A New Model of Genetic Zone Routing Protocol (GZRP): The Process of Load Balancing and Offloading on The UMTS-IEEE 802.11g Hybrid Networks

TELKOMNIKA, Vol.15, No.2, June 2017, pp. 598~605
ISSN: 1693-6930, accredited A by DIKTI, Decree No: 58/DIKTI/Kep/2013
DOI: 10.12928/TELKOMNIKA.v15i2.5633  598
Received February 15, 2017; Revised April 12, 2017; Accepted April 26, 2017
A New Model of Genetic Zone Routing Protocol (GZRP):
The Process of Load Balancing and Offloading on The
UMTS-IEEE 802.11g Hybrid Networks
Setiyo Budiyanto*
1
, Arissetyanto Nugroho
2
1
Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia
2
Universitas Mercu Buana, Jakarta, Indonesia
Corresponding author, e-mail: sbudiyanto@mercubuana.ac.id*
1
, arissoehardjo@yahoo.com
2
Abstract
The stages of the process of Genetic Algorithm (GA), are: Encoding Genotype and Chromosome;
Set Initialization Population; Evaluation Fitness Function; and Selection Process as well as in the later
stages Cross Over Process and Mutation. Outputs from the tests performed in this study can be obtained
by comparing the Genes of the Child (condition data traffic on the UMTS Hybrid - 802.11g network after
the GA) against Gen Holding (traffic data before the GA process).
The research was conducted by calculating the environmental factors, namely: The scheme Two
- Ray Model Propagation and Overlapping Channel Interference Factor, the Doppler Effect be ignored
because the User Equipment (UE) is considered not to shift significant arenas on the IEEE 802.11g
networks. The results of the research is as follows: In the process of cross over, there is a significant
change in the bandwidth, data traffic capacity and Power parameter changes by 9 MHz, 36 MB, and 40
dBm. In the process of mutation, there is a significant change in the bandwidth, data traffic capacity, and
Power parameter by 17 MHz, 32 MB, and 20 dBm.
Keywords: genetic algorithm, UMTS-IEEE 802.11g hybrid networks, two-ray model propagation,
overlapping channel interference factor
Copyright © 2017 Universitas Ahmad Dahlan. All rights reserved.
1. Introduction
The utilization of data traffic on the Universal Mobile Telecommunications System
(UMTS) has been increased, along with the supporting technology development [1]. It resulted
in the idea to stream the mobile data traffic to other wireless networks such as Wireless Fidelity,
in this study used t type IEEE802.11g [2-3]. Mobile Advanced Delivery Network (MADNETs) is
the network is able to process the transfer of data from several different networks (UMTS and
WIFI)[4-5]. The process of moving data traffic from UMTS network to a WiFi network and also
the reverse process (the transfer of data traffic from the WiFi network to a UMTS network) is
namely the process of UMTS - WiFi Offload. Vertical Hand Over (VHO) algorithm Used in order
to perform the offloading process [6-7]. Until nowadays, there has not been a study that
addresses the special routing protocols that can divert traffic to other access points that are in a
cluster. Meanwhile, on the other hand technology Mobile Ad-Hoc Network (MANET) has some
concept of routing protocols: Reactive, Proactive, and Hybrid [8].
The activities carried out at the investigation are: Development of Genetic Zone Routing
Protocol (GZRP) that has been developed in previous studies [9-11]. Namely by elaborating the
Genetic Algorithm begin from population initialization process with the best individuals search by
cross over methods as well as to the process of genetic mutation.
2. Related Research
The development of technology resulted in increased usage of data in the mobile
network. On the other hand, the technology that existed at present incapable of becoming the
solution of the problem of increased traffic on these data; it brought the idea to drain the mobile
traffic to other wireless networks such as WiFi [12-13]. A MADNET technology architecture that
is capable of forwarding traffic to mobile wireless networks such as WiFi accordance research

TELKOMNIKA ISSN: 1693-6930 
A New Model of Genetic Zone Routing Protocol (GZRP): The Process of… (Setiyo Budiyanto)
599
conducted in [4]. On the process of offloading traffic from UMTS network to a WiFi network,
contained VHO algorithm is: capable of performing the handover process from the UMTS
network to a WiFi network [6]. In UMTS - WiFi Offload technology there has been no special
routing protocols that can divert traffic to other access points that are in a cluster. On the other
hand, wireless technologies such as Mobile Ad-Hoc Network (MANET) have some concept of
routing protocols: Reactive (on-demand), Proactive, and Hybrid [8].
In [10-13], a concept known as load balancing using Genetic Zone Routing Protocol
(GZRP) on the wireless network MANET, which is a load balancing with bringing the total
packets received to an alternative route so as to reduce the traffic load on a standalone service.
According to [9], GZRP is the development of hybrid routing protocols in MANET namely Zone
Routing Protocol (ZRP) which is coupled with Genetic Algorithm (GA) [14]. ZRP is used to
reduce the burden of proactive routing protocol control and reduce the latency caused by the
discovery in a reactive routing protocol. In [15] described a WiFi network interworking and
UMTS networks, one of which is the handover process that goes from the cellular network to the
WLAN. In [6] described a concept handover algorithms set up with both the process of handover
from UMTS to WiFi known as algorithms Vertical Handover (VHO). In [6], Vertical Handover
(VHO) focused on Goodput and RSSI, known as Hybrid-RSSI algorithm. One thing that is not
easy to get an accurate estimate of goodput in the real environment. The second proposal is a
hybrid-RSSI estimation algorithms utilizing VHO goodput to ensure the quality of services
provided to users.
In [10-11], [16-17], has carried out research related to the use of protocols GZRP
combined with VHO occupancy in order to achieve efficiency levels of data traffic, either on the
network or UMTS and WiFi networks; as well as the simultaneous performance of both
networks. The discussion in detail to the discussion of performance improvement GZRP
protocol can be used as a very interesting discussion in order to seek more comprehensive
solutions related to problems that occur in the process of load balancing using GZRP protocol.
The Hybrid protocol used is the Genetic Zone Routing Protocol (GZRP) [10-11], is able to
improve the efficiency of the performance of a network. It can also reduce the load on the track
by balancing the distribution of packet delivery over the course of the alternatives available.
Utilization concept GZRP especially in the process of traffic load balancing between nodes.
This study aims to investigate intelligent systems load balancing algorithms and WiFi offload in
the wireless communication traffic bottlenecks can be overcome; in addition, also equal
distribution of traffic and to develop methods of genetic algorithm combined routing protocol
ZRP (Zone Routing Protocol) in the process of offloading in the load balancing and IEEE
802.11g WiFi network. In this case the load balancing process in the Hybrid UMTS networks-
IEEE 802.11g. Load balancing happened in the WiFi network is a follow up of the process of
offloading data traffic from UMTS network to a WiFi network. Offloading process occurs when
the condition value is smaller than the UMTS RSS RSS threshold (do the process of moving
traffic from UMTS networks to WiFi).
3. Proposed Algorithm
Offloading process occurred conditions at the time a UMTS RSSI value less than the
RSS threshold (carried out process of moving the traffic from a UMTS networks to WiFi). The
parameters used in this study were related to load balancing using GZRP (in the WiFi network)
is the bandwidth, capacity and power. These three parameters will be linked with other methods
of dealing with the propagation and interference, while the effect doopler ignored for User
Equipment (UE) is considered not to shift a significant place. Propagation models used is the:
Two-ray propagation model models, while the interference parameters using Overlapping
Channel Interference Factor. The algorithms developed in the study can be seen in Figure 1.

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TELKOMNIKA Vol. 15, No. 2, June 2017 : 598 – 605
600
START
RSS >
Threshold
UMTS Active
yes
RSS >
Threshold
Mx = 0
yes
Data Transmit
no
T = 50s
no
END yes
Link Going
Down Event
yes
no
Inactive
RSS >
Threshold
no
no
yes
RSS >
Threshold
no
Mx = 0
yes
yes
no
Capacity Fall
Or Status Down
GZRP
yes
T = 50s yes
no
no
WiFi Active
Data Transmit
Figure 1. The Proposed Algorithm
Figure 1. Schematic of a working
system algorithm developed in the the
research, it can be seen Wi-Fi offload
process that can be described as
follows:
1. User Equipment (UE) is
automatically connected to the
UMTS network, if RSS> RSS
threshold, then it would use the
UMTS network; If the RSS <RSS
threshold then alert will be given a
link going down and will carried out
Initialization network conditions and
checking RSS in the nearest WiFi
node.
2. If the WiFi network also did not
have RSS> RSS threshold, then the
demand for packet was suspended
for a specified timeout.
Subsequently, the EU network be
deactivated.
3. At the time of the network used, has
one of the parameter value 0 of the
variable Mx, it will be vertical
handover. The parameters that
determine handover is defined in
Equation (1).
( ) ( ) ( ) ( ) (1)
Annotations:
= The bandwidth used by the network to connect (to a UMTS network or WiFi network)
bth = The threshold of the bandwidth required by the EU
= The value of the received signal strength by the EU
= The RSS threshold value of the EU
= The energy possessed by the base station and the access point
Pth = The energy required by the EU
= The capacity of the network service capabilities by the EU
Cth = The threshold of capacity is required to process UE connection to the network
In a WiFi network, are applied the algorithm with the ability to determine when capacity
nodes is in the process of transition or receive the data reaches the threshold or link node status
is down applied GZRP routing protocol.
4. Simulation, Results and Discussion
The study bounded during load balancing from a UMTS network to the IEEE 802.11g
network. The Genetic Algorithm process begins; as for the stages of the process is carried out
as follows: Encoding, Population Initialization, Determination of Value Fitness, Selection, Cross
Over and Mutation.
To initiate this process first define the problem, the scenario was made of the condition
of User Equipment (UE) and Access Point (AP). AP assumed each of which there are 10 with
the bandwidth, capacity and power as follows:

601
UE
Power 10 dBM
Video via Youtube 5MB
-GZRP-
AP 1
WiFi
AP 2 AP 3 AP 4 AP 5 AP 6 AP 7 AP 8 AP 9 AP 10
Figure 2. Assumptions for User Equipment (UE)
Annotations :
Bandwidth (Bth) = 5 MHz
Capacity (Cth) = 5 MB
Power (Eth) = 10 dBm
Details of the process, described further, as follows:
1. Encoding in the process of Genetic Algorithm
The encoding process in the genetic algorithm is the process to encode a gene in a
chromosome. These genes can be represented in the form of binary bits, real number, a list of
rules, permutation elements, and element of the program or other representation that can be
operated in the genetic operations.
In load balancing, to a WiFi network each node is encoded form of binary numbers are
adjusted for the number of nodes. Forms for each individual chromosome can be seen in
Table 1, as follows:
Table 1. The form of chromosomes to each individual (in binary format)
Bandwidth
(MHz)
Capacity
(MB)
Power
(dBm)
AP1 000101 000110 010100
AP2 000110 001000 010100
AP 3 001000 001010 010100
AP4 001001 001111 010100
AP5 001011 010100 010100
AP6 001101 011001 010100
AP7 001110 011110 010100
AP8 010000 101000 010100
AP9 010010 101101 010100
AP10 010100 111000 010100
Based on the data presented in Table 1, it can be seen that the WiFi network (IEEE
802.11g) consisted of 10 individuals (access point) where each chromosome is defined in binary
form. Defining chromosomes are based on three parameters such as bandwidth that put the
group first column, column group capacity in the second and third power in the column. Each
chromosome is made up of six genes that total in single individual genes to 18 genes.
Fitness Function in the Genetic Algorithm
A function is a reference for the optimal value based on the objectives, namely: the
selection of the optimal AP for the EU to consider the bandwidth, capacity and power. The
fitness function used can be seen in Equation (2) as follows:

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[ ] * ( ) ( ) (
(
)+ (2)
Description of the parameters used in Equation (2):
X[i] = Fitness Function for the access point number - i
A = Coefficient of Bandwidth
B = Coefficient of Capacity
C = Coefficient of Power Consumption
= Bandwidth contained in the access point
= Bandwidth Threshold (contained in the UE)
= Capacity of Access Point
= Capacity Threshold (contained in the UE)
= Power of Access Point
= Power threshold (contained in the UE)
5. Results and Analysis of the Research
In this section will be discussed related to the results and analysis of outcomes which
have been obtained. In this research, discusses the process of genetic algorithms starting from
the stage of the gene encoding the individual constituent (access point) and ending with the
mutation of an existing gene. The following discussion details about the results of research and
analysis of the results of this study:
a. Process of Cross Over at the MADNETs Network by GZRP
The discussion done with the assistance of software NS2.35 and Matlab; for further
validation of the data based on by parameter adjustment (6). Be discussed in more details
regarding the parameters of bandwidth, capacity and power before and after through GZRP (by
comparing the value of both of them using the parameter propagation and interference).
b. Parameter Bandwidth in the Crossover Process
The first parameter is used as a media data validation at the the cross over is
bandwidth. Values bandwidth before experiencing GZRP process is the result of the bandwidth
that has been presented in Table 1 while the value of the bandwidth after processing GZRP is
the value of the match by fitness on the bandwidth which has been interbred by another access
point. Outcomes bandwidth obtained before and after the process of GZRP, as shown in
Figure 3:
Figure 3. Bandwidth on the conditions before and after the process GZRP
Based on the Figure 3, can be seen the results of the cross over process in the
bandwidth parameters contained in the access point. It was concluded that the access point 5
has a value change is the greatest bandwidth is 9 MHz.
c. Parameter Capacity Data Traffic in the Crossover Process
In the cross over process, the data traffic capacity is used as a parameter in terms of
measurements and data validation. The value of capacity in before the GZRP process is the

603
result of the capacity that has been presented in Table 1, while the value of capacity after
processing GZRP is the value of the match with fitness on the part of the capacity that has
undergone cross over to the other access point. Outcomes of capacity earned before and after
the process of GZRP, as shown in Figure 4.
Figure 4. Capacity Data Traffic on the conditions before and after the process GZRP
Based on the Figure 4, can be seen the results of the cross over process in the capacity
of traffic data parameters contained in the access point. It was concluded that the access point
5 has a value change is the greatest capacity of traffic data is 36 MB.
d. Parameter Power in the Crossover Process
Process of Mutation at the MADNETs Network by GZRP: Mutations in the the GA will
influence the gene at the individual, which generates the best individual or otherwise decreased
of quality. In the process of testing mutations in MADNETs network using GZRP, which used
the same parameters as in the process of Cross Over: Bandwidth, Capacity Data Traffic and
Power.
e. Parameter Bandwidth in the Mutation Process
The first parameter is used as a tool for validation data on the mutation process is
bandwidth. The value of bandwidth before experiencing the GZRP process is the result of the
bandwidth that has been presented in Table 1; the value of Bandwidth after processing GZRP is
the value of the matches with fitness on the bandwidth that has develop of mutation. Outcomes
of bandwidth earned before and after the process GZRP, can be seen in Figure 5:
Figure 5. Bandwidth on the conditions before and after the process GZRP
Based on the Figure 5, can be seen the results of the cross over process in the
bandwidth parameters contained in the access point. It was concluded that the access point 8
has a value change is the greatest bandwidth is 17 MHz.

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f. Parameter Power in the Mutation Process
The value of power before experienced the process GZRP is the result of a power that
has been presented in Table 1, while the value of power after processing GZRP is the value of
the match with fitness on the part of the capacity that has undergone mutation to the other
access point. Outcomes of power earned before and after the process of GZRP, as shown in
Figure 6:
Figure 6. Power Bandwidth on the conditions before and after the process GZRP using two ray
model and interference dynamic overlapping channels
Based on the Figure 6, can be seen the results of the cross over process in the power
parameters contained in the access point. It was concluded that the access point 5 has a value
change is the greatest power is 20 dBm.
6. Conclusion
In this section, there will be a discussion and analysis of results obtained from testing
the model renewal GZRP on IEEE 802.11g network, the load balancing the process and
offloading on Hybrid UMTS networks - IEEE 802.11g. The process of discussion and analysis of
the test results of the research that has been done is to determine the performance of the
performance of the system that has been created based on the methodology proposed in this
study.
1. The process of GZRP on the MADNETs network; The steps undertaken in this process
starting from the Encoding, Population Initialization, Determination of Value Fitness,
Selection, Cross Over and mutation.
2. The discussion on the results of research that has been done by calculating the
propagation factor two ray model and interference dynamic channel assignment.
3. In the the process crossovers; Access point 5 have the value changes bandwidth, capacity
and power of the greatest in the amount of 9 MHz, 36 MB and 40 dBm. Retrieved a
conclusion based on these conditions, namely: User Equipment will be connected to the
Access Point 5 at the time of the selection of the access point with the network UMTS -
WiFi (IEEE 802.11g).
4. In the process of mutation; Access point 5 have the value changes bandwidth, capacity
and power of the greatest in the amount of 17 MHz, 20 MB and 20 dBm MHz. Retrieved a
conclusion based on these conditions, namely: User Equipment will be connected to the
Access Point 5 at the time of the selection of the access point with the network UMTS -
WiFi (IEEE 802.11g).
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A New Model of Genetic Zone Routing Protocol (GZRP): The Process of Load Balancing and Offloading on The UMTS-IEEE 802.11g Hybrid Networks

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