A mobile agent based approach for data management to support 3 d emergency preparedness scenario over ad hoc networks

International Journal For Research & Development in Technology
Volume: 2, Issue: 4, Oct -2014 ISSN (Online):- 2349-3585
14 Copyright 2014- IJRDT www.ijrdt.org
A Mobile Agent based Approach for Data
Management to Support 3D Emergency
Preparedness Scenario Over Ad-hoc Networks
Yassine Daadaa1,
Anis Zarrad 2
1
College of Computer science and information Systems
1
Al-Imam University, Riyadh, Saudi Arabia
2
Computer Science and Information Systems Department
2
Prince Sultan University, Riyadh, Saudi Arabia
Abstract— In present-day, technology is moving towards
Mobile Ad-hoc Networks (MANET), which creates
temporary network in environments that have no previous
network infrastructure. 3D Mobile Collaborative Virtual
Environments (3D MCVEs) to support emergency
preparedness scenario such as security sensitive operations
(firefighter, biological attacks ) and military training, have
made a considerable impact on both commercial and
academic fields over the last few years. In such systems,
users will share a 3D virtual environment through their
mobile devices in order to accomplish specific missions.
Effective data management is vital due to the massive
amount of data that need to be exchanged and displayed.
When the mobile devices resource capabilities are smaller
than the 3D virtual environment, we need an efficient
approach to maintain and manage active data in the device
memory. Traditional data management schemas become
inadequate when applied in mobile environment, because it
is important to guarantee the existence of the VE even when
many users leave suddenly the virtual environment with
critical data such as (3D geometric data, score credits etc...).
To meet this challenge, we propose a novel approach using
decision-based mobile agent that enables nodes to
autonomously make intelligent decision about data
computation and node state in the network. The resulting
approach limits the damage of application interest and offers
a realistic virtual environment. We also provide an example
of how this approach can be implemented in a real-life
emergency preparedness scenario.
Keywords— Mobile Collaborative Virtual Environment;
Emergency preparedness scenario, Ad-hoc network;
MANET; 3D world Data management.
I.INTRODUCTION
The frequent occurrence of disasters has raised people‟s
consciousness and increased their efforts to prevent, manage,
and resolve the resulting issues. Many disasters derived from
one cause or another has been witnessed. Therefore, it is
important to develop a 3D virtual environment for emergency
scenarios in order to apply a pre-rescue plan in graphical
environment before applied in real situation to avoid any
threats to human lives and properties. In 3D emergency
preparedness scenario applications over ad-hoc, users will
share a 3D virtual environment through their mobile devices in
an ad-hoc network (MANET) in order to accomplish specific
missions in disaster situation. The design of such application to
support emergency preparedness scenario like firefighter,
biological attack, earthquake and military training with an
independent network infrastructure, and which can run at
anytime, anywhere are challenged by the dynamicity of the
network configuration, and the amount of data that need to
proceeded online compared to the available physical memory
of a display client.
Novel technologies are being applied to handle various kinds
of applications. These include: Internet, wireless technology,
and, 3D acceleration cards. These emerging tools and
technologies can enhance communication capabilities, data
management, and experience in virtual environment running on
mobile devices such laptops and smart phones. For example
with J2ME [30], we can use modern mobile phones locally to
browse and play 3D games. However, 3D emergency
preparedness applications requires effective image rendering,
and richer contents, which is most likely, does not fit into
available client memory resource. Therefore, how to manage in
an efficient manner the amount of data for large virtual scene
while maintaining interactive visualization with 3D world
becomes an emerging issue that needs to be addressed.
In MCVE each user is represented by a graphical embodiment
called an avatar. The avatar [7] concept enables users to
progress in the virtual environment (VE) and see other users‟
actions. We divide the VE into zones in order to ensure that the
amount of data that the client handles is small enough to fit into
the memory of the mobile device [7]. Activities in zones are
grouped into sessions. A zone owner node is assigned
dynamically to act as an authoritative server on a specific zone.
Any user can participate in any number of sessions. Therefore,
there is a need for a session manager mechanism to control
session access and guarantee the existence of the VE even

Paper Title:- A Mobile Agent based Approach for Data Management to Support 3D
Emergency Preparedness scenario Over Ad-hoc Network (Vol.2, Issue-4) ISSN(O):- 2349-3585
when many users leave the environment. The system initially
assigns a unique ID to each session and zone. The
unpredictability of MANETs [6] can cause sudden node
crashes, which has a devastated effect on the performance of
MCVE system as a whole. Nodes have to re-establish
connections with neighboring peers, and the virtual
environment data must be relocated according to the new
physical position of the user in the VE. Often, nodes are able to
leave the network over time; however, it is difficult for the
virtual environment to remain persistent if nodes disappear,
taking with them data that is necessary for the proper
functioning of the virtual environment.
The importance of developing MCVE to support emergency
preparedness scenario can be observed by the necessity to run
some scenarios where communication cannot deployed quickly
or simply too expensive. Also sometime there is a need to
apply some emergency scenario in computer graphics
environments before applying them in real life. Accidents
involving real missiles and lethal weapons can very often be
deadly, and thus have devastating impact, both economically,
and humanity. A representative example to better understand
the impetus of such system is Al-Hajj Scenario: Every year,
Saudi Arabia receives about three million people perform Hajj-
e-Baitullah. It is important to have a believable virtual
environment to prepare a backup rescue scenario with an
acceptable response time whenever there is a need. Usually in a
crowded area where pedestrian and traffic are involved you
can't safeguard everybody and everything, trampled accident
may happen. Thus, having such system with a 3D
representation of this situation as input is very helpful for
police, military and medical personals in order to let them react
properly with an appropriate effort management when they
arrive to the accident site. In addition the system can prevent
accidents by applying some worst scenarios of a specific
situation in computer graphics and redraw an efficient rescue
plan. Figure 1 shows an Al-hajj emergency preparedness
scenario.
Figure 1: AL-Hajj Scenario
The security department in Saudi Arabia receives an event
about an accident in Baitullah Mecca. A spontaneous 3D
representation of the situation is loaded in all mobile devices of
different organization (police, military, medical staff etc...)
while preparing to leave. An ad-hoc network is created to
allow efficient communication between them and try some
scenarios in computer graphics before heading to the event
destination. Such scenarios are very helpful for the different
team organization, since it provides a real overview of the
situation awaiting them.
Data management in 3D emergency preparedness scenario is
referred as providing a continue service and the world remain
persistent if user disappear, while in possession of critical data
that is necessary for the proper functioning of the 3D virtual
environment, and thus can cause system perturbation. The data
provider, needs to guarantee persistent world, be able to
execute dense data between avatars [7] participating in the
environment, and the results must be free-perturbation system
in order to give the application more usability and availability
regardless of whether an individual player is logged off. The
deployment of data management mechanism is not evident in a
mobile virtual environment because link failures are less likely
in a wired network than in an ad-hoc environment, and
resource constraints. With incompetent mechanism, the user
starts losing the feeling of immersion, decreasing his/her rate of
interaction, and eventually causing him/her to lose interest to
the application.
In this paper, we describe scalable reasoning mechanism for
data management in 3D mobile emergency scenario based on
mobile agent. Instead of periodic data update message
exchange between users, which is computationally expensive
and harm the network throughput, we use multiple mobile
agents to reason about user interest in the VE and predict
user‟s behavior intention. The main contribution of this
research is the creation of mobile multi-agents system to gather
critical data acquired by avatars during the play and supply
neighbor nodes with appropriate data for future use, when
former node leave the network suddenly.
In general agents can be defined as computer systems situated
in some environment, which are capable of autonomous action
in this environment in order to meet their design objectives.
Three main characteristics are crucial for agents. On the one
hand they are reactive, which means the agents should respond
in a timely fashion to changes they perceive in their
environment. Also, agents are proactive in the sense that they
take the initiative to meet their design objectives, and they
exhibit goal-directed behavior. Finally, they have social
abilities to interact with other agents (and humans) to satisfy
their design objectives [32].

The proposed solution adapts an agent to represent a node
and have the ability of to go through the network while they
take decision on behalf of the node to push data to a stable
neighbor node. The selection of the stable node is based on the
following criteria:
 The node degree d of a node v is given by the number of its
neighbors N (v)
 Stability Period: is the time interval from the start of
network operation until the death of the first network
node. We also refer to this period as “stable region.”
In this approach agents must determine the appropriate time to
save permanent data that is essential for the functioning of the
3D world in another location and make it available for all
participants in the VE. We define persistent data, which is
relevant to all users, and should remain in the system even
when the user leaves the network or logs off from the session.
Nodes holding such data are called coordinator nodes. Example
of permanent data includes player modification reported to
shared objects, or player objects created during run time, such
as a home, car parked in the street etc…
Current research has been focused on data management for
virtual environment in wired network. In mobile networks, data
management is computationally very expensive because of
strict and delicate application domain, frequent node sudden
disconnection node, the particularity of wireless links, and the
limited resource constraints of mobile devices pose great
challenges for any data management solutions developed in
mobile environments foe emergency preparedness scenario.
As the user interest may vary over the time depending on its
avatars' position in the virtual environment. Thus, it is not
merely a simple matter of moving permanent data and their
agents. Removal of inappropriate data from source location
without compromise with other nodes can degrade or even
cause system stop. For this, we introduce an assurance node list
for every coordinator node to handle the amount of work when
the former node leaves suddenly the network. The assurance
node list is created in terms of integrity with the coordinator
node in a given location in the VE and the state optimization of
the node with their network‟s neighbor. State optimization
involves the total number of neighbor in the neighboring
resource table and the network delay that represents the time
difference between the packets was send by the coordinator
and the time it was received.
The remainder of this paper is organized as follows. First, we
summarize related work on persistency date in CVEs. Section
3 provides a description of our mobile agent based approach.
Section 4 describes the simulation environment and results.
Finally, Section 5 presents conclusions and identifies areas of
future work, and is followed by References.
II. RELATED WORK
Mobile agents are active computational entities that move on a
network. In the literature, they have been studied under a
variety of assumptions regarding their environment and
capabilities. The agents have computing capabilities and
private storage, although the computational power depends on
the amount of storage they may have. Over the past few years,
many efforts in agents‟ research have been done for network
exploration, Black Hole search, Rendezvous, and Network
Decontamination [31]. Typically agents have memory, distinct
identifiers, can communicate with other agents when they
meet or can exchange information writing on whiteboards
(storage area located at the nodes).
In exploration and rendezvous the network is assumed to be
safe; that is, the agents are assumed to be able to freely and
safely move in the network to perform their tasks. In the Black
hole search and decontamination problem either the nodes
(hosts) or the agents can pose some danger to the network. In
the first case the dangerous node is a black hole, a node where
incoming agents are trapped, and the problem is for the agents
to locate it; in the second, the dangerous agent is a virus, an
agents moving from node to node infecting them, and the
problem is for the ``good” agents to capture it, that is, to
decontaminate the network.
Collaboration agent model are proposed in [5, 8]. Each
agent is considered as an independent entity to reason about a
common problem and gives the agent the ability to
communicate with one other and cooperate with each other. In
[9] authors propose a probabilistic model for Multi Agent
System (MAS) to resolve link failure in MANET and respond
correctly to the new changes in the network. A Java Agent
Development Framework (JADE) [1] was designed to support
mobile devices and to simplify the MAS implementation. A
JADE light version called JADE-LEAD [4] was developed
specifically to run on mobile devices with limited capabilities
such as computation power, and storage resource. The main
drawback is JADE [2] cannot be used where TCP/IP is not
supports and thus it cannot support MANET [6]. Another
notable approach is proposed by A. Genco et al. [3] that use a
Bluetooth protocol to develop agent service on mobile devices
called Agent Network for Bluetooth Devices (ANBD). ANBD
is running on heterogeneous network that contains mobile and
fixed devices with Bluetooth technology enabled. Contrary to
JADE, ANBD can be offer services where TCP/IP protocol is
not supported. Information security and authentication in
MANETs is also a major goal in agents‟ research. There is a
limited amount of literature in this area. In [11] authors
describe a routing protocol using agent in the face of security
compromise. Another approach is proposed by L. Zhou et al.

[4] to manage effectively the digital certificates using Public
Key Infrastructure PKI.
To the best of our knowledge, there are no research efforts that
have considered for data persistency in MCVE application
using mobile agents. The world state will be retained from one
play session to another even when a player is offline. DIVE
[14], Everquest [19], UltimaOnline [24], and SecondLife [20]
are typical applications for persistent worlds. Applications such
as Quake [13] and StarCraft [12] have no persistent ongoing
nature: the world state exists only when a user is actively
participating in the VE. In DIVE [14], the sense of persistency
is handled by running an impassive process called
PERSISTENT that periodically saves the world state to a file in
order to achieve failure-proof restarts. An
AUTOPERSISTENT process controls the PERSISTENTs‟
running process. Like DIVE [14], NPSNET [16] uses active
replication to confront the persistency issue. All object
modifications are done locally and are then distributed to all
peers. However, there is no detailed description of how to
maintain persistency among different users and determine how
they act while they are logged off from the session. Users can
modify the file world state and stress the system. Neither DIVE
nor NPSNET provide any state data classification; thus, all
state data is recorded. This may lead to the consumption of the
peer storage capacity, especially for systems that are always
running and integrate mobile users in the application.
Moreover, we believe that there is a need to create a back-up
approach for certain key nodes in the network which are
necessary for the system to work properly. Key nodes include,
for example, the session manager and zone owner nodes.
Authors in [17] study the persistency issue in structured peer-
to-peer networks [18] in order to support Massive Multiplayer
Games (MMGs). The persistency mechanism takes advantage
of the structured network characteristics in order to control and
manage the replica node. Such a mechanism causes many
difficulties when a higher portion of replications are requested.
Since in DHT a hash function decides in which node the
replica data must reside, this can result in some nodes being
overloaded or unable to handle the enormous amount of data
that must be stored when these nodes function as object or
region coordinators. Existing structured overlay networks were
designed primarily with stationary hosts and high capacity
backbones. The best known examples of CVE applications are
multiplayer online games like EverQuest [19], SecondLife
[20], and Ultima online [24]. These types of games are built on
client-server architecture. The application of a “persistent
world” in a centralized manner provides an easy way to handle
the persistency requirement. However, the requesting server
database maintenance requires more effort and may present a
single point of failure. The salient point of most games, notably
SecondLife, is that they are established with massive VE and
player interaction drives the success of the game. Therefore,
the persistency requirement becomes an important issue for any
CVE application. On the other hand, commercial games
concentrate on the graphics data aspect; some personal
computers have difficulty with the graphics and rendering
process. Thus, they are unable to cope with mobile
applications. In [23], the authors study the replication data
issue in order to support Massive Multiplayer Games (MMGs).
Each participating node and application object is mapped to a
unique ID. Objects are mapped to nodes where their IDs are
numerically close to the object ID. Regions, also known as
zones, are mapped in the same manner and are assigned to a
node participant. Each node can easily elect a replica node to
take over the work when the node is down.
Our approach focus specifically on conserving data persistency
and what to do after a user leave the network with some critical
data that essential for the functioning on the 3D virtual
environment. We use mobile agents which is defined a self-
controlled program to navigate between nodes participating in
the virtual environment and transmitting critical data when
necessary to another node intelligently selected based on the
following criteria: network stability, signal strength and VE
Interest. Data can be quickly transmitted, so the 3D tactical
scenario can be competed effectively.
III.PROPOSED SYSTEM
In order for nodes to maintain data persistency in mobile
collaborative virtual over MANETs, they need to retrieve
critical data from departed nodes. However, with the fact that
Ad-hoc networks are error-prone and nodes may disconnect
suddenly, it can be clearly seen the great feasibility to
incorporate agent services for them that enables nodes to
autonomously make intelligent decision about the node state in
the network and user interest in the virtual environment. Nodes
with worst states are expected to transmit their critical to a
neighbor node, and then former node must inform all neighbors
about the node states. In this paper we propose the detail of
the system with the following:
 Provide agent data persistency service among mobile user
participating in the virtual environment without a fixed
network infrastructure.
 Choose an assurance node list for every coordinator node in
the network to take over the role when necessary.
Mobile agents are special software resides in a node and have
the ability of moving through the network while they take
decision about transferring critical data. It can halt themselves,
migrate to another node, and execute services without being
affected by the status of origin node.
One agent should have three dimensions from representation
and mobility to intelligence:
 Representation: one agent represents one node to other
node or agents
 Mobility: one agent can move through the network and
deliver its node critical information while they travel from
one node to another

 Intelligence: Ability to apply knowledge in order to solve
problems and to take decisions based on collected data.
We claim that agents on MANETs can decide about the status
of the coordinator node by sensing network briefcase and
virtual environment briefcase.
• Network briefcase contains:
o The signal strength measured as energy pickup
from the transmission antenna.
o Network latency represents the time difference
between the time the packet was send and the
time it was received.
• Virtual environment briefcase contains
o The user interest in the virtual environment such
as: Session ID, total number of processed objects
per second, and score earned.
The status of briefcases‟ variables needs to be updated when
necessary for example: user changes his session ID or the
network signal worsens.
Saving critical data in other node works to our benefit, since it
reduces the opportunity for cheating. Data saved on the user
machine may be overwritten and updated; this occurs in
particular when a score increases – when this happens, there is
no need to store previous values. In order to fulfill the limited
mobile device storage requirement, other data that is not likely
to be altered for the purposes of cheating and functioning of the
VE, i.e. private user data, should be saved in the log file
located in the user machine. The log file also records the last
previous user actions; this may be useful when a connection
interruption occurs for a small delay, i.e. a node in the tunnel.
In this case, the system can resume the last previous
intermittent actions when the connection is established once
again. Many advantages can be retrieved by the integration of
the log file. First, it allows a certain level of security. Second, it
minimizes failure-less restarts. Finally, it reduces network
traffic. In order to remain flexible and to handle the high
volume of communication between nodes, many existing
techniques such as caching [21], super-node selection [10, and
22], and download priority scheme may be integrated into the
system in order to limit the amount of network traffic.
A. Agent Navigation Algorithm
The primary goal of agent is to deliver persistent information
from one node to others in the network. In order to achieve this
goal when coordinator node leaves the network for any reason,
the agent needs to exchange message with an agent hosted in
the top position of assurance node list. The top element in the
assurance node list represents the first node candidate to handle
critical data for a coordinator node when the current one leaves
the network. Each coordinator node is responsible to maintain
and manage their assurance node independently.
Initially we assign an agent to each coordinator node in the VE,
agent perform the following operations:
1. Regularly copy critical information from the node memory
2. Update assurance node list
3. Update Briefcases variables
4. Agent Evaluation
4.1. IF Node status worsens “node may leave the
network”
i. Transmit critical data to the first node in the
assurance node list and makes the data of the
crashed node at the service of the community
member.
ii. If the first assurance node is unable to
receive the date, the system will select the
next one in the list.
iii. Inform all neighbors about the changes
4.2. ELSE
i. Go back to step 1
5. stop
B. Agent Evaluation’
The agent‟s signal strength evaluation in our approach uses the
method deployed in Multi Agent based Adaptive DSR
(MADSR) [28]. MADSR is an extended version of the
dynamic source routing protocol DSR [27]. It uses signal
strength as routing metric to predict link break before they
actually occurs. It measures the strength at which it received
the packet and energy level of the node. If the received signal
strength is greater than a certain threshold, the link is
considered to be stable. Thus, agent decision - no need for data
transfer.
The value of the network latency evaluation should be less than
400ms as described in [26] to provide a sense of immersion for
participating users. Such requirement was initially stated for
CVE in wired network. We believe this requirement can be
relaxed to cover CVE in mobile environment.
The user interest evaluation in the VE is defined as the
combination of number of users participating in the same
session, and the total number of processed objects per second.
A connection between agents in the same session requires a
network path between hosts on which agents reside.
IV.SIMULATION RESULTS
We evaluate our system over ad-hoc networks. We create
randomly various scenario files that describe the mobility
pattern for each node using the setdest command provided by
(NS2 v.2.35) [29]. We run the scenarios for about 7200

seconds. The routing protocol based on [28] acquires some
properties such as signal strength, shortest-path metrics,
congestion measurement and energy level in each node; these
are used in route selection decision and by agent to determine
the user feeling in the virtual environment.
Figure 2, shows the average number of virtual environment
system failure. Network size is shown along the x-axis while
the average number of system‟s failure is shown on the y-axis.
In Both approaches, once the network size increases, the
average number counter decreases due to the increased size of
the assurance list. The average number of failure is very low
when employ our mobile agent scheme. This is could be
explained by the impact of agent decision on the node statue.
Figure 2: Average number of system’s failure using
both approaches.
Clearly, the average number of system failures is significantly
affected, when we disable the mobile agent scheme, because
coordinator nodes will send at regular time interval to its
selected neighbor their critical data. The total number of
failures is increased because nodes may leave the network
before the commencement of the time interval and thus all data
are lost.
The overall variation of the failures‟ counter in both
approaches is most likely stable when the network size
increases. With mobile agent the average number of failure is
reduced by almost 60% compared to the regular approach
(Mobile agent disabled).
V.CONCLUSIONS
This paper provides a mobile agent based approach to design a
persistent world for emergency preparedness scenario over ad-
hoc network. Persistency is guaranteed through the agent
evolution of the node state in the network and the user behavior
during the run scenario. The approach was designed s to
ensure reduced traffic between the coordinator node and its
network‟s neighbors. Unlike other approaches, the algorithm is
not directly affected when many nodes leave suddenly the
network. The overall system will provide more reliability and
efficiency because node selection is based on an intelligent
decision computation done by agent resides in a node. The
qualities of our proposed approach: they produce a minimum
data error recovery when a node disconnects, no extra control
messages are required. Data transfer is guaranteed. As shown
in the simulation results the mobile agent decision strategy has
a great impact on the number of system failure. More
simulations need to be done. Several evaluation parameters
can be integrated in the decision strategy to improve the system
performance and functionalities.
ACKNOWLEDGMENT
Authors would like to express their thanks to Prince Sultan
University, and Al-Imam Muhammad ibn Saud University for
supporting this work.
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