18-03-2014, 04:32 PM
Comparison between Vertical Handoff Decision Algorithms for Heterogeneous Wireless Networks
[attachment=60206]
Abstract
The next generation wireless networks will support
the vertical handoff mechanism in which users can maintain the
connections when they switch from one network to another (e.g.,
from IEEE 802.11b to CDMA 1xRTT network, and vice versa).
Although various vertical handoff decision algorithms have been
proposed in the literature recently, there is a lack of perfor-
mance comparisons between different schemes. In this paper, we
compare the performance between four vertical handoff decision
algorithms, namely, MEW (Multiplicative Exponent Weighting),
SAW (Simple Additive Weighting), TOPSIS (Technique for Order
Preference by Similarity to Ideal Solution), and GRA (Grey Re-
lational Analysis). All four algorithms allow different attributes
(e.g., bandwidth, delay, packet loss rate, cost) to be included for
vertical handoff decision. Results show that MEW, SAW, and
TOPSIS provide similar performance to all four traffic classes.
GRA provides a slightly higher bandwidth and lower delay for
interactive and background traffic classes.
INTRODUCTION
Currently, there are various wireless access networks de-
ployed. Examples include wireless cellular networks, WLANs
(Wireless Local Area Networks), and wireless PANs (Personal
Area Networks). There is an emerging trend that some of the
mobile devices are equipped with multiple network interface
cards, which are capable of connecting to different wireless
access networks. Users with multimedia-enabled wireless de-
vices are expected to obtain both real-time services (e.g.,
voice, video conferencing), and non-real time services (e.g.,
Simple Message Service (SMS), Multimedia Message Service
(MMS))
BACKGROUND AND R ELATED W ORK
Both QoS parameters and handoff metrics are required
for vertical handoff decision [5]. The QoS parameters (e.g.,
bandwidth, delay bound) are specified by the applications. The
information of different handoff metrics are gathered during
the system discovery phase. Fig. 1 shows various handoff
metrics and traffic classes (e.g., conversational, streaming,
interactive, background). The handoff metrics and QoS para-
meters are categorized under different groups (e.g., bandwidth,
latency, power, price, security, reliability, availability).
Various vertical handoff decision mechanisms have been
proposed recently. In [7], the handoff decision mechanism
is formulated as an optimization problem. Each candidate
network is associated with a cost function. The decision is to
select the network which has the lowest cost value. The cost
function depends on a number of criteria, including the band-
width, delay and power requirement. Appropriate weight factor
is assigned to each criterion to account for its importance. In
[8], an Active Application Oriented (AOO) vertical handoff
decision mechanism is proposed. The decision mechanism
considers the QoS parameters required for the applications
(e.g., minimum and maximum bandwidth requirement for
voice service).
CONCLUSIONS
In this paper, we presented the results for the performance
comparison between four different vertical handoff decision
algorithms, namely: namely, MEW (Multiplicative Exponent
Weighting), SAW (Simple Additive Weighting) [9], TOPSIS
(Technique for Order Preference by Similarity to Ideal So-
lution) [9], and GRA (Grey Relational Analysis) [10]. The
attributes that we considered in the simulation model included
bandwidth, delay, jitter, and BER. Results show that MEW,
SAW, and TOPSIS provide similar performance to all four
traffic classes. GRA provides a slightly higher bandwidth and
lower delay for interactive and background traffic classes.
[attachment=60206]
Abstract
The next generation wireless networks will support
the vertical handoff mechanism in which users can maintain the
connections when they switch from one network to another (e.g.,
from IEEE 802.11b to CDMA 1xRTT network, and vice versa).
Although various vertical handoff decision algorithms have been
proposed in the literature recently, there is a lack of perfor-
mance comparisons between different schemes. In this paper, we
compare the performance between four vertical handoff decision
algorithms, namely, MEW (Multiplicative Exponent Weighting),
SAW (Simple Additive Weighting), TOPSIS (Technique for Order
Preference by Similarity to Ideal Solution), and GRA (Grey Re-
lational Analysis). All four algorithms allow different attributes
(e.g., bandwidth, delay, packet loss rate, cost) to be included for
vertical handoff decision. Results show that MEW, SAW, and
TOPSIS provide similar performance to all four traffic classes.
GRA provides a slightly higher bandwidth and lower delay for
interactive and background traffic classes.
INTRODUCTION
Currently, there are various wireless access networks de-
ployed. Examples include wireless cellular networks, WLANs
(Wireless Local Area Networks), and wireless PANs (Personal
Area Networks). There is an emerging trend that some of the
mobile devices are equipped with multiple network interface
cards, which are capable of connecting to different wireless
access networks. Users with multimedia-enabled wireless de-
vices are expected to obtain both real-time services (e.g.,
voice, video conferencing), and non-real time services (e.g.,
Simple Message Service (SMS), Multimedia Message Service
(MMS))
BACKGROUND AND R ELATED W ORK
Both QoS parameters and handoff metrics are required
for vertical handoff decision [5]. The QoS parameters (e.g.,
bandwidth, delay bound) are specified by the applications. The
information of different handoff metrics are gathered during
the system discovery phase. Fig. 1 shows various handoff
metrics and traffic classes (e.g., conversational, streaming,
interactive, background). The handoff metrics and QoS para-
meters are categorized under different groups (e.g., bandwidth,
latency, power, price, security, reliability, availability).
Various vertical handoff decision mechanisms have been
proposed recently. In [7], the handoff decision mechanism
is formulated as an optimization problem. Each candidate
network is associated with a cost function. The decision is to
select the network which has the lowest cost value. The cost
function depends on a number of criteria, including the band-
width, delay and power requirement. Appropriate weight factor
is assigned to each criterion to account for its importance. In
[8], an Active Application Oriented (AOO) vertical handoff
decision mechanism is proposed. The decision mechanism
considers the QoS parameters required for the applications
(e.g., minimum and maximum bandwidth requirement for
voice service).
CONCLUSIONS
In this paper, we presented the results for the performance
comparison between four different vertical handoff decision
algorithms, namely: namely, MEW (Multiplicative Exponent
Weighting), SAW (Simple Additive Weighting) [9], TOPSIS
(Technique for Order Preference by Similarity to Ideal So-
lution) [9], and GRA (Grey Relational Analysis) [10]. The
attributes that we considered in the simulation model included
bandwidth, delay, jitter, and BER. Results show that MEW,
SAW, and TOPSIS provide similar performance to all four
traffic classes. GRA provides a slightly higher bandwidth and
lower delay for interactive and background traffic classes.