The document proposes a scalable network support system for 3D virtual shopping malls. It focuses on scalability and universal accessibility. To improve scalability, it uses an inter-region interaction scheme and user interest group filtering to reduce network load. The client runs in a web browser using Java, VRML and ActiveX, allowing ubiquitous access via the internet.

1. Scalable Network Support for 3D Virtual
Shopping Mall
Seunghyun Han(1), Mingyu Lim(1), Dongman Lee(1), Hea Dong Kim(2), Bon Ki Koo(2),
Sung Ye Kim(2), and Byoung Tae Choi(2)
(1)
Dept. of Engineering, ICU, 58-4, Hwaam-Dong, Yuseong-Gu, Daejeon, 305-732, Korea
(2)
Software Laboratory Virtual Reality Division, ETRI,161 Gajeong-Dong, Yuseong-Gu,
Daejeon, 305-350, Korea
{dennis, cats, dlee}@icu.ac.kr, {hdkim, bkkoo, inside, btchoi}@etri.re.kr
Abstract
As the Internet is rapidly deployed and computational power increases, Web-based electronic commerce
becomes popular. A typical presentation of the static 2D text and image information does not attract users as
much as in a real life one because it gives users a very limited opportunity to manipulate or observe products. In
this paper, we propose a scalable network support for 3D virtual shopping malls which mainly focuses on
scalability and accessibility. A large numbers of users and objects likely impose a heavy burden especially on the
network and computational resources. To improve scalability, we use an inter-region interaction scheme and user
interest group based filtering which exploits application semantics. For ubiquity of access in the Internet, clients
of the proposed system run on a Web browser using Java, VRML, and ActiveX control technology.
1. Introduction
As the Internet is rapidly deployed and computational power increases, electronic commerce
(e-commerce) using the Web becomes popular. A typical presentation of the information is
done using static 2D texts and images. However, the 2D-based presentation does not attract
users as much as in a real life one because it gives users a very limited opportunity to
manipulate or browse products. To allow e-commerce users to experience as close as possible
to real life shopping, a 3D virtual shopping mall is introduced which allows users to interact
with each other and manipuate objects in a cyber space. One of key aspects to consider for
designing a 3D virtual shopping mall system is scalability for interactive performance
because there exist a large numbers of users and objects and they likely impose a heavy
burden on the network and computational resources especially when the users are crowded in
a small area. Another aspect is universal accessibility which enables users to access a
shopping mall anywhere without any preparatory job, such as downloading and installation of
extra dedicated softwares, as long as the client is connected to the Internet.
There have been several approaches for a 3D virtual shopping mall. Among them are
VRCommerce [13] and @mart [1]. VRCommerce is based on the Web and VRML [11]. It
adopts ‘room’, ‘door’ and ‘hallways’ concepts which exploit shopping malls in a real world.
When a user approaches to a door, the door automatically senses the user and downloads
world data of the room. Users can interact and manipulate objects in the room. This approach
reduces the number of events by limiting a field of views of users to a room. It, however, is
not scalable when many users are crowded in a specific room or place because every event
generated by a user is propagated to all the nearby users even when they are not interested in
it. @mart in Active Worlds exploits progressive loading based on spatial constraint of a user
to increase scalability with a dedicated browser. It exploits a field of view of users to filter out
unrelevent events. A user just receives the events generated in its field of view, so called aura
[4], and other events generated by other users who are not within its aura are filtered out to
reduce communication overheads of users. This approach, however, does not provide
scalability when many users are crowded in a small space because a user should receive all

2. events generated by others nearby even though he is not interested in them. These impose
communications overheads on the users.
To overcome the limitation of existing systems, we propose a scalable 3D virtual shopping
mall system. The proposed system is based on ATLAS [7] which is a scalable network
framework to support NVEs. To improve scalability, we supports two schemes: a inter-region
interaction scheme [8] and user interest group based filtering [6]. In the former, a region
manager selects only a subset of users from the neighboring regions whose members have
high possibility of interaction with users in the current region. This enables users in the region
to receive update messages from only the users whom they are interested in the neighboring
regions. The user interest group based filtering extends the filtering even further. It allows
users with the same interest to dynamically form a group and exchange data with high fidelity
among them. However, data is transmitted either sporadically or little to other users. It could
filter out irrelevant data to be transmitted. For universal access, our client supports VRML
and Java that allow users to easily access a virtual shopping mall anywhere using a standard
Web browser, not a dedicated browser.
This paper is organized as follows. Section 2 discusses the existing systems. In section 3,
we describe design considerations to build a scalable 3D virtual shopping mall system and
then the design details of the proposed system. Section 4 presents the implementation
details of the proposed system. Finally, conclusion and future work follow in section 5.
2. Related Works
In this section, we describe the existing 3D virtual shopping mall systems for providing
users with interactive environments for e-commerce.
2.1 VRCommerce
VRCommerce [13] provides tools to design 3D VRML mall and virtual stores on a Web
browser. Users can interact with other users, and manipulate objects in a virtual shopping
mall. VRCommerce focuses on communication overheads incurred by large world data
distribution as well as integration of independently designed virtual shops to a large shopping
mall.
It uses ‘room’, ‘door’ and ‘hallways’ concepts which are the artifacts of real world shopping
malls. A shopping mall is composed of several separated rooms and hallways which link the
rooms. Using door, users can enter a room for shopping. When a user approaches to a door, it
loads a related room data by predicting the user may enter the room. This approach can
reduce large world data distribution overheads by dividing world into smaller regions and
distributing them if needed. It also reduces the number of events by limiting the boundary of
events delivery to a room. It, however, does not provide a scalable solution when many users
are crowded in a small region because users have to receive events that they are not interested
in.
2.2 Active World
Active World [1] provides toolkits to build interactive virtual community. @mart in Active
Worlds is an exemplary world which shows how the toolkit can be used to build a 3D virtual
shopping mall. Users can get 2D information on objects by clicking them, but Active World
does not allow users to manipulate them. For improving interactive performance, it leverages
a field of views of users to progressively load dynamic objects in a world, which reduces
initial world data distribution. It also uses proximity based filtering in which each user has its
own field of view, so called aura [4], and only receives events generated in its aura. Other
events generated by users who are not within its aura is filtered out and thus the number of
messages to maintain a consistent state with other users is reduced.
This approach is not scalable because when, many users are crowded in a small space, a user
should receive all the events generated by others nearby even though he is not interested in

3. them. Active World has limited accessibility since it requires its own world data format and a
dedicated viewer.
3. The Proposed System
In this section, we discuss key design issues that should be considered for a 3D virtual
shopping mall system and then we present the proposed system in detail.
3.1 Design Consideration
3.1.1 Scalability
Interactive performace is one of key factors in multi-user interactive systems such as a 3D
virtual shopping mall. To support acceptable performance as the number of users increases,
various relevant filtering schemes have been proposed [2, 4, 9]. The existing filtering
mechanisms are mostly based on location proximity or object types (classes or organizations)
by which participants are classified before starting a session. These approaches are not
scalable because a user should receive all the messages generated by others nearby even
though he is not interested in them. To overcome this, we first leverage application semantics
to filter out irrelevant events. User interest group based filtering and inter-region interaction
scheme adopts application semantics based on proximity of users as well as interest of users.
These schemes will be explained in detail in Section 3.5.
Secondly, we divide the roles of servers. A Web server is used for static scene data
distribution, and a server dedicated for shopping mall support, which will be detailed
explained in the next section, is for dynmaic data distribution and consistency management of
virtual worlds.
3.1.2 Accessibility
When users are asked to download and intall an extra software for accessing the service that
they want, it may eschew a user to access the service. To make a virtual shopping mall more
accessible, the mall should be accessed via a standard Web browser. We use Java, VRML,
and ActiveX to enable users to access a shopping mall with a standard Web browser. EAI is
used to mediate between network module and client viewer. This enables users to easily
access a 3D virtual shopping mall anywhere as long as a client machine is connected to the
Internet.
3.2 System Architecture
The proposed virtual shopping mall system is based on a client/server model. The system
is composed of three main components, a VS server, a Web server, and clients as shown in
Figure 1.
ATLAS VS Web Server
Roles: Product
Session Management
Consistency
Management World Rules
Concurrency Control World Data
ATLAS Client Interaction events
EA for consistent view
VRML Viewer Static data distribution
Web Web
Figure 1. Overall System Architecture

4. A VS server not only performs user management but also keeps up with the consistent
state of virtual world objects. We use ATLAS [7] as a network framework to build a
scalable VS server. ATLAS will be explained in detail in Section 4.2.
A Web server distributes virtual world data, avatar information, product information, and
rule description file which defines dynamic objects in a virtual world for concurrency
control among users. A client application consists of a client module which enables
communication to a VS server and a VRML viewer [10] which enables a user to navigate
in a virtual world.
The event exchange between ATLAS client and a viewer is performed via External
Authoring Interface (EAI) [3] and additional interfaces which RTV viewer [10] provides.
3.3 Session Management
A session implies an independent virtual shopping mall in which users can navigate,
interact with each other, and purchase products. To satisfy various requirements of users,
we support multiple sessions. A session is coupled with a Web server to distribute its own
shopping mall data. The states of users who participate in different sessions should not be
shared not only to protect privacy of the users, but also to prevent events propagation.
However, users in different sessions can interact with each other in the control of the
multi-session management. For dynamic management of sessions, it is required to provide
an interface for new session configuration. ATLAS VS server provides the dynamic
session configuration service, such as adding, deleting, and updating session information.
3.4 Concurrency Management
In a 3D virtual shopping mall system, users share the same view to interact with each
other. The shared information is often replicated at each user’s site to provide acceptable
interactive performance, especially where users are geographically distributed over large
networks like the Internet. Here concurrency management is required to resolve conflicts
of concurrent access to objects in a virtual world.
The proposed system takes optimistic concurrency control instead of strong one such as
locking since interactive performance is highly required and partial, temporal
inconsistency among users is acceptable in highly interactive applications such as a virtual
shopping mall. A user manipulates a target object immediately after he/she requests an
ownership instead of waiting for the ownership to arrive. If the ownership request is
denied, the target object is deactivated immediately. This causes temporary inconsistency
among users but it increases interactive performance.
3.5 Interest Management
Interest management mainly focuses on how to reduce the number of messages or events
without degrading interactive performance of users. It manages interests of users and
keeps track of intormation on the users who participate in a region and its neighboring
region. In this system, we use two interest management schemes, called inter-region
interaction [8] and user interest group based filtering [6].
In a real world shopping mall, not only can people perceive the objects near them
frequently than those far from them, but also focus more on objects of high interest than
those of low interest. The user interest group based filtering exploits this. With the
filtering, a user expresses its interests to objects in the shopping mall. Users who share the
same interest create an interest group and the users exchange update messages with high
fidelity, that is, every update message is sent to the others. Update messages are sent with
low fidelity data to the users who do not share the interest, that is, every update message is
not sent.
In order to solve deterioration of interactive performance due to region partition [9], we
apply the inter-region interaction management scheme based on sub regions to a virtual

5. shopping mall system. Based on distance and viewing direction, a user receives only
messages from only users in its neighboring regions whom it is interested in instead of all
users. The inter-region interaction scheme can reduce the number of messages, which then
support interactive performance in large-scale NVEs.
4. Implementation
The proposed system is based on ATLAS, which is our scalable network framework. It
consists of two parts: a server module and a client module. We first describe ATLAS and
then the implementation details of the proposed system.
4.1 Implementation Environment
The proposed system is written in Java language to enable users to access a virtual shopping
mall with Web browser. We use VRML [11], which is a graphic standard language, to build a
3D shopping mall scene without any extensions. A VRML viewer, which is also compatible
with X3D [14], is written in C++ and built as an ActiveX control to transparently work
with Internet Explorer. To mediate events, we use External Authoring Interface (EAI) [3]
and additioanl interfaces which the viewer provides.
4.2 ATLAS
ATLAS is a scalable network framework for networked virtual environments. It is an
ongoing project to support scalability in NVEs in terms of four scalability issues:
communication architecture, interest management, concurrency control, and data
distribution. ATLAS is written in Java and C++ and runs on Windows and Unix
compatible operating systems to incorporate with the various requirements of viewers or
applications. ATLAS does not define application specific policies or semantics but
provides mechanisms supported by various managers. ATLAS managers are divided into
two groups, high level managers group and low level managers group.
High level managers aim to provide NVE specific interfaces in the considerations of
scalability. It includes session manager, region manager, interest manager, concurrency
manager, and data distribution manager.
Session manager provides interfaces for membership management, and defines session-
specific rules applied to the session. Region managers play a major role to provide
consisent states among users who participate in a virtual whold. Region manager keeps
track of all states information including dynamic objects and users in the region or partial
information of neighboring regions. Interest manager provides several filtering
mechanisms including not only basic proximity based filterings but also user interest
group based filtering to filter out irrelevant events to users. Concurrency manager
maintains synchronization of dynamic objects in a virtual world. Data distribution
management aims to efficiently distribute virtual world data to clients to meet the
requirements of application demands.
Low level managers have duties for communications among ATLAS peers and servers. It
is mainly composed of communication manager and event manager. Event manager
mediates events delivery between communication manager and high level managers.
Primary duty of communication manager is channel management, which includes channel
creation, deletion and event transmissions.
Detailed description of ATLAS is found in [7].
4.3 Server Module
VS server consists of multi-session manager, session manager, region manager, interest
manager, concurrency manager, and data manager as high-level components and
communication manager and event manager as low-level components. High-level managers
inherit CAtlasHandler interface in order to process ATLAS events.

6. They must be registered to event manager with a target event types which they process.
Event manager has duties to pack byte array, which is received by communication manager,
to ATLAS events and route events to appropriate registered managers. Communication
manager holds the references of channel lists. It creates a new channel when a new user
joins a session or deletes the channel when the user leave the session.
Figure 2 shows the overall internal architecture of ATLAS VS server. Each component is
described in detail in the following sub-sections.
Figure 2. Internal Architecutre of ATLAS VS server
4.3.1 Session Manager
Session manager provides users with the interfaces for entering or leaving a virtual
shopping mall and membership management, and defines specific rules applied to the
session. Since we assume that a virtual shopping mall is divided into several logical
regions, the session manager holds the references to the region managers that manage
logical regions. It also supports multiple sessions. For dynamic management of sessions,
the multi-session manager holding reference list of session managers provides users with
the interfaces for initiation, termination, selection, join, leave, creation and deletion of
sessions.
To enter a virtual shopping mall, users query the multi-session manager about
information on available sessions, and select a session among several sessions maintained
by the ATLAS server.
Receiving a login request from a user, the session manager verifies the user with his/her
name and password. It then informs the user of regions in it, among which the user enters
a default region. After receiving information on other users and objects in the region, the
user can interact with them.
4.3.2 Consistency Manager
A virtual shopping mall is divided into several logical regions and we maintain consistent
states of regions. Region manager plays a major role of keeping consistent states or view
among users who participate in the shopping mall. For this, it keeps track of all states
information including dynamic objects and users in a region or partial information of
neighboring regions.
Figure 3. Event Flows in ATLAS Region Manager

7. Region manager, interest manager, data manager, and concurrency control manager are
incorportate with consistency manager to keep up with consistent states of a region. All
the events, which change virtual world states, are reflected to users who participate only in
the region after processing registered filterings or concurrency control mechanisms.
Detailed explanations about scalable filtering and concurrency control schemes are
described in following sections. Figure 3 illustrates a basic structure and event flows in
region manager.
4.3.3 Interest Manager
A primary role of interest manager is to filter out irrelevant events. We use interest
group based filtering and inter-region interaction scheme. With the user interest group
based filtering, a user expresses its interests to objects in the shopping mall. The user
sends all the interest events which are generated in a local host to the corresponding
region manager where the user participates. Region manager maintains group information
in User Table, and interest manager refers the table.
When an interest event, for instance UIG_USER_MOVED, comes in, interest manager
checks if the event results in creation, join, or leave of group based on interest of users in
the User Table and proximity. It determines group of users to distribute the event with
high-fidelity. It distributes the event to the group based on fidelity level, and checks the
level of low fidelity to determine event distribution to the other users who are not
members of the group. In some case, user may wish only to receive interaction data
occurred in its participating group. It could be also enabled by regulating the level of low
fidelity to zero. Figure 4 shows the users’ interactions under user interest group based
filtering.
Figure 4. Data Tramsmissions with UIGB filtering scheme
To characterize users’ interests in neighboring regions, a region is logically divided into
several sub-regions. Whenever ATLAS server receives position messages from users, it
updates them per user in the User Table. A region manager in the server then determines
each user’s interest in its neighboring regions, and then selectively forwards receiving
messages to users in the neighboring regions according to each user’s interest in them.
Figure 5 shows a part of data transmissions with inter-region interaction scheme in a
virtual shopping mall. RM1, RM2, RM3, and RM4 are region managers which manages
from region1 to region4 respectively. There are nine users represented as U1, U2, and so
on. When RM2 receives a position message from U4, it first forwards the message to other
users in region2. RM2 then determines interests of other users in the neighboring regions
of region2, region1 and region4. For region1, since U4 belongs to sub-region which is far
from region1, only U1 is interested in U4, not U2 and U3. For region4, all users, U8 and
U9 are interested in U4, because U4 belongs to sub-region which is adjacent to region4.
As a result, RM2 forwards U4’s update message to U1 in region1, and to U8 and U9 in
region4.

8. Figure 5. Data Tramsmissions with Inter-region Interaction Scheme
4.3.4 Concurrency Management
VRML adopts a single machine event model which implies that it does not provide any
synchronization or concurrency control mechanism for interactions among users in the
language. It supports EAI which enables a client system to extract states of virtual world
objects or generated event types. It, however, is not designed to consider distributed
environments. In the propsed system, we use EAI and additional interfaces to enable
interactions in distributed environments.
We define object and event handling rules to provide concurrency control for virtual
shopping mall objects. An event handling rule consists of a predefined action name, a
node name which is defined in VRML world file using DEF, and a field in the node that
can be modified when an event is generated. Each virtual shopping mall has its own
handling rule. We describe the handling rules in the world description file which is
distributed by Web server. This makes it possible to reuse existing VRML data without
modification. Shopping mall providers simply write a rule file instead of building an entire
scene. Figure 6 shows an event handling rule for concurrency control as an example.
Event Handling Rule
ActionName NodeName NodeTypeEventField FieldType [FieldValue] –[Action]
Action Names
Action Names Field – BUY, TRANS, ROTATE, TRANSROT, DECDB, etc.
Example
BUY Pooh TouchSensor isActive SFBool
Figure 6. Event Handling Rule for Concurrency Control
When a user joins a session, which is a virtual shopping mall, ATLAS client receives the
handling rules. The ATLAS client parses the rules and get objects and fields references
from VRML viewer. When a user triggers an event on the defined object, ATLAS client
sends ownership request event. Concurrency manager checks Object Table whether the
object is already occupied by other users. If other user does not have ownership,
concurrency manager sends ownership grant event to the client and object occupied event
to the other client in order to prevent other clients to manipulating the objects, otherwise,
it sends ownership denied event to the client. If a user finishes manipulating the object, it
sends ownership release event to concurrency manager. It sets the object state in the
Object Table as free, and sends ownership released event to the other clients to activate
the object.

9. 4.4 Client Module
Our virtual shopping mall client is run on Internet Explorer. It consists of VRML viewer
and ATLAS client. The VRML viewer, which is provided by Real Time Visual company
[10], not only supports VRML, but also supports X3D format. It is written in C++ and
built as ActiveX control to cope with Internet Explorer. It downloads VRML form of
shopping mall scene data from Web server, and generates scene gragph.
ATLAS client is written in Java and provided as Java Applet. It is composed of ATLAS
managers which are counterparts of ATLAS VS server. Not only does it provides
functionality for communication with ATLAS server, but also mediates event delivery to
the viewer. To mediate viewer with ATLAS client, we abstract EAI to higher level
interfaces because EAI is too low level interface to access VRML scene.
Those interfaces is primarily aimed to provide concurrent access for virtual world objects
and view synchronization among clients. It is called veneer layer interface in ATLAS
terms. The veneer layer converts ATLAS events to VRML events and vice versa.
ATLAS client provides a user with an interface for selecting an avatar type and a session
from a list of avatar types and sessions before joining a shopping mall. Once the user joins
a session, the viewer downloads the shopping mall scene data for a given session from the
corresponding Web server and initiates a navigation mini-map. Then, the user can
navigate the shopping mall, manipulate products, and interact with other users via a
chatting tool.
Figure 7 shows our prototype system where a user navigates in a virtual shopping mall.
Figure 7. Navigation in 3D Virtual Shopping Mall
5. Conclusions
In this paper, we propose a scalable 3D virtual shopping mall system which uses ATLAS
as a network framework and RTV VRML viewer. The proposed system is based on a
client/server communication architecture. The system is composed of three main
components, ATLAS server, Web servers, and clients. Web servers are used for static scene
data distribution, and ATLAS server is dedicated for dynmaic data distribution and
consistency management of virtual worlds. To build a scalable system, we exploit the inter-
region interaction and user interest group based filtering schemes which are provided by
the ATLAS network framework. The filtering schemes leverage application semantics
based on proximity of users to filter out irrelevant events without degrading interactive
performance of the users. The client of the proposed system is composed of a java version
of ATLAS client and a VRML viewer based on ActiveX control and runs on Internet
browser to provide universal accessibility. We use event handling rules which define
dynamic objects in a virtual shopping mall. It enables to reuse existing VRML worlds, and
enable users to manipulate virtual products in a shopping mall.
The current system provides multiple shopping malls with ATLAS server to adopt
various requirements of users. Even though scalable filtering schemes are used in the

10. proposed system, they do not overcome physical limitations, such as processing power
and the number of connections. We currently work on developing a scalable and adaptive
load balancing algorithm. In this, an overloaded server performs a load balancing locally
if most of its neighbor servers are not heavily loaded. Otherwise, it conducts load
balancing with more servers beyond its neighboring servers.
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