1. Reducing Processing Delay and Ping Pong Impact of
Multi Attribute Decision Making Handover for
Heterogeneous Wireless Networks
M. Yadollahi1
, V.T. Vakili2
, M. Ghaseminajm3
, A. Jafarian4
Abstract—Maintaining permanent availability and high
quality connection to desired networks are amongst the essential
concerns of heterogeneous networks considering user criteria. In
this direction, suggesting solutions to decrease the processing
delay and the number of extra vertical handovers of the SAW
and TOPSIS through proposed techniques are the main purpose
of this paper.
Keywords — Heterogeneous Network, Multiple Attribute
Decision Making, Processing Delay, Vertical Handover.
I. INTRODUCTION
The subscribers play an increasingly pivotal role in driving
the mobile network operators to meet their diverse demands.
Otherwise, they simply lose the market to their rivals. In
today's fast-paced world, users tend to connect to networks
that best fulfill their needs in a flexible and reliable way. For
this reason, heterogeneous network management has gained
more attention by service providers. Heterogeneous networks
bring the need of vertical handover in order to select the most
appropriate access network taking the quality of service
criteria into account [1], [2].
In heterogeneous wireless communication, context-awareness
is very important for network selection process, which can be
influenced by various methods for improving the quality of
the user connection. Therefore, the network selection among
other things, is based on the network performance, the end
user's terminal and the defined context. These approaches
attempt to provide the best user perceived service [3].
A substantial amount of research has been carried out in
case of MADM methods for vertical handoff in recent years.
However, it is necessary to widely evaluate and compare their
performance under different scenarios in order to provide the
best solution for a particular application [4]. There is a body
of research in relation to the best network selection based on
user requirements [3], [5], [6], [7]. A new context-aware
vertical handover algorithm has been developed based on a
Multi Attribute Decision Making (MADM) approach in [3]
considering the PQoS (Perceived Quality of Service) as well.
1
M. Yadollahi and A. Jafarian are with the Mobile
Communication Company of Iran, Iran, E-mails:
mahnaz.ghaseminajm@hud.ac.uk, a.jafarian@mci.ir
2
V. T. Vakili is with Iran University of Science and Technology
Engineering, Iran, E-mail: vakili@iust.ac.i
3
M. GasemiNajm is with Department of Engineering and
Technology, University of Huddersfield, UK, E-mail:
u1073452@hud.ac.uk
A vertical handoff decision scheme to enhance the service
mobility using the Simple Additive Weighting (SAW) method
in a distributed manner has been proposed under
heterogeneous environments [7].
In this paper, first of all, we focus on MADM concept for
mobility management especially vertical handoff. SAW and
TOPSIS algorithms are two important methods which will be
discussed. In the next part, proposed approaches will be
introduced and simulated with MATLAB.
II. MADM (MULTI ATTRIBUTE DECISION MAKING)
MADM is an introduced method for vertical handover in
heterogeneous networks. This method offers a new multi
attribute approach which aims to make the decisionin the best
network selection based on different criteria and requirements
of subscribers. These criteria can be very important for service
providers. Considering user and network criteria in the
decision making process introduced a new concept called
context awareness. It means the network selection process will
be more intelligent considering varying needs of users in order
to recommend a better network in variable conditions.
Handover process can be divided into three major sections
[8] which are network discovery, handover decision and
handover execution.
In fact, vertical handoff happens when new network
selected by mentioning method based on decision making
parameters. Noticeably, input of this introduced approach is
named decision matrix with M×N size that M is the number of
surrounded networks and N is the number of decision making
parameters or criteria which M and N is a positive integer. Xij
is array of relatedmatrix which indicates measure of jth
parameter of ith network as below:
�
x11 x12 … x1j … x1N
x21
…
xM1
x22
…
xM2
…
…
…
…
xij
xMj
…
…
…
x2N
…
xMN
�
It is worth noting that we dedicate some weighting values
to our criteria according to user preference. For this reason, it
is necessary to determine traffic classes in line with user
context awareness. wj is weight of jth decision making
parameter that defined by requested traffic. Additionally, the
sum of weights must be equal to 1.
∑ wj = 1N
j=1 ( 1 )
978-1-4673-7514-6/15/$31.00 ©2015 IEEE 365

2. Network selection parameters comprise two types which
are benefit and cost parameters. Benefit parameters are
desirable for users, but cost ones are unfavorable. The larger
the benefit parameter the better it functions. In other words,
smaller cost parameters are also better.
III. PROPOSED APPROACHES
As mentioned beforehand, reducing the processing delay
and decreasing the number of extra handoff are two important
issues to prevent ping pong impact focued on in this paper.
Two types of traffic class, voice connection and data
connection are considered in this research. For voice context,
packet delay and packet jitter have more weight in comparison
with other parameters. While for data context, the weight of
available bit rate and maximum bit rate are more in proportion
of others. It is important to note that our heterogeneous
networks consists of two UMTS networks that are namely
UMTS1 (Network 1) and UMTS2 (Network 2). Also, there
are two WLANs and last two networks are WiMAX, which
are named respectively WLAN1 (Network 3), WLAN2
(Network 4), WiMAX1 (Network 5) and finally WiMAX2
(Network 6). As a decision making table, Table 1 is a base for
decision matrix. This table involves the value range of
different parameters such as bit rate in Mbps (Parameter
1),total bit rate or maximum bit rate in Mbps (Parameter 2),
packet delay in ms (Parameter 3), packet jitter( packet delay
variation) in ms (Parameter 4), packet loss per each 106
packets (Parameter 5) and cost per byte (Parameter 6).
TABLE I
VALUE RANGES OF THE DECISION MAKING PARAMETERS
Paramet
er
UMTS
1
UMTS
2
WLAN
1
WLAN
2
WiMAX
1
WiMAX
2
Availabl
e Bit
rate
(Mbps)
0.1-2 0.1-2 1-11 1-54 1-60 1-60
Total Bit
rate
(Mbps)
2 2 11 54 60 60
Packet
delay
(ms)
25-50 25-50
100-
150
60-150 60-100 60-100
Packet
jitter
(ms)
5-10 5-10 10-20 10-20 3-10 3-10
Packet
loss (per
106
)
20-80 20-80 20-80 20-80 20-80 20-80
Cost per
byte
(price)
0.6 0.8 0.1 0.05 0.5 0.4
A. First Proposed Approach
In this approach, user requirement for a special service has
higher priority to select network among others. In the next
step, selection matrix eliminates networks which do not meet
requirement set for quality of service and user. Steps of the
first approach are as below:
For voice connection:
Step 1: choosing the minimum value of packet delay
(parameter 3) of all networks.
x3min
= mini∈M[xi3] ( 2 )
Step 2: if �
xi3
x3min
�
i∈M
≥ Xth, Then related network can be a
candidate for elimination that Xth is a threshold for
valuecomparison which can be varied based on user demands
and QoS concern and also it is a positive value (Xth > 1). It is
noteworthy that less parameters and networks will be
eliminated from a decision matrix if related threshold is
bigger.
Step 3: choosing the minimum value of packet jitter
(parameter 4) among other networks.
x4min
= mini∈M [xi4] ( 3 )
Step 4: If �
xi4
x4min
�
i∈M
≥ Xth, , Then related network can be
eliminated from existing networks.
Step 5: if a network meets both conditions, then the network
removes from other networks for the selection process.
For data connection:
Step 1: choosing the maximum value of the available bit rate
(parameter 1) of all networks.
x1max
= maxi∈M[xi1] ( 4 )
Step 2: If �
x1max
xi1
�
i∈M
≥ Xth, , Then related network can
candidate for elimination.
Step 3: choosing the maximum value of the total bit rate
(parameter 2) among other networks.
x2max
= maxi∈M[xi2] ( 5 )
Step 4: If �
x2max
xi2
�
i∈M
≥ Xth, ,Then related network can be
eliminated from existing networks.
Step 5: If a network has both conditions, Then the network
removes from other networks for the selection process.
B. Second Proposed Approach
While in the first approach network selection is based on
network omission from decision matrix andin the second
approach weighting factor for parameters play prominent role
in vertical handoff process and decision making. The
following steps describe this approach clearly.
For voice connection:
Step 1: choosing a minimum of value of Packet Delay (PD)
and Packet Jitter (PJ)parameters.
wmin = min�wPD , wPJ� ( 6 )
Step 2: if�
wmin
wj
�
j∈N
≥ 𝑋𝑡ℎ , Then related parameter is
eliminated from decision matrix.
366

3. Step 3: weight byremoving parameter must be divided equally
into other parameter weights for satisfying ∑ 𝑤𝑗 = 1𝑁
𝑗=1 .
For data connection:
Step 1: choosing a minimum of the value of the Available Bit
rate (AB) and Total Bit rate (TB) parameters.
wmin = min(𝑤𝐴𝐵 , 𝑤 𝑇𝐵) ( 7 )
Step 2: if�
wmin
wj
�
j∈N
≥ 𝑋𝑡ℎ, Then related parameter is
eliminated from decision matrix.
Step 3: weight of removed parameter must be divided equally
into other parameter weights for satisfying ∑ 𝑤𝑗 = 1𝑁
𝑗=1 .
C. Combinatorial Proposed Approach
This approach is the combination of two proposed
approaches.In the first step, networks will be selected
according to the user requirement, then remain networks will
be considered for selection according to the weighing process.
Significantly, combined approach has better performance in
view of processing delay among other methods based on
simulation results.
IV. RESULTS ANALYSIS
The purpose of this section is to analyze the simulation
results of the proposed approach by MATLAB software
which concentrate to processing delays and number of vertical
handoffs. First of all, it is essential to know that processing
delay is the time consumingwith the decision matrix to select
the proper networkthrough SAW and TOPSIS algorithms.
Processing delay is a very significant factor to acquire proper
QOS and requirements of subscribers. Before all this, it is
important to note that decision point is a point that multi
criteria algorithms select the network (new or previous
network). In below pictures 1 and 2 processing delay of
conventional and proposed approaches can be observed.
Delay reduction can be spotted by using the described
methods obviously. It’s noteworthy that matrix values are
chosen randomly by using MATLAB simulator.
Fig. 1.Comparison between Processing Delay of conventional
and proposed approaches for TOPSIS in voice connection
(Horizontal axis shows the decision point number)
Fig. 2. Comparison between Processing Delay of conventional
and proposed approaches for TOPSIS in data connection(Horizontal
axis shows the decision point number)
In the next step, we focus on the number of vertical
handoffs in the network selection process. From extra and the
undesired vertical handoff point of view, 100 decision points
are considered by TABLE II for clarifying effects of the
mentioned methods to diminish number of extra handovers.
TABLE II
COMPARISON BETWEEN NUMBER OF HANDOVERS IN CONVENTIONAL
AND PROPOSED APPROACHES
Number of
vertical
handovers
Conventi
onal
approach
First
proposed
approach
Second
proposed
approach
Combinatorial
proposed
approach
SAW 74 70 45 64
TOPSIS 73 72 56 67
The upper table clearly shows that proposed approach,
especially second one reducesthe number of handoffs. It leads
to shrinkingthe ping pongimpact. Figure No.3demonstrates
the comparison of the number of handoverin conventional and
second proposed approach for SAW.
Fig. 3. Comparison between number of handovers in
conventional and second proposed approach for SAW
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4. V. CONCLUSION
Heterogeneous networks can achieve customer satisfaction,
providing the best service based on users' requests and QoS.
Therefore, vertical handover methods are introduced in order
to maintain this aim. This paper has proposed and explained
three decision making approaches that can lead to reducing
processing delays of mentioned algorithms and declining the
number of extra verticals. It also helps shrinking handoffs for
relieving ping pong impact based on reduction of the decision
matrix size.
APPENDIX
A. SAW
Simple additive weighting (SAW) is one of the best known
and most widely used scoring methods because of its
simplicity [4], [9] and [10]. For vertical handoff decisions, the
parameters usually have different measuring units, thus the
values of the parameters require to be normalized first. In
SAW, network ranking is based on summation of 𝑤𝑗 and 𝑟𝑖𝑗
where rij =
xij
xj
+� for benefit parameters and rij =
xj
−
xij
� for cost
parameters. Furthermore, xj
+
= maxi∈Mxij and xj
−
=
mini∈Mxij and weighting vector must satisfy ∑ wj = 1N
j=1 . At
last, the selected network is ASAW
∗
:
ASAW
∗
= arg maxi∈M � wjrij
j∈M
B. TOPSIS
This algorithm is based on the technique for order
preference by similarity to ideal solution (TOPSIS) with M
networks that are evaluated by N decision criteria [10], [11]
and [12]. Here, the chosen candidate network is the one which
has the shortest distance to the ideal solution and the longest
distance to the worst case solution as follows:
a) Construct the normalized decision matrix, which leads
to comparison across the parameters, mentioned
matrix is as below
rij =
xij
�∑ xij
2
i∈M
b) The weighted normalized decision matrix is as
vij = wj ∗ rij
c) Determine ideal and negative-ideal solutions by
A+
= {�maxi∈Mvij|j ∈ J�, (mini∈Mvij�j ∈ J́)}
And
A−
= {�mini∈Mvij|j ∈ J�, (maxi∈Mvij�j ∈ J́)}
Where J is the set of benefit parameters, and J´ is the set of
cost parameters.
d) The positive and negative ideal networks are
Si
+
= ��(vij − vj
+
)2
j∈N
, Si
−
= ��(vij − vj
−
)2
j∈N
e) Find out the relative closest to the ideal solution are as
follows
ci
∗
=
Si
−
(Si
+
+ Si
−
)
Selected network based on this algorithm is
ATOP
∗
= arg maxi∈Mci
∗
.
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