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Design of a Mobile Agents Based Solution to 
Distributional Management of Computer Networks, 

Taking into Account the Security Mechanisms 
 

Saeed Bahrami 
Department of Science 
Farhangian University 

 Qazvin, Iran 
saeedbahrami13@chmail.ir 

 

 

Abstract—Mobile agents (MAs) is one of the technologies 
considered in the recent years to perform management processes. 
This technology provides the ability to move code in distributed 
environments and to connect with other resources and agents 
locally which makes it an appropriate technology in the 
development of software applications of distributed network, 
especially management systems. For using mobile agent 
technology, an infrastructure for the management of MAs is 
needed. In this project, an infrastructure called MCT 
management is introduced for network management. In this 
infrastructure, some protocols like SNMP are used to get 
management data for the network administrator. With respect to 
management ability, MAs can dynamically access the database 
SNMP (i.e. MIB) and extract the data required by the managers. 
Most well-known methods are characterized by being static 
relative to code and location in which components cannot modify 
their location or code in a lifetime. However, the MAs method 
can dynamically increase communications, reduce costs and 
overcome certain limitations by changing location and 
components. 

Keywords-design; Mobile Agent; security mechanisms; MCT 

I. INTRODUCTION  
For a long time the Client-Server (C/S) model has been 

applied for various network affairs. In this model, a computer, 
taken as the Client, demands a request from another device as a 
server and returns the response. The relationship between the 
two is done in sync format and can be done in RPC and 
Message Passing [1]. This method is frequently used in 
network management systems including distributed systems. 
Network management can be a process of controlling a 
network with complex data for maximizing its efficiency. 
Given that network systems are constantly increasing their size, 
their management with modern styles is not efficient, because 
of the stability, synchronous operation, transfer of massive data 
and homogeneous acts. In order to overcome such limitations, 
various decentralized methods have been recommended. One 
of these methods is the use of Mobile Agents (MAs). Agents 
are actually codes moved from a network element to another 
and communicate with local resources and other agents, 

returning the data of one network element to the manager. 
Because of their movement, agents are called mobile. Due to 
their ability to move in distributed environments, MAs are very 
suitable for the development of distributed software 
applications, especially in network management systems where 
the decentralization of management operations is one of the 
main characteristics. In this mode of operation, management 
duties are delegated to the Agents and a number of them can be 
dynamically distributed between management entities in the 
network management system. Using migration capacities, they 
can communicate locally using this protocol, and according to 
information already stored, use the hardware and software 
necessary for the operations management. 

In this paper, first the case of MA technology and its 
management is introduced and then the managing infrastructure 
called MCT is presented and its connection with SNMP is also 
expressed. Then, in simulation mode, the communication of 
MA and MIB, SNMP for administrators is designed in order to 
monitor and control the network.  

II. NETWORK MANAGEMENT BY THE MA SCHEME 
One of the major problems in the C/S method occurs due to 

large data volumes that do not improve network’s efficiency. 
As noted earlier, client-server communication is synchronous 
in C/S model. Although this method performs well in some 
aspects, higher applications in distributed systems will reduce 
the quality of connections and cause problems in applications 
due to the synchronous nature of communications. Therefore, 
MAs are proposed as a new method that instead of moving the 
data to the code, it moves code towards the data. The efficiency 
of the method depends on the code/data volume relation. This 
method basic function is that a code form agent is sent to the 
station(s). The code carries the operations defined on it and 
then returns the required information in two ways: directly or 
by assigning it to another agent [2]. According to the motion, 
this method is particularly suitable for distributed 
environments. With respect to their performance (mobility) 
MAs have enormous potential. For example, they can stop their 
run at one point and resume execution at another location until 



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www.etasr.com Bahrami: Design of A Mobile Agents Based Solution to Distributional Management of Computer …

 

the interruption point [3]. Agents can also communicate with 
stations locally [4, 5]. These capabilities have advantages over 
the traditional method of C/S that include: overcoming network 
latency, reducing network load, working in heterogeneous 
environments, being adaptable to dynamic form and being 
fault-tolerant. This feature also makes this method capable of 
being used in various fields, one of them being the field of 
network management. SNMP protocol is widely used for 
network management [6]. In this protocol, all properties of the 
system either software or hardware are stored in a table called 
MIB. In reality, regarding the existence of different types of 
Agents, they can be moved towards various stations, as the 
required data is extracted from MIB table and report to the 
manager. Therefore, Agents can be used in different network 
management fields including fault management, configuration 
management, performance management and audit management 
applications. 

III. THE SECURITY MECHANISMS OF MOBILE AGENTS 

A. Security Threats 
Agents provide great opportunity for misuse and improper 

use, widening the range of threats [7-9]. To discuss on security 
is enough for one to select a simple method that consists of two 
parts: Agent and Agent Platform. An Agent includes code and 
data that required performing calculations. Mobility provides 
the possibility of movement and circulation of Agent among 
the Platforms. Agent Platform provides the necessary 
environment for the Agent to perform calculations and 
computing affairs. A Platform that an Agent stems by is called 
a Home Platform, which is usually the safest environment for 
an Agent. A Host may contain one or more Agent Platforms 
and an Agent Platform may protect several computing 
environment and meeting places where Agents are connected. 
Four categories of threats have been detected including threats 
created by the attacks of an Agent to an Agent Platform or an 
Agent Platform to the Agent and an Agent to another Agent in 
the Agent Platform, or when other entities attack to System 
Agent. The last classification covers the attack of an Agent to 
another Agent and attack of an Agent Platform to another 
Platform because these attacks at first focused on Platform 
communication capabilities and benefit from potential 
vulnerabilities. The last classification also includes 
conventional attacks against the operating system under Agent 
Platform. For more studies about security, readers can refer to 
[10-13]. 

B. Security Requirements 
Users of networked computer systems, have four kinds of 

security requirements: the ability to be faithful, integrity, 
responsibility or accountability and accessibility. Agent users 
and framework of MA also need the above requirements 
(confidentiality, integrity, responsibility or accountability, 
accessibility, and anonymity.) 

C. Countermeasures 
Many Agent systems relied on a series of hypothetical 

demarcation lines with regard to the issue of safety. First, an 

Agent relies on its Home Platform, where it has been 
established and its implementation begins. Afterwards, Home 
Platforms and other Agent Platforms who rely in this case can 
be safely realized without defect or deficiency. Third, coding or 
encryption which is in the beginning in the form of digital 
signage and used in the list of revoked or certificated, is 
supervised and managed by a specific and general 
infrastructure based on Mobile Agent. In order to create a 
system based on MA, a sub-structure is required. Each 
infrastructure should be capable of running a defined Agent 
and can move it in different machines, and even, if necessary, 
is able to establish communication between Agents. Also it 
provides the necessary security operations for the Agent and 
infrastructure. Unfortunately no infrastructure with the desired 
security could have been created so far. All MAs based 
infrastructures work on the Java Virtual Machine (JVM). So 
first the JVM is installed; then, the working infrastructure will 
be installed. Of course there are a lot of infrastructures, but 
very few of them are standardized. There are two standards 
named MASIF and FIPA for them, as we select one of them 
named Grasshopper which is based on MASIF standard for 
simulation of one of the network management operations. In 
the simulation process, we created 3 locations where one of the 
Agents starts to move on the other two virtual machines and 
reports on a management accounting in telecommunication 
networks. 

IV. SIMULATION AND RESULTS 
Various experiments in the following manner were 

conducted to evaluate both types of network management, each 
one was individually investigated and the results were 
recorded. 

A. Effect of the Number of Network Managed Elements 
(MNE) 

First, we investigate the effect of managed network 
elements to assess the response time. Assumptions: the request 
/ response length was fixed (50 bytes), with 2 Mbps rate of data 
communication, the delay of data connections was within 
milliseconds and initial number of the MAs was five obtained 
as a result of the experiments. Test: behavior of MAs does not 
change according to the type of topology and is almost 
constant, but in SNMP response times in different topologies 
increase faster by increasing the number of managed elements, 
because packets surveyed in SNMP are dependent on the type 
of topology. This experiment shows that if the number of 
managed elements is low, SNMP works better than MA 
because the SNMP message is smaller than the initial value of 
MA. As managed elements increases, the response time for 
SNMP shows a proportionate growth, while is faster for MA. 
Result: Between the two areas, by increasing managed 
elements, MA performs better than SNMP. 

B. Effect of Initial Value of MA 
In this section, we investigate the effect of initial value of 

MA on response time. Assumptions: data communication rate 
was in Mbps and connections delay was 4 Ms. Testing was 
started by different initial values of MA (1, 3, 5, 7, 9 KB) and 



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other affairs are as noted before. Experiment: Conducted tests 
showed that for smaller number of elements less bites are used 
for MA. But when the number of MNEs increases, MA is more 
suitable, according to the PDU Getreguest, UDP and Ipheader. 
As the size of MA increases, the number of bytes depended on 
the management station also relatively increases. In the case of 
response time, as the number of MNE increases the difference 
between the types of MA size increases faster. For example, 
MA with size of 5 K has a better performance than SNMP in 
MNE less than 200. But in more than 200, response time of 
SNMP is less. Results: The lower initial value of MA, the 
better it performs than the SNMP. 

C. Effect of Task 
In this section, we examine the effect on response time 

regarding the kind of action. Assumptions: first action is 5 
bytes in length (like the previous sections), the second action 
has a request / response with a length of 400 bytes and the third 
action has a variable length of 150 bytes. MA size is 5 KB and 
topologies are like the previous section. Experiment: According 
to test carried out on these three different size actions, it 
showed that when the MA or SNMP are used for network 
management, different response times are obtained. In SNMP 
type of operation does not have a high impact on response time 
(very small difference), because in fact the number of bytes 
exchanged between the management station and MNEs is low, 
but in MA, because the number of exchanged bytes increases 
(for example, from the first to the third action) response time 
also increases because MA is transmitted with more problems. 
The result: By increasing the size of an action, response time 
increases in MA and is nearly constant in SNMP. 

D. Effect of Unload Strategies 
In this part, two strategies are considered for MA. First their 

performance is explained and then we examine which of them 
is better. Assumptions: We consider the three different actions 
of previous section. The maximum number of visited elements 
is from 1 to 240. MA topologies and sizes are as the previous 
section and the number of visited elements in sweep is the 
same. Test: In the previous sections was revealed that size of 
MA has a direct relationship with number of visited elements, 
which means that as the number of visited elements increase, 
MA size also increases and as a result migration is more 
difficult. Now consider two strategies to evaluate this issue: 

• The first strategy (S1): MA is returned to the management 
station with the results. 

• Strategy 2 (S2): MA only returns the results to the 
management station. (Number of elements that MA passes 
during the sweep is fixed.) 

1) Strategy 1 (S1) 
Experiments show the response time of strategy S1, when 

the number of managed elements in the path of movement 
visited by the Agents is greatly reduced. If the visited nodes 
during movement are rising up to a specific point, the response 
time is decreased, and it increases if the number of Agents 
raises and creates problems for motion. The optimum point for 

the number of nodes for this strategy is 16. The tests are shown 
in Table I. 

TABLE I.  RESPONSE TIME IN S1 STRATEGY WITH DIFFERENT 
OPERATIONS 

Taskt3(s) Taskt2(s) Taskt1(s) Elements per trip Numbers 
32.73 32.63 32.54 1 1 
19.63 19.53 19.44 2 2 
10.25 10.02 9.80 8 3 
9.16 8.75 8.34 16 4 
10.03 9.29 8.54 30 5 
11.75 10.28 8.82 60 6 
15.83 12.93 10.03 120 7 
24.35 18.56 12.78 240 8 
11.30 10.75 10.21 SNMP 9 

 

Based on the data of this Table, the response time is up to 
62% compared with optimal point (16 elements) of t1 and t2 
operations, and is reduced by accumulation of all 240 variables 
in path. The strategy optimized for all operations works better 
than SNMP. For a smaller number of elements in motion, size 
of operation has no effect when MA has a low size, but when 
number of elements in the movement is bigger, for example, 
240, difference between practices is significant. Therefore, 
increase of the size effect, makes this strategy better. 

2) Strategy 2 (S2) 
Response time in S2 strategy has an optimum point. The 

following Table shows the results of tests performed in 
accordance the results. Based on Table II, the response time is 
up to 64% compared with optimal point of t1, t2 and t3 
operations and is reduced with accumulation of all 240 
variables in path. 

TABLE II.  RESPONSE TIME IN S2 STRATEGY WITH DIFFERENT 
OPERATIONS 

Taskt3(s) Taskt2(s) Taskt1(s) Elements per trip Numbers 
21.86 21.54 21.22 1 1 
14.51 14.19 13.86 2 2 
9.48 9.03 8.58 8 3 
8.86 8.45 7.84 16 4 
9.87 9.13 8.38 30 5 
11.67 10.20 8.74 60 6 
15.79 12.89 9.99 120 7 
24.33 18.54 12.76 240 8 
11.30 10.75 10.21 SNMP 9 

 

Comparison of both strategies for action, t1, indicates that 
S2 performs better when the number of managed elements in 
path is low, compared to the case where MA’s code is not sent 
to the management station. As the number of elements in path 
is increased, both methods act in the same way, because the 
size of the data collected by the Agent becomes more than the 
size of MA code. In this experiment, the initial value of MA 
also has an effect. Because the initial value of MA is lower 
response time is also less. The result: if the number of elements 
met in path is high (more than 16) and if results are returned to 
origin or MA is returned associated with MA, they act in 
similar ways. 



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E. Effect of the Data Rate of Domain Links 
In this section, we want to know how data rate affects the 

connections made between domain links. Assumptions: Each 
request / response possess 50 bytes data, data rates are of 1, 2 
and 0.064 Mbps, connections delays of 4 ms and the initial MA 
value of 5 kb. According to the operation performed on 
different data rates, the results show that in lower data rate 
(0.064), SNMP and MA both have more response time (but 
response time of MA is more than SNMP). But for other data 
rates, both have almost the same response time. Results: When 
data rates are higher, MA and SNMP have a better performance 
compared to the case where data rates are lower. 

V. CONCLUSION 
Considering their performance, MAs have many 

capabilities. They can stop running in one point and continue 
running from that stop point in another location. They perform 
synchronously and they can communicate with stations locally. 
These capabilities offer them advantages over the traditional 
Client-Server scheme. SNMP protocol is widely used for 
network administration. In this protocol, all traits and 
characteristics of the system are stored in a MIB table. In fact, 
different existing agents can be moved to different stations to 
extract data required by administrator from MIB table of each 
station and report to the administrator. In this study, an MA 
based solution was designed to manage distributed computer 
networks, taking into account security mechanisms. In this 
project, an infrastructure called MCT is introduced for network 
management. Results of simulation have revealed that between 
the two areas, by an increase of the managed elements, MA 
works better than SNMP. If the initial MA value is lower, it 
performs better than SNMP. Increasing the size of an action 
leads to an increase of MA response time but it is almost 
constant at SNMP when the number of visited elements in the 
path is large (more than 16). MA acts almost the same and in 
higher data rates, if the MA is returned by the result or the 

result only is returned to the source. MA and SNMP work 
better in the conditions where data rates are lower. 

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