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.

1M. Yadollahi and A. Jafarian are with the Mobile Communication Company of Iran, Iran, E-mails: mahnaz.ghaseminajm@hud.ac.uk, a.jafarian@mci.ir

2V. T. Vakili is with Iran University of Science and Technology Engineering, Iran, E-mail: vakili@iust.ac.i

3M. 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 … x1Nx21…

xM1

x22…

xM2

………

…xijxMj

………

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 = 1Nj=1 ( 1 )

978-1-4673-7514-6/15/$31.00 ©2015 IEEE 365

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

Parameter

UMTS1

UMTS2

WLAN1

WLAN2

WiMAX1

WiMAX2

Available 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 � xi3x3min

�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 � xi4x4min

�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 �x1maxxi1

�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 �x2maxxi2

�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�wminwj

�j∈N

≥ 𝑋𝑡ℎ , Then related parameter is

eliminated from decision matrix.

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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 ,𝑤𝑇𝐵) ( 7 )

Step 2: if�wminwj

�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

Conventional

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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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 =

xijxj+� 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

�∑ xij2i∈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+)2j∈N

, Si− = ��(vij − vj−)2j∈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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