CHAPTER 3

VERTICAL HANDOVER DECISION S CHEMES FOR NETWORK

SELECTION USING MADM

3.1 OVERVIEW

Methods and material required for this research work are described in this

chapter. VHD schemes for network selection using MADM algorithms are used in a

distributed manner. Based on the survey, VHD is discussed in chapter 2, the

handover decision schemes are mainly focused, assuming the calculation of the

handover decision criteria is performed on the MT and the candidate network. This

calculation requires a non- negligible amount of resource that can affect the MT

performance in terms to reduce handover processing delay. To evaluate the VHD

schemes some evaluation parameter are calculated to reduce the processing delay.

The decision schemes performance with the handover matrix of MTs running

application, MT offered QoS parameters to calculate the neighbour networks

availability and the available network calculate the required QoS for MT using

MADM algorithms and send to the MT and then MT choose the network by the MT

to handover.

The section of this chapter are organised as the vertical handover

management in NGWNs are conjunction with IEEE 802.21 framework explained in

section 3.2, VHD process and the decision algorithm MADM for network selection

are discussed in section 3.3, section 3.4 discussed about the QoS parameter, which is

used for selecting the network for MT VoIP application. Section 3.5 explains the

VHD schemes. Section 3.6 explains the performance evaluation parameters for

reducing handover processing delay in HWNs environment and finally in section 3.7

summary of this chapter is discussed.

3.2 VERTICAL HANDOVER MANAGEMENT IN NEXT GENERATION

WIRELESS NETWORKS

In NGWNs, IEEE 802.11 a/b/g WiF i, IEEE 802.11 p Wireless Access in

Vehicular Environment (WAVE), IEEE 802.16 WiMax, UMTS, High Speed

Downlink\Uplink Packet Access (HS DPA/HS UPA), Long Term Evolution (LTE)

and so on are the critical challenges to achieve ABC in vertical handover. As

discussed in [34, 126, 127], the key requirement in HWNs is seamless vertical

handover, where different networks are integrated. In this research work, IEEE

802.21 Media Independent Handover (MIH) networks are used to accelerate vertical

handover. Handover management issues include mobility scenarios, matrix, decision

algorithms and procedures. Mobility scenarios can be classified into horizontal and

vertical handover. In this work, vertical handover is used as a mobility scenario.

The vertical handover is used in the heterogeneous network can be initiated for

convenience rather than the connectivity reasons. According to user choice, vertical

handover is used for choosing a service from available service. The main challenges

in vertical handover management are seamlessness and automation aspects in

network switching.

3.2.1 IEEE 802.21 Media Independent Handove r

Framework fo r vertical handover signalling is called IEEE 802.21 MIH. The

purpose of IEEE 802.21 is to improve user experience by providing an MIH

functionality that facilitates both mobile - initiated and network initiated handovers.

The specification consists of the following elements as in [126]

i. MIH functions (MIHF)

ii. Service Access Points (SAPs)

iii. MIH users.

MIH Functions

IEEE 802.21 MIH function defines three services to facilitate vertical

handover in heterogeneous networks.

i. Media Independent Event Service (MIES).

ii. Media Independent Command Service (MICS).

iii. Media Independent Information Service (MIIS).

MIES provide events reporting, events filtering and events classification services

depending on the link dynamics. MICS supports methods to send commands from

higher layer to lower layer. F inally, MIIS defines a mechanism for an MIH entity to

discover available neighbouring network information within a geographical area.

The current 802.21 MIIS specifies, a MT gets the neighbourhood information server

(IS). The static and dynamic information are providing in IS.

Static Information

In static information, the name of service providers, Medium Access Control

(MAC) addresses and channel information of the MT‟s current network

neighbourhood are present.

Dynamic Information

It includes link layer parameters such as data rate, throughput and other

higher layer service information to make an intelligent handover decision.

Therefore, IEEE 802.21 MIH is an evaluation to support vertical handover by

providing capabilities to detect and initiate handover from one network to another

network. Also, MIH provides service to assist handover between the HWNs which

is used in this research work.

SAP: It defines both media independent and media-specific interfaces. Here,

MIH_S AP, MIH_LINK_SAP, MIH_N ET_S AP are included.

i. MIH_S AP

The MIH_S AP provides a uniform interface for higher layer to

control and monitor different links regardless of access technology.

ii. MIH_LINK_SAP

The media-specific S AP provides an interface for the MIHF to contro l

and monitor media-specific links.

iii. MIH_NET_S AP

The media-dependent S AP provides transport services over the data

plane on the local node, supporting the exchange of MIH information and

message with the remote MIHF.

MIH Users

The MIH is the functional entities employed for MIH services. MIH users

are abstraction of the functional entities that employ MIH services. A typical user of

Comma nd

Li nk Comma nds

Li nk Events

Even ts

MIH service could use those services to optimize handover, where MIH users can

subscribe the MIES to be notified when events necessary to the handover decision

and process occur.

IEEE 802.21 defines, MIH framework that can significantly improve

handover between heterogeneous network technologies. The standard defines the

tools required to exchange information, events and commands to facilitate handover

initiation and handover decision phases. Therefore, the MIH framework is equally

applicable to systems that employ Mobile IP at the IP layer as the systems that

employ Session Initiation Protocol (SIP) at the application layer. It does not attempt

to standardize the actual handover execution.

In figure 3.1, it shows the MICS & MIES Models. MICS used MIH users to

manage and control link behaviour relevant to handover. MICS is initiated by higher

layer and sends it commands to lower layer. MICS typical examples are MIH scan,

MIH configure, MIH switch etc., MIES are mainly providing event classification,

event filtering and event reporting to upper layers.

Upper La y er

(La yer 3+)

Upper La y er

(La yer 3+)

MIH Comma nds Remote MIH MIH Even ts Remote MIH

MIH

Functi on

MIH

Functi on

Lower La yer

(La yer 1 + La yer 2)

Lower La yer

(La yer 1 + La yer 2)

Figure 3.1: MICS & MIES Models

MIES have some defined events, M IH link up, MIH link down, Link up and

Link down. Lower layer generates link up and Link down events. These events are

notified to the MIHF and then MIHF reports this situation to the upper layer by

triggering MIH link up and MIH link down events. MIH provides information about

neighbouring network for MIH users. This information, such as neighbour map, link

layer information and availability of services, can be used to select the target

network, when vertical handover is needed. IEEE 802.21 MIH has de fined as

Information Server (IS) to maintain the visitor network information and offer it to

the MT.

The figure 3.2 explains the procedure of vertical handover in IEEE 802.21

[128]. The following steps illustrate the vertical handover procedure

Step 1: When a handover is triggered, an MT sends a neighbour list query message,

which requests the neighbouring network list from the IS. Then the IS sends a

neighbour list response message containing the available networks information such

as QoS requirement, network type, PoA address and so on.

Step 2: After receiving the response message, the MT scans for nearby PoA to

measure up-to-date channel states.

Step 3: Once the MT completes the scanning procedure, it sends target list query

messages containing the measured channel state values to the IS. Then, the IS to be

evaluated each suitable networks, as the handover target network by means of

vertical handover decision function. After completing the evaluation, the IS sends a

target list response message to the MT.

Step 4: F inally, the MT executes a handover to the target network with the highest

priority in the target list.

As illustrated in figure 3.2, the MT should perform multiple scanning

procedures to measure the channel state from neighbour networks where N is the

networks. The delay significant is shown. Especially, when the number of available

network is large, significantly handover delay increased can be observed.

In this research work, the MT managed by the same operator and has

different wireless technologies are used as heterogeneous networks. As discussed

above, delay is increased significantly. To reduce the processing delay, MADM

algorithms are used in distributed manner. This section presents a scenario, where

IEEE 802.21 can improve the user experience by facilitating seamless handover

across HWNs access technologies.

MT N1 PoA N2 PoA2 IS

Ha ndover Tri gger

Nei ghbour Li s t Query

Scanning

Nei ghbour Li s t Res pons e ( N1 PoA, N2 PoA )

Scanning

Network S el ecti on

Vertical Handover to N2 PoA

Figure 3.2: Vertical Handover procedures in IEEE 802.21

Figure 3.3 represents a handover scenario between two-access network

administered and managed by the same operator. The networks worked as groups,

which supports seamless mobility within their own networks. The IEEE 802.21

working group provide a media independent framework to support handover

initiation and decision as in [43].

The IEEE 802.21 working group is filling this gap by providing a media

independent framework to support handover preparation and initiation. In the core

network elements, MIH services can be integrated and then MT facilitates the

handovers.

Dual- mode MT can access the I EEE 802.21 services, through any access

technology. For example, while a MT is within the WiMax network, it can query the

IS to obtain available WiF i network information, without activating and directly

scanning through the WiF i interface. This can conserve the battery power of the MT

significantly. Using the information provided by the IS, the MT can activate its

WiF i interface, confident that an appropriate WiF i network is available. Then, it can

associate and authenticate with the WiF i network while the session is active through

the WiMax interface. The MIES allow new links to be discovered and qualified

prior to handover, while MIH commands can be used to begin the handover process.

The MIH services allow the time-consuming work associated with handover

initiation, which prepared to be completed before the handover takes place, thus

significantly reducing handover delay and packet losses.

MIHF (IS) Server)

Mobility

Management

Entity

HSS/AAA

Network 1 Network 2

Figure 3.3: Handover between two networks

Both network working groups are creating media-specific extensions in

respective task groups to enable interaction with the IEEE 802.21 framework. After

these extensions are completed, the MIH framework can enable seamless handover

scenarios.

3.3 NETWORK S ELECTION IN HETEROGENEOUS WIRELESS

NETWORK

Service delivery in a HWN environment requires the selection of an optimal

access network. The selection of an access network in a HWN environment depends

on several parameters with different relative importance. The HWN gives the option

to mobile users to benefit the advantages of diverse network characterization.

The following crucial factors should be considered for a sufficient vertical handover

decision is as follows

i. User Mobility: User Mobility includes, dynamic factors like speed and

location information

ii. Network Condition: Network Condition includes, a factor like the number

of active users and available bandwidth in the network.

iii. Service Type: Different service types may affect the handover decision as

the requirements of each service differ in terms of data rate, latency, etc,.

iv. User Preference: A user may prefer one of the networks to another in

terms of cost and QoS.

v. Pricing Issues: Pricing issues includes financial costs, which affects the

use r‟s choice in the handover decision.

Selection of a non-optimal network can result in undesirable effects such as

higher costs or poor service experience network selection in such environment are

influenced by several factors and currently a complete solution is not available to

solve this problem. This research work describes a comprehensive decision making

process to rank candidate networks for service delivered by the MT. In [129], the

system architecture for MT based approach uses network assistance for network

selection. This research describes an extensive decision- making process for network

selection that can be used in the network to provide candidate network for service

delivery to the MT.

The proposed mechanism is based on the decision process that uses MADM

algorithms jointly on the network side to assist the terminal to select the top

candidate networks. The research work describes the use of the compensatory

MADM algorithms. It identifies various factors, which influence the selection of an

optimal network and then inputs to the multi decision making based decision process

should be used. It explores different aspects of the problem and proposes a solution

on the MADM algorithms. This process is completed before compensatory MADM

algorithms, which can be used to rank the networks.

3.3.1 Decision Process in Network Selection

Figure 3.4 shows the decision making process in network selection. In the

network assisted mechanism, which is proposed in [129], the network assisted the

terminal in the selection process by performing data collection and analysis to

provide the ranking of the network.

The architecture proposes the use of three network based functional entities

i. Data Collection Node (DCN): It characteristics the retrieving network.

ii. Service Announcement Node (SAN): It provid ing the service related data.

iii. Authentication, authorization and accounting (AAA) node: It provides the

information with security.

These three nodes provide input data to a network based assessment entity that

calculates network ranking for selecting network by the MT. The terminal provides

its location and any other information that could be considered by the network

analysis like service request or QoS request.

The initial network access is similar to getting directory circuits switched

voice network. The initial network may not be the optimal network for the requested

service, but it can be changed once sufficient information has been collected to make

a decision.

Network S el ecti on reques t recei ved from the us er M T

Retri eve r el eva nt i nforma ti on from network en ti ti es for us e i n the deci si on -ma ki ng

The l i s t of ca ndi da te network us i ng compens a tory MADM a l gori thm wi th a ttri butes

li ke QoS rel a ted pa ra met ers

Provi de the ca ndi da te network rel a ted i nforma ti on to MT

Figure 3.4: Decision making process in network selection

In this research work, the decision process in network selection is formulated

in a HWN environment as an MADM problem that deals with the evaluation of a set

of alternatives using a set of attributes. The alternative represents different choices.

In [47], the decision process ranks the alternatives in order of preference

using the set of attributes that provide different aspects by which the alternatives can

be viewed.

Table 3.1 Category 1 attributes for network selection

The factors attribute impacting network selection can be divided into the

following categories

i. Category 1: The attributes include parameters that are not QoS-related.

These parameters do not change way often, but it can usually be

provisioned in the network.

ii. Category 2: It includes mostly QoS related attributes, both dynamic ones as

well as largely statics ones that can be provisioned.

Tables 3.1 lists the attributes that are taken into consideration for network

selection using the algorithm proposed in this work and classifies them into two

categories.

Table 3.1 Category 1 & 2 attributes in network selection

Category1 Attributes Brief Exp lan ation

Opera tor Na me

Auth enti ca ti on

Mecha nis m

Acces s technol ogy

Servi ces a vaila bl e

Geogra phi c l oca ti on

Thi s a ttri bute i ndi ca tes the i denti ty of th e opera tor for whi ch

the res t of the i nforma ti on is bei ng provi ded

Thi s a ttri bute i ndi ca tes the a uthen ti ca ti on

mecha ni s m us ed by the roa mi ng pa rtner. Exa mpl e: SI M or Us er

ID / Pass word

Thi s a ttri bute i ndica tes the wi rel ess a ccess technol ogy the

a ccess network

Thi s a ttri bute provi des a lis t of s upported s ervice [VoIP]

Thi s a ttri bute i nforma ti on on the g eogra phi c l oca ti on li ke ba s e

s ta ti on.

Covera ge a rea Thi s a ttri bute provi des a mea s ure of the covera ge a rea .

Category 2

Cos t per byte

Ba ndwi dth

Al l owed Ba ndwi dth

Uti li za ti on

Pa cket Ji tter

Pa cket Los s

Thi s a ttri bute i ndica tes rel a ti ve tra ns port cos t of the opera tor

for a particul a r a ccess

Thi s a ttri bute i ndi ca tes how much ba ndwi dth is a vail a bl e overall

on the wi rel ess access li nk

Thi s a ttri bute i ndica tes the ba ndwi dth a ll owed by th e AN on a

per us er bas is

Thi s a ttri bute gi ves the a vera ge pa cket del a y wi thi n the a ccess

s ys tem. Thi s i s not the End-to-End d el a y

Thi s a ttri bute mea s ure the a vera ge del a y va ria ti ons wi th the

a ccess s ys tem. A l a rge ji tter coul d res ul t i n pa cket reorderi ng or

droppi ng of real -ti me pa ckets a t recei ver.

Thi s a ttri bute mea s ures the a vera ge pa cket l oss ra te wi th the

3.3.2 Multi-Attribute Decision Making

In MADM problems, the alternative has performed for attributes as in table

3.1, which represents the characteristics of the alternatives [130], it is common to

transform performance ratings into a compatible measurement unit, and a

normalization procedure is used.

An MADM problem usually involves a set of m alternatives (i = 1,

2,

…, m), which are to be evaluated based on a set of n attributes (j = 1, 2, …, n). It

is assets to determine

i.

The weighting vector

ii. The decision matrix

The W represents the relative importance of n attributes

.

MADM algorithms involved into two processes for obtaining the overall

preference value for each alternative.

i. Normalization procedure

ii. Aggregation method

Normalization is first applied to transform performance rating to a

compatible unit scale, then aggregation algorithms is used to combine normaliz ed

decision matrix and attributes, weights W to achieve an overall preference value for

each alternative and is based on the overall ranking of the network alternatives. As

discussed in [130], the four well-known normalization procedures used in MADM

are briefly described below

i. Vector normalization

ii. Linear scale transformation (max- min)

iii. Linear scale transformation (max)

iv. Linear scale transformation (sum)

a) Vector Normalization

In this procedure, each performance rating of the decision matrix is divided

by its norm. The normalized value is obtained by

(3.1)

This procedure has an advantage of converting all attributes into dimensionless

measurement unit, thus making inter-attribute comparison easier. However, it has

the drawback of having non-equal scale length leading to difficulties in

straightforward comparison [28, 131].

b) Linear Scale Transformation (Max-Min)

This method considers both the maximum and minimum performance ratings

of attributes during calculation. For benefit attributes, the normalized value is

obtained by

(3.2)

For cost attributes, is computed as max

(3.3)

where is the maximum performance rating among alternatives for attribute (j =

1, 2, ..., n) and xj min is the minimum performance rating among alternatives for

attribute (j = 1, 2, ..., n). This procedure has the advantage that the scale

measurement is precisely between 0 and 1 for each attribute. The drawback is that

the scale transformation is not proportional to outcome [131].

c) Linear Scale Transformation

This method divides the performance ratings of each attribute by the

maximum performance rating for that attribute. For benefit attributes, the

normalized value is obtained by

For cost attributes, is computed as

(3.4) (3.5)

where xj is the maximum performance rating among alternatives for attribute (j =

1, 2, ..., n). Advantage of this procedure is that outcomes are transformed in a linear

way [28, 131].

d) Linear Scale Transformation (Sum)

This method divides the performance ratings of each attribute by the sum of

performance ratings for that attribute as follows

(3.6)

Where xj is performance rating for each alternative for attribute (j = 1,

2…, n) [131].

In order to obtain the overall preference value, the normalized decision

matrix generated by a normalization procedure needs to be aggregated by an MADM

algorithm.

In this research work, the MADM algorithm are used in different

normalization procedure to active compatibility between different measurement

units, in the aggregation algorithm like SAW, TOPSIS, WPM, GRA and AHP.

i. SAW and WPM algorithm uses linear scale transformation.

ii. TOPSIS use vector normalization procedure.

iii. AHP use linear scale transformation.

iv. GRA uses normal procedure.

MADM algorithms are conducted on the suitability of normalization procedure

used in the algorithms. Next to the normalization, the weights reflect the relevance

in the sense of being a measure of the gain associated with replacing the worst

outcome by best outcome for this criterion [132].

The simplest way of accessing weight is to arrange the attributes from high to

low attribute. When assigning one to high attribute and n to the low attributes, the

cardinal weights can be obtained from one of the following formula in literature.

Where

(3.7)

(3.8)

Where is the rank of the jt h attribute. But in this work, weight is calculate

by the priority vector weight using the AHP algorithm. The process of the

compensatory MADM algorithms is as discussed in the chapter 7.

Compensatory MAD M algorithms

This involves the following steps

Step 1: Identify all alternative and compensatory MADM attributes

influencing the decision process.

Step 2: Assign relative importance in the decision making process to each of

the attribute.

Step 3: Use a compensatory MADM algorithm to get a ranking of the

alternatives.

This work consider the x access network as the network selection network to

handover as shown in figure 3.4. In order, to apply a compensatory MADM

algorithm to facilitate network selection, consider the attributes in category 2 of table

3.2, the candidate network i, from a decision- making perspective can be

represented as follows

(3.9)

Equation 3.10, represent the n networks to be cons idered in the selection

process in the form of matrix as follows,

(3.10)

3.4 QOS PARAMETERS FOR NETWORK S ELECTION

QoS refers to the capability of a network to provide better service to select

network over the VoIP application and tec hnology like WiF i and WiMax, WLAN,

etc. QoS is the quality of a call over a network. It gives the priority types of traffic

on IP network. In VoIP, QoS prioritized the voice traffic at a higher level than the

other forms of traffic like data, thus the voice traffic will not be delayed or dropped.

As discussed in [23] the advancement in technology, voice communication over the

PSTN is characterized by high quality, offer referred to as toll quality. In VoIP, QoS

constraints must be met in order to provide the same level of quality. There is the

main performance indicator that characterizes the quality of voice communications

over the internet. They are delay, jitter, packet loss, also bandwidth and cost. This

bandwidth and cost are also taken in to t he account for choosing the best network.

Delay or Latency

The first delay can be defined as the total time it takes a person

communicating another person, mouth to ear delay. The VoIP application is

sensitive to delay although they can tolerate the packet loss to some extent.

There are five components that contribute to the mouth to ear delay [23]

i. Encoding Delay: The time interval needed to encode the voice signal,

which depends on the voice codec employed.

ii. Packet Delay: The interval that is required to packetsize the encoded voice

stream.

iii. Network Delay: It is the sum of transmission, propagation and queuing

delay.

iv. Playback Delay: The delay induced by the playback buffer that resides

at the receiver‟s side, which is needed to smooth delay jitter betwee n

consecutive packets.

v. Decoding Delay: The time interval needed to reconstruct the voice

signal.

Delay has two acute effects on voice performance. F irst, it increases the

subjective effects of any echo impairment. Second, when echo is controlled one-way

delay affects the character of the conversation. This research use packet delay for

the decision.

Jitter

Jitter is a variation in packet transmits delay caused by queuing, contention

and serialization effects on the path through the network. The usual causes include

connection timeout, connection time lags, data traffic congestion and interference

that is jitter an undesirable output of system flows and interruptions in [149].

(3.11)

Where,

IP network does not guarantee for packet delivery time, which introduced the

variation in transmission delay, it has more negative effects on voice quality [113].

Thus, the jitter is the result of network congestion and improper queuing. When a

packet is transfer at the sending side, vo ice packets are transmitted at a constant rate,

while, at the other end the packets be received at an uneven rate. S till the voice

packets of the same flow are not received at the same time. So jitter buffer is

introduced.

In VoIP implementation, the mechanism that is used to compensate for delay

jitter and smooth out the distribution of packet delay is the play-out buffer, also

referred to as jitter buffer. Jitter buffer is a shared data area, where voice packets can

be collected, stored and sent to the voice processor in evenly spaced intervals. It is

located at the receiving end of the voice connection, intentionally delays the arriving

packets so that the end user experiences a clear connection with little distortion of

sound. There are two types o f jitter buffer, static and dynamic jitter buffer. S tatic

jitter buffer is hardware based. Dynamic jitter buffer is software based and can be

configured by the network administrator, to adapt configured by the network ‟s delay.

So, in this work jitter is taken as a decision parameter, which is used to reduce the

handover processing delay from the result of improper queuing.

Packet loss

Packet loss will deteriorate voice quality because voice packets are highly

time sensitive. Lost packet recovery can be done by interpolating voice from the last

received packet to fill the place with the cost packet. It has consider that delivery

ratio of more than 99% is required for VoIP [131, 132, 111]. Packet losses can occur

due to many reasons. An IP packet may be lost due to congestion in the IP network.

An IP packet may also be discarded at the destination. For example, when a packet

arrives too late it will be played out. In addition to these reasons, the wireless

systems intense variations in the received s ignal power brought about by intense

fading conditions result in the loss of a significant number of packets too. Therefore,

packet loss is the total loss occurs to network congestion and late arrival [112]. In

case of packet loss, the sender is informed to retransmit the lost packets, which cause

more delay and affect the transmission of QoS.

Bandwidth

Bandwidth (B) is used an interchangeable with connection speed, although

technically they are not exactly the same. Bandwidth presents the capacity of the

connection. In wireless technology, B will have speed up to several Mbps. B, in

this research, it considered as the networks in overlay. So it is provided by the

network for both wireless networks in the range of 1 to 50 B. Here, the user is

running in a VoIP application, which needs the amount of B from 1 to 10.

Therefore, a MT may handover to target network, if the network offer at least 10 B.

Cost

Cost is used as one of the handover matrix value. Cost of service wants to be

low in the HWN. In this research work, Cost is C, which is assigned to calculate the

cost of possible target networks. The cost of each possible target network for the

service with the highest priority is calculated by as in the eq. 3.12.

(3.12)

where is the per-service cost for network n, is the normalized QoS

provided by network n for parameter p and service s. is the weight which

indicates the impact of the QoS parameter on the user or the network and is the

network elimination factor, indicating whether the minimum requirement of

parameter p for service s can be met by network n. The total cost is the sum of the

cost of each QoS parameter, including the bandwidth, jitter and delay. The service is

handed over to the network with the minimum cost.

Thus to achieve fast and seamless handover, the handover scheme are

introduced in this research work.

In this work, consider the MT is moving in an overlapping area covered by a

set of wireless networks and managed by the same network operators as in figure

3.5. Network can be divided into two categories viz (i) Home Network (HN) and (ii)

Target Visitor Network (TVN). HN represents the networks where MTs generate

their connection and TVN represents the target networks to which MT intend to

handover, the VoIP application is used as service application in MT, the user profile

is used as distributed among those TVNs. In this work, Delay (D), Jitter (J),

Bandwidth (B) and Cost (C) are the handover matrix o ffered for handover by a MT

and BS. The decision algorithm is used in the works are MADM cardinal a lgorithms

like S AW, TOPSIS, WP M, GRA and AHP. The following section discussed the

VHD schemes.

3.5 VERTICAL HANDOVER DECISION S CHEMES

The vertical hando ver decision schemes, which is use for reducing the

handover processing delay use DVHD and TDVHD schemes, both schemes

delegates the handover calculation to the VN rather than on the MT. The schemes

take into an account: D, J, B and C (in money) as evalua tion matrix to select a

suitable TVN from several VNs. The matrix are gathered as a MADM algorithm

[112] access selection function.

The schemes comprise the following addition to this work

i. The delegation of handover matrix calculation to the VNs.

ii. The addition of the evaluation parameter matrix is to calculate the handover

matrix.

iii. The delegation of the calculation task and implement the user profile among

the neighbour networks.

iv. The distributed decision task among networks are applied in order to

decrease the processing delay, when exchanging the voice message between

MT and neighbour networks (VNs).

v. To distribute the processing task, the VHD is formulated as MADM problem.

vi. The SAW, WPM, TOPSIS, GRA and AHP are offered in all the VHD

schemes.

3.5.1 Scenario of the Proposed Work

The proposed work use the IEEE 802.21 MIH services to assist the VHD

schemes to enhance the overall handover decision exchanging the voice message,

offered by the MIH function between the MT and the TVN. In order to model the

mobility environment, the following assumptions have been made. MT is moving in

an overlapping area covered by a set of enable MIH wireless networks and the same

network operator manages it.

i. The cellular network covers the entire mobility area, while wireless ne tworks

are networks provide limited coverage as in figure 3.5.

ii. Networks are divided into three categories

a. HN is the network in which the mobile node has initiates its connection.

b. VNs are the networks to which MTs intend to handover.

c. TVNs is the best network chosen by the MT using the VHD schemes.

In this work, technologies are the VNs and the user profiles are distributed

among the VNs.

iii. The HN provides relatively low data rates, where as WLAN and WMAN

supports higher data rates.

iv. MT runs with a VoIP application that requires an appropriate QoS level.

v. MT and network are MIH enabled.

The following section describes the VHD schemes in detail.

Figure 3.5: Scenario of network selection in vertical handover

3.5.2 Centralized Vertical Handove r De cision (CVHD) Sche mes

In this C VHD scheme, a MT exchanges the message between the MT and the

neighbour networks. When exchange is done with major effects has processed at

MT and it increases the processing delay. When processing delay had increased

overall handover delay will increase. To avoid this causes by the CVHD, DVHD

schemes were proposed in (48, 115).

3.5.3 Distributed Vertical Handover Decision (DVHD) Sche mes

Centralizing the VHD process at the MT has a major effect. It increase the

processing delay caused by exchanging information message between the MT and

the neighbour networks. Increasing the processing delay will increase the overall

handover delay. The goal is to decrease the processing delay by decreasing the time

to exchange the mes sage in packets between the MT and the neighbour networks.

Thus, DVHD delegates the handover calculation to the TVN rather than on the MT.

Use IEEE 802.21 MIH services to assist MTs to communicate their requirements to

all VNs and implement a table representing the user profile table 3.2 among these

TVNs.

In this work, DVHD takes into an account: D, J, B, C as evaluation matrix to

select a suitable TVN. This matrix is gathered as a MADM access selection

function.

Table 3.2: User Profile

Class J WJ D WD C WC B WB

1 J1 WJ1 D1 WD1 C1 WC1 B1 WB1

2 J2 WJ2 D2 WD2 C2 WC2 B2 WB2

3 J3 WJ3 D3 WD3 C3 WC3 B3 WB3

Distributed Network Selection Algorithm

a) Network Selection Function (NSF)

The network selection decision problem is formulated as a MADM problem,

which is an evaluation of a set of alternatives (networks) with different attributes

using a multiple attribute NSF. NSF consists of a set of evaluation parameters as D,

J, B and C. This function provides a measure of the VNs Network Quality Value

(NQV) i.e., a measure of the target-handover network quality. Thus, the

decision algorithm can select the “best network” that has the highest quality value.

The function is defined as follows

(3.13)

Where D is the Delay, J is the Jitter, B is the Bandwidth and C is the cost of

the service. Evaluation parameters are the user required parameters and the

parameters offered by the network. Therefore, the function used in this work as

depicted by eq. 3.14 as the generic weighted NSF

(3.14)

Where represents the quality of the it h TVN, represents the benefit

parameters i.e., D, J, B. While represents the negative benefit parameters i.e., C.

and are the weights indicating the importance of the parameters and

.N is the number of TVNs, while and are the number of the benefit and

negative benefit parameters. Based on the user‟s service profile the HN assigns

different “weights” to the handover decision parameters in order to determine the

parameter‟s levels of importance ie., user preference. The sum of these weights must

be equal to one as shown in eq. 3.15.

(3.15)

As stated before, evaluation parameters for the decision process used to

evaluate NSF as shown in eq. 3.16.

(3.16)

b) Distributed Decision Scheme

The DVHD scheme is based on the MADM algorithm, which is applied in a

distributed manner. Thus, it places the computing processing among TVN than on

the MT. DVHD allows the MT to choose the “best” TVN towards which it will

connect.

In this research work, MADM algorithms apply the NSF on the quality

parameters of each TVN by using the matrix 3.16, which cont ain the quality

parameters of each TVN. In order to distribute the computing task, the matrix

consists offered and required (Joff, Doff, Coff, Breq) and (Jreq, Dreq, Creq, Breq) i.e., user

requirements are retrieved from the user profile. Thus each TVN computes its NQV

and sends it to the MT.

(3.17)

The weights of the decision parameters are gathered as ( in the

eq. 3.18.

(3.18)

After scaling the matrix element, the matrix in eq. 3.19 is weighted and the

NQV is calculated.

(3.19)

The MT communicates with HWN‟s TVN, it needs to exchange

homogeneous messages with these TVNs. Thus, use a subset of primitives offered

by the MIH function. Next, it defines Information Elements known as evaluation

request and NQV response.

Table 3.3: Information Ele ments

Type

Length

Value

User profile

Variable

MT_ID

Required Parameters

Parameter Weights

PoA_NQV

Variable

PoA_ID

NQV

In order to exchange the information between the MT and the VNs shows in

table 3.3. Using the evaluation request message, it sends its requirements to the

TVNs and by using the NQV response message, each VN sends its NQV to the MT.

Each service provided by the MIH function has its service flow model as

shown in the figure 3.6. It presents a generic flow model for all remote request /

reply primitives used in this research work.

The DVHD scheme steps are as follows

Step 1: Once the MT identifies the handover process that is potential VNs for

handover, by the degradation of the offered quality or the availability

of TVNs offering better quality than the quality offered by the

network to which the MT is connected.

Step 2: It broadcasts a handover request message to all the available TVN this

message includes the MT required handover matrix with their

respective weights.

Step 3: The handover decision metric calculation is performed on the VNs,

each VN applied the MADM algorithm using on the required (Dreq,

Jreq, Breq, Creq,) and offered (Doff, Joff, Boff., Coff) parameters as in

eq.3.20.

(3.20)

Step 4: The MT chooses the higher quality value and then recommended the

wireless network with highest metric as a potential by the MT,

triggers the handover.

MT

Ha ndover reques t

Is VNs

a vaila bl e?

Broa dca s t ha ndover pa ra meter

by s endi ng requiremen ts of MT

Remote Tra ns port

(reques t fra me)

Recei ve a ll VNs NQVs a nd

compa re the NQVS

Pi ck up the hi ghes t NQV

offeri ng VN a s TVN

Remote Tra ns port

(res pons e fra me)

MAD M a ppli ed to cal

cula te NQV vi si tor

networks a ccess

Is ma tched

requi red

pa ra meter?

Send RQ to new BS for regi s ter

Ha ndover compl eted

Figure 3.6: Distributed Vertical Handove r Decision Sche me

3.5.4 Trusted Distributed Vertical Handover Decision (TDVHD) Sche mes

TDVHD scheme is proposed for distributing the decision task among

network in order to decrease the processing delay caused by exchanging information

message between MT and VNs in trus ted manner. In order to distribute the

processing task, the vertical handover decision is formulated as MADM problem.

Neighbour network are managed by different wireless networks delegating the

calculation task among these networks risks that the informat ion received by the MT

to make the decision may be falsified, for example the information representing the

network quality doesn‟t reflect the real network ‟s condition. Receiving falsified

information may cause multiple handover events, which may increase the processing

delay. Thus, the trust relationship is established in such environment to create a

major challenge.

In this regard, exchanging trust information between networks and MT is an

important factor, which guarantees a trusted handover decision a nd avoids the

unnecessary handover events. For that, in [45] propose an extension of the DVHD

scheme, the TDVHD scheme.

Distributing the VHD process provides benefits in term of processing delay,

as the computing task is performed at the TVNs a trust problem occurs. TVNs may

be falsified e.g. economic reason, their NQV may se nd qua lity va lue that doesn‟t

reflect its real condition, which impacts the handover delay. Receiving falsified

NQV from a TVN, as the decision is based on NQVs, may affect the MT d ecision.

So, if the MT chooses a TVN that doesn‟t meet its requirements, it may be obliged to

initiate another handover process. Thus, multiple handover events may occur, which

increase the vertical handover delay.

In order to avoid multiple handover e vents this research work describe, the

TDVHD scheme, this guarantees a trusted handover decision, by offering a

knowledge leve l about the MT‟s mobility environment. TDVHD affects a Level of

Trust (LoT) parameter for each available TVN; the value of this parameter is updated

using a Trust-test function. Thus, when the MT chooses the VN, and before

achieving the handover execution phase, it compares the LoT value of the chosen

network with a predefined threshold, the threshold value depends of the running

application VoIP. If the test is positive then the MT redirects its connection to the

chosen VN and initiates a Trust-test function used to accommodate the MT

knowledge. If the test is negative, the MT picks up another available TVN and

executes the Trust-test function for the network.

T-DVHD Scheme

As illustrated in figure 3.8 the MT sends its User-Profile reference to each

TVN, which in turn retrieves the MT requirements from the User Profile table 3.2

and applies the MADM decision algorithm to compute the NQV. Each TVN sends

its NQV to the MT, which groups them in a list. Then, it picks up the highest NQV

from the list and before connecting to the appropriate TVN it initiates the Trust

process.

LoT-test function

The LoT-test function is initiated after that the MT receives all NQVs from

the different TVNs and build its NQVs list. Its goal is to test whether the chosen

TVN is a trusted network or not. A LoT table 3.4 is placed at the MT side, in table

3.5, it contains the TVNs identities associated with LoT values, which are updated

by the Trust-test function in figure 3.8.

Table 3.4: Level of Trust Table

Network Reference

LoT

Network-1

L1

Network-2

L2

…

…

Network-n

Ln

Therefore, before the MT switches to the chosen TVN, the LoT-test function

is initiated and the algorithm in figure 3.7 is applied on the LoT of the appropriate

TVN (corresponding to the highest NQV). The LoT value corresponding to the

chosen TVN is retrieved from the LoT-table and is compared to a predefined

threshold, the threshold value depends on the running application e.g. if the

application is delay sensitive, the threshold value must be high, in order to avoid

multiple handover events.

If the LoT-value is greater or equal to the threshold, then the MT switches to

the VN and initiates the Trust-test function. If not, if another TVN is available, its

LoT value is retrieved from the LoT-table and the LoT-test is applied on this value.

Finally, if no more NQV in the list or the maximum handover delay is exceeded, the

hando ver is blocked.

Algorithm : LoT - Test fun ction

Step 1: If Lo Ti >= thres hol d

Step 2: Connect to th e TVNi

Step 3: Ini tia te Trus t-tes t functi on

Step 4: else if Lo Ti < thres hol d {

Step 5: if (s ui ta bl e-TVN a va il a bl e)

Figure 3.7: LoT-test Function

Trust-test function

The Trust-test function is initiated once the MT connects to the VN. The MT

executes this function in order to accommodate knowledge about the neighbour

TVNs. This is done by upda ting the LoT table using the algorithm illustrated in

figure 3.7.

Algorithm : Trust – Test Fun ction

Step 1: If Qoff < Qreq

Step 2: LoTi = LoTi – (de lta)-;

Step 3: els e

Step 4: LoTi = Lo Ti + (del ta )+;

Figure 3.8: Trust-test Function

As presented in figure 3.8, the test compares the Quality offered (Qoff) by the

VN with the Quality required (Qreq) by the MT. In case Qoff < Qreq for e.g. if a

remarkable quality degradation appears after connecting to the VN, the LoT value is

decreased by delta value . However, in this work, delta value is taken

as difference of network requirement value and NQV. Else Qoff >= Qreq the LoT

value of the considered VN is increased by . Where nr is the network

requirement QoS parameters and the nq represents the NQV, which is used to

calculate the running application by the MT. The delta is calculating the time

between the arriva ls of voice packets. Therefore, in TDVHD scheme network

requirement are (Jreq, Dreq, Creq, Breq), these parameters are the QoS for VoIP, which

calculates the best network by calculating these parameter sends different voice

packet from source to destination. Likewise, network quality vector calculate the

matrix of offered and required decision parameters and the weight of the required

decision parameters to calculate the delta value. By calculating this delta value for

VoIP, it can find the trusted network to handover, which reduces the handover

processing delay.

3.6 PER FORMANCE EVALUATION PARAMETERS FOR VHD

SCHEMES

VHD algorithms can be quantitatively compared under various usage

scenarios by measuring the mean and maximum handover delays, handover even ts,

end-to-end delay, P DR, packet loss incorrect decisions, and the overall throughput of

a session maintained over a typical mobility pattern. These metrics are further

explained below

3.6.1 Handover Events

In wireless networks, a call during its lifetime can be represented by a

sequence of events, where N denotes the events that a new call is admitted, Hn

denotes the event of a mobile user nt h handover, S denotes the event of the call

sojourning in the same call and E denotes the call termination events. Note that in

some cases, there are no handover events during the life time of a cell and thus no Hn

in the sequence of events like (N, H, H1, Hn ,..., Hn, S,…, E).

In this work, multiple handover events occur when the MT chooses un-

trusted TVN that provides falsified quality value (i.e. NQV). In this case, another

handover event may be performed as the switched VN doe sn‟t provide the

appropriate quality, which adds additional delay to the handover process. Handover

Events parameter reflects the number of handover achieved by the MT. Multiple

handover events may occur, which increase the vertical handover delay.

3.6.2 Decision Delay

Decision delay is a process, which takes time by the MT for making the decisio n

towards the network to handover i.e. when a MT starts the searching of the network

to handover by sending the request to the available networks and finding the a TVN

to handover the MT. The time calculation of MT handover to the particular TVN

was Decision Delay.

3.6.3 End-to-End Delay

End-to-End delay refers the time taken for a packet to be transmitted across a

network from source to destination. It represents the average data delay for an

application or a user experiences when transmitting data. The delay is usually

measured in seconds.

Average end-to-end delay = (3.21)

Where, Packet_Delay=

The delay for a packet is the time taken for it to reach the destination and the

average delay is calculated by taking the average of delays for every data packet

transmitted. The parameter comes into play only when the data transmission has

been successful.

3.6.4 PDR

Packet Delivery Ratio (PDR) defined as the number of received data packets

divided by the number of generated data packets i.e. it indicates the percentage of the

transmitted data packets that are successfully received. It is an important matrix

which can be used as an indicator to a packed network. The P DR is only considered

for data packets. The total number of transmitted packets is counted, followed by t he

total number of received packets and the total number of dropped packets. The PDR

is calculated as the packets received to the packets transmitted. The number of

packets dropped does not take into account retransmissions. As an example, if a data

packet with an ID: 4 is transmitted and has been dropped for the first time. The

packet is retransmitted, as long as we have a successful transmission or the

maximum number of retransmissions has been reached. But the drops due to

retransmission is not take n into account and are only counted when the packet is

ultimately dropped, and even in those cases its counted as a single drop.

PDR =

(3.22) However, if the packet is successfully received by the destination

after

several retransmissio ns, the drops are not considered. This would effectively make

the number of transmitted packets equal to the sum of the number of received

packets and number of dropped packets.

3.6.5 Throughput

Throughput is the average rate of successful message deliver over a

communication channel. These data may be delivered over a physical or logical link

or pass through a certain network in MT. Throughput is usually measured in bits per

second (bit/s or bps) and sometimes in data packets per second or data packets per

time slot as shown in eq. 3.23.

Throughput = (3.23) where,

time is in seconds. It is a measure of the amount of data transmitted from the source

to the destination in a unit period (in second). For example, considering the

low data rates and throughputs supported by the technology, the throughput is

measured in total bits received per second. In addition, to be noted is that this metric

only measures the total data throughput ignoring all other overhead over the

network. The throughp ut of a MT is measured by first counting the total number of

data packets successfully received at the MT and computing the number of bits

received, which is finally divided by the total simulation runtime. The throughput of

the network is finally defined as the average of the throughput of all MTs involved in

data transmission.

3.6.6 Packet Loss

Merely comparing the time consumed by the vertical handover is not enough.

During the vertical handover process an important to compare the amount of packets

that are dropped. This packet loss is described by eq. (3.24)

(3.24)

Notice that packet loss should be calculated solely for the vertical handover period.

3.7 SIMULATION MODEL

The simulation in this work was done in NS2. It is modified from REAL

network simulator and developed through VINT project at UC -Berkeley. NS2 is a

discrete-event driven and object-oriented network simulator. Types of simulation

are continuous, discrete events and combined.

In this research work, the simulation co nsiders MT, which is moving in an

area covered by the heterogeneous wireless networks managed by BS and APs. The

access point covered mobility area and it is supporting the technologies like WiMax,

WiF i etc. These AP and BS are offered different characte ristic in terms of coverage

and QoS [D, J, B, C]. VoIP is used as application in this simulation.

Table 3.5: Simulation matrix

Topography 200 * 200

Mobile Node

Base Station

Access points

Routing Protocol

Packet S ize

Simulation time

Wireless Standards

20 nodes 2 4 DODV 500 kb 500 (s) 802.16,802.11

3.8 SUMMARY

In this chapter, the method and materials for this research work are discussed.

This chapter discussed about the vertical handover decision schemes, parameters

used to select the VN as TVN for handover by the MT and evaluation parameters

used to minimize the processing delay when handover done by the MT. The

following chapters show the MADM algorithm for selecting the network, which are

applied to the VHD schemes and conclude the best VHD schemes.

CHAPTER 4

APPLICATION OF S AW AND WPM FOR NETWORK SELECTION IN

VERTICAL HANDOVER

4.1 OVERVIEW

SAW and WPM algorithm are the most popular algorithms of classical

MADM. The S AW and WPM algorithms are the additive and multiplicative

weighting approaches in MADM [28]. These algorithms allow compensations

between partial values, whereas the normalization of values facilitates balancing and

different original scales inhibit trade-offs. Determining weights and identifying

traditional values is difficult when combining the value functions in additive or

multiplicative. The advantages of both approaches are the simplicity of their scoring

algorithms. According to these additive and multiplicative approaches network

ranking are evaluated in this chapter.

The rest of this chapter is designed as follows. An overview of simple

additive weighting and weighted product method in 4.2 and 4.3, section 4.2.1 and

4.3.1 discussed how these algorithms are applied to VHD schemes for selecting the

best network to handover. Section 4.2.4 and 4.3.3 evaluated the result of this usage

of algorithm in VHD schemes using the evaluation parameters to reduce the

handover processing delay between the MT and TVN to handover.

4.2 SIMPLE ADDITIVE WEIGHTING (SAW) ALGORITHM

SAW, which is also referred as a weighted linear combination or scoring

method or weighted sum method, it is a simple and most commonly used MADM

algorithm [132], [28]. It is based on the weighted average. The basic logic of this

algorithm can obtain a weighted sum of the performance rating of each alternative

over all attributes. An evaluation score is calculated for each alternative by

multiplying the scaled value, which is given to the alternative, the attribute with the

weights of relative importance directly assigned by the decision maker followed by

the sum of products for all criteria.

The application of SAW requires the identification of objectives and

alternatives, evaluation of alternatives, determination of sub-objective weights,

additive aggregation of weighted partial preference value and sensitive analysis. It