pro-

vided for each answer, which can be viewed when the

correct answer is shown.

While a user uses the proposed e-Learning system,

his/her computer is a part of the system. Namely, it

receives some number of categories and exercises in

them from another node when it joins the system and

has responsibility to send appropriate exercises to re-

questing nodes.

The important point to note is that the categories a

node has are independent of the categories in which

the node’s user are interested as shown in Fig.1. Fig-

ure 1 illustrates that user A’s request is forwarded at

ﬁrst to the neighbor node, next forwarded to the node

which has the requested category.

Network

Physics

I want to try

an exercise

of history!

User A

English History

User B

User C

Searching Message

Migration of Exercise Agent

Node Node

Node

Figure 1: Proposed e-Learning system.

2.2 P2P Aspect

When the proposed system begins, one initial node

has all categories in the system. When another node

joins the system, it is received some number of cate-

gories from the initial node. The categories are dis-

tributed among all nodes in the system according as

nodes join the system or leave the system.

We would like to emphasize that in existing P2P-

based ﬁle sharing systems such as Napster(Napster,

1999) and Gnutella(Gnutella, 2000) each shared ﬁle

is owned by a particular node. Accordingly, ﬁles

are originally distributed among all nodes. On the

other hand, the categories in the proposed system

are originally concentrated. Consequently, when a

new node joins the system, not only location infor-

mation of a category but the category itself must be

handed to the new node. Considering that, the P2P

network of the proposed system can be constructed as

a CAN(Ratnasamy et al., 2001).

A CAN has a virtual coordinate space that is used

to store (key, value) pairs. To store a pair (K

key K

is deterministically mapped onto a point P in

the coordinate space using a uniform hash function.

The corresponding (key,value) pair is then stored at

the node that owns the zone within which the point

P lies. In the proposed system, we let each category

be a key and let a set of exercises belonging to the

category be the corresponding value.

Our P2P network is constructed with 2-

dimensional coordinate space [0,1] × [0,1] to

store exercise categories, as shown in Fig.2. The

ﬁgure shows the situation that Node C is joining

the system where Node A and Node B have already

joined. Before Node C joins, Node A and Node B

shared the whole coordinate space half and half. At

that moment, Node A managed “Math/Geometry”

category and Node B managed “Grammar” and

“History” categories, respectively. When Node C

joins the system, it is mapped on a certain coordinate

space according to a random number and takes on

corresponding categories from another node. For

example, in the case of Fig.2, Node C takes on the

“History” category from Node B and exercises move

to Node C.

2.3 Mobile Agent Aspect

Generally, in addition to service to show an exercise, a

WBT server provides services to mark the user’s an-

swers, tell the correct answers, and show some ex-

tra information about the exercise. Therefore, for the

proposed system which can be considered a distrib-

uted WBT system, it is not enough that only exercises

are distributed among all nodes. Functions to provide

the above services also must be distributed among all

nodes. We adopt mobile agent technology to achieve

this goal. Namely, an exercise is not only data but

also an agent so that it can mark user’s answers, tell

the correct answers, and show some extra information

about the exercise.

DISTRIBUTED E-LEARNING SYSTEM USING P2P TECHNOLOGY

251

(0,0)

(1,1)

Math/Geometry

Grammar

History

Node B

Node A

Node C

Grammar

Math/Geometry

History

Exercise1

Exercise2

Category

Exercises to be contained

in a category

Figure 2: Peer to peer network.

In addition, mobile agent technology is applied to

realize the migration of categories, that is, each cate-

gory is also an agent in the proposed system.

2.4 Interactive Communication

Function

A questioner is a learner who wants to ask for some-

one’s advice. An answerer is a learner who has a

good score and gives good advice. When a questioner

wants to get some advice from an answerer interac-

tively using online chat, however, a questioner cannot

know what kind of learner uses the system. Therefore

the system provides the function to ﬁnd an answerer.

In the system, answerers are deﬁned that they already

solved the request’s exercise and its score was higher

than 80. The algorithm to ﬁnd an answerer is shown

in Fig. 3. The queue Q contains addresses of nodes

to inquire and the set S contains addresses of inquired

node. The algorithm is explained using Fig. 4. It is

assumed that the node of a questioner is A. Adjacent

nodes of A are B, D, E, and G. First, the address of A

is appended to S, and the addresses of B, D, E, and G

are appended to Q.

S = {A}

Q =[B,D,E,G]

Next, B which is the top of Q is retrieved and the

learner on B is inquired whether he is an answerer.

If he is not an answerer, adjacent nodes of B will be

appended to Q, but A which is already contained in Q

is not appended. And only C will be appended to Q

because E already is contained in Q. After inquiring,

B will be appended to S.

S = {A, B}

Q =[D, E , G,C ]

Next, D which is the top of Q is retrieved and the

learner on D is inquired whether he is an answerer. If

he is not an answerer, F and I will be appended to Q

and D will be appended to S.

S = {A, B, D}

Q =[E,G, C,F, I]

The above-mentioned operations are repeated until an

answerer is found, or Q becomes empty.

Figure 3: The algorithm to ﬁnd an answerer.

3 DESIGN AND

IMPLEMENTATION

We have implemented a prototype of the proposed

system on Maglog that is a Prolog-based framework

for building mobile multi-agent systems we have de-

veloped.

Node Agent There is one node agent on each node.

It manages the zone information of a CAN and for-

wards messages to the category agents in the node.

Category Agent Each category agent stands for a

unit of a particular subject. It manages exercise

WEBIST 2006 - INTERNET TECHNOLOGY

252

Figure 4: The example of arrangement of nodes.

agents in itself and sends them to the requesting

node.

Exercise Agent Each exercise agent has a question

and functions to mark user’s answers, tell the cor-

rect answers, and show some extra information

about the exercise. These data are formatted in

HTML.

Messenger Agent A messenger agent is created

when a questioner want to ﬁnd an answerer. It goes

round nodes to ﬁnd the answerer.

Log Agent Each log agent contains learners’ scores

of the corresponding exercises. The number of

them is identical of the number of learners. Teach-

ers can get score of any learner by communicating

with the corresponding log agent.

Interface Agent There is one interface agent on each

node. It is an interface between the user interface

program and other agents.

Agents communicate with other agents through

‘ﬁeld’s provided by Maglog framework. A ﬁeld is

kind of a preemptive queue. Roughly speaking, the

above-mentioned six kinds of agents execute a mes-

sage dispatch loop. Each message to an agent is

queued into the ﬁeld owned by the agent. The user in-

terface program also communicates with the interface

agent through a ﬁeld via XML-RPC(Winer, 1998).

As mentioned above, the user interface program of

the proposed system has been developed through ex-

tending Scamper which is a simple web browser runs

in Squeak(Ingalls et al., 1997).

Figures 5, 6, and 7 are screen-shots of the user

interface program. By clicking the left button of a

mouse on the category, a user can select it. After se-

lection of the category, a user can obtain an exercise

belonging to the category by clicking the left button

of a mouse on one of buttons in the button pane. Af-

ter a while an appropriate exercise agent comes from

some node and the user can try the question. The

user can require to mark his/her answer anytime by

clicking the submit button. Figure 5 shows an exam-

ple result of marking. Figure 6 shows the correct an-

swers and extra information about the exercise that

are shown by clicking the answer button. Figure 7

shows a questioner and an answerer communicate us-

ing online chat.

Figure 5: User’s answers are marked as correct or incorrect

by clicking the submit button.

Figure 6: Correct answers and extra information are shown

by clicking the answer button on the screen shown as Figure

4 PERFORMANCE SIMULATION

This section presents performance simulations ob-

tained from a prototype implementation of the pro-

posed system described in the previous section.

The experimental environment consists of 8 PCs

with Intel Pentium4 2.4GHz processor and 512MB

of RAM, and all the PCs are running on GNU/Linux

(kernel version is 2.2.26) operating system.

We measured the searching latency in the exper-

imental environment under the conditions shown in

DISTRIBUTED E-LEARNING SYSTEM USING P2P TECHNOLOGY

253

Figure 7: A questioner and an answerer communicate using

online chat.

Table 1. All nodes send searching requests at the

same time and exercises to be searched are selected

randomly. We compared distributed and concentrated

systems where these terms are deﬁned as follows:

Distributed System Each node has one category.

Concentrated System One node has all categories

and the rest nodes have no category.

It must be noted that the distributed system represents

the proposed system in which all categories have ideal

distribution. The concentrated system is equivalent to

an ordinary WBT system.

Table 1: Experimental Conditions.

Number of Nodes 8

Number of Categories

Number of Exercises/Category

Searching Frequency [times/sec]

Simulations are carried out with the time interval

of 600 seconds. Each Simulation is repeated 10 times

and the average of those is reported in Figure 8. Nat-

urally, the higher searching frequency is, the larger

searching latency is. Figure 8 shows that search-

ing latency grows rapid in the concentrated system,

while it grows slowly in the distributed system. In

other words, the result suggests that the proposed e-

Learning system has higher scalability than ordinary

concentrated WBT systems have.

5 RELATED WORKS

A great deal of effort has been made on agent-based

systems(Wong et al., 1997; Lange and Oshima, 1998;

Tarau, 1999; Satoh, 2000). However, these tech-

nologies provide support for agent collaboration and

communication but lack support for P2P technology.

Therefore, there are few agent-based P2P applica-

tions. PeerDB(Ng et al., 2003) is one of them, how-

5000

10000

15000

20000

25000

0 0.1 0.2 0.3 0.4 0.5 0.6

Average Searching Latency [msec]

Searching Frequency [times/sec]

Concentrated System

Distributed System

Figure 8: Comparison of concentrated and distributed sys-

tems in searching latency.

ever agent technology is only used to assist query

processing while in the proposed e-Learning system

it is used not only for interactiveness but also for mi-

gration of the functionality of the system.

Edutella is P2P network for exchanging infor-

mation about learning objects(Nejdl et al., 2002).

Edutella is based on RDF(Resource Description

Framework), which is a framework for representing

information in the Web. Consequently, Edutella does

not intend to receive user’s response. In contrast, that

is one of main goal of the proposed system and it is

achieved through agent technology.

6 CONCLUSION

Since existing asynchronous WBT systems are based

on the client/server model, they have problems of

scalability and robustness. The proposed e-Learning

system solves these problems in decentralized manner

through both P2P technology and mobile agent tech-

nology. The user interface program of the proposed

system is built on Squeak so that it obtains much

interactiveness and ﬂexibility. Performance simula-

tions suggest that the proposed e-Learning system has

higher scalability than ordinary concentrated WBT

systems have. More work needs to be done in the

evaluation of the robustness of the proposed system.

For example, whole services will be stopped if any

one computer in the system is crushed, because there

is no backup mechanism in our proposed e-Learning

system. At that time, exercise agents located in the

crushed computer can not be restored. Considering

these points, the backup mechanism, especially for

the distributed systems, is considered as future prob-

lems.

WEBIST 2006 - INTERNET TECHNOLOGY

254

REFERENCES

Gnutella (2000). http://welcome.to/gnutella/.

Helic, D., Krottmaier, H., Maurer, H., and Scerbakov, N.

(2003). Implementing project-based learning in wbt

systems. In World Conference on E-Learning in Cor-

porate, Government, Healthcare, and Higher Educa-

tion, pages 2189–2196.

Homma, H. and Aoki, Y. (2003). Creation of wbt server

on digital signal processing. In Proceedings of 4th

International Conference on Information Technology

Based Higher Education and Training. Marrakech,

Morocco.

Ingalls, D., Kaehler, T., Maloney, J., Wallace, S., and Kay,

A. (1997). Back to the future: The story of squeak, a

practical smalltalk written in itself. In Proceedings of

ACM Conference on Object-Oriented Programming,

Systems, Languages, and Applications, pages 318–

326.

Kawamura, T. and Sugahara, K. (2005). A mobile

agent-based p2p e-learning system. IPSJ Journal,

46(1):222–225.

Lange, D. B. and Oshima, M. (1998). Programming and

Deploying Java Mobile Agents with Aglets. Addison-

Wesley.

Motomura, S., Kawamura, T., and Sugahara, K. (2006).

Logic-based mobile agent framework with concept of

ﬁeld. IPSJ Journal, 47(4). will be published.

Napster (1999). http://www.napster.com/.

Nejdl, W., Wolf, B., Qu, C., Decker, S., Sintek, M., Naeve,

A., Nilsson, M., Palm

er, M., and Risch, T. (2002).

Edutella: A p2p networking infrastructure based on

rdf. In Proceedings of the Eleventh International Con-

ference on World Wide Web, pages 604–615. ACM

Press.

Ng, W. S., Ooi, B. C., Tan, K.-L., and Zhou, A. (2003).

Peerdb: A p2p-based system for distributed data shar-

ing. In Dayal, U., Ramamritham, K., and Vijayara-

man, T. M., editors, Proceedings of the 19th Interna-

tional Conference on Data Engineering, pages 633–

644. IEEE Computer Society.

Ratnasamy, S., Francis, P., Handley, M., Karp, R., and

Shenker, S. (2001). A scalable content-addressable

network. In Proceedings of the 2001 conference on

Applications, technologies, architectures, and proto-

cols for computer communications, pages 161–172.

ACM Press.

Satoh, I. (2000). Mobilespaces: A framework for building

adaptive distributed applications using a hierarchical

mobile agent system. In Proceedings of IEEE Interna-

tional Conference on Distributed Computing Systems,

pages 161–168. IEEE Press.

Tarau, P. (1999). Inference and computation mobility with

jinni. In Apt, K., Marek, V., and Truszczynski, M.,

editors, The Logic Programming Paradigm: a 25 Year

Perspective, pages 33–48. Springer.

Winer, D. (1998). Xml-rpc speciﬁcation.

http://xmlrcp.com/spec.

Wong, D., Paciorek, N., Walsh, T., and Dicelie, J. (1997).

Concordia: An infrastructure for collaborating mo-

bile agents. In Proceedings of the First International

Workshop on Mobile Agents, volume 1219, pages 86–

97. Springer-Verlag.

DISTRIBUTED E-LEARNING SYSTEM USING P2P TECHNOLOGY

255