Optimal Channel Allocation Algorithm with Efficient Bandwidth Reservation for Cellular Networks

Abstract

As the growth of mobile users increasing in the present scenario and because of limited bandwidth available, there is a need to efficiently use the bandwidth available. The quality of service can be maximized by efficient bandwidth reservation. In this paper, the cross layer based bandwidth reservation scheme is proposed which initially reserves some amount of bandwidth for handoff flows. After that the bandwidth can be increased for handoff flows by the base station based on the user mobility. The user may not only go straight but also left, right and backwards. This paper considers all possibilities of user movements and bandwidth is reserved accordingly. Therefore making the base stations to dynamically increase the reserved bandwidth for handoffs when the initially reserved bandwidth is insufficient reduces the end to end delay and increases the throughput of the system. The proposed system performance is compared with the legacy systems and is shown to be better.

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International Journal of Computer Applications (0975 – 8887)
Volume 25– No.5, July 2011
40
Optimal Channel Allocation Algorithm with Efficient
Bandwidth Reservation for Cellular Networks
K. Madhavi
Asst. Professor
JNTUA College of Engg
Anantapur, AP, India
K. Sandhya Rani
Professor
Dept. of Computer Science
SPMVV, Tirupathi, AP, India
P. Chandrasekhar Reddy
Professor
JNTUH College of Engg,
Hyderabad, India
ABSTRACT
As the growth of mobile users increasing in the present scenario
and because of limited bandwidth available, there is a need to
efficiently use the bandwidth available. The quality of service
can be maximized by efficient bandwidth reservation. In this
paper, the cross layer based bandwidth reservation scheme is
proposed which initially reserves some amount of bandwidth for
handoff flows. After that the bandwidth can be increased for
handoff flows by the base station based on the user mobility.
The user may not only go straight but also left, right and
backwards. This paper considers all possibilities of user
movements and bandwidth is reserved accordingly. Therefore
making the base stations to dynamically increase the reserved
bandwidth for handoffs when the initially reserved bandwidth is
insufficient reduces the end to end delay and increases the
throughput of the system. The proposed system performance is
compared with the legacy systems and is shown to be better.
General Terms
Mobile Computing, Cellular Networks, Bandwidth etc
Keywords
Hand offs, Channel allocation, QoS etc.
1. INTRODUCTION
In cellular wireless networks, the challenges are increasing more
and more as there are encroachments in the technology.
Optimization leads to many more challenges to dig out more
from the scientific growth [11].
The enormous growth of mobile users in the present scenario
with limited bandwidth is a challenging task today. The
bandwidth should be utilized in an optimal way so that more
number of users may be serviced. One of the important factors
to improve the quality of cellular service is to make handoffs
nearly invisible to the user and successful [5]. Unsuccessful
handoff requests are one of the main causes of end to end delay.
In spite of the last several years of research on wireless ad-hoc
networks, massive real-life deployments of ad-hoc networks still
remain a challenge. Although the freedom of ad-hoc networks
from utilizing fixed infrastructure for offering wireless
communication services makes them attractive for fast
deployment in application domains such as the military and
emergency services, they are limited by their ability to
efficiently offer global accessibility and web-based services
such as file sharing, messenger services and voice-over-IP [12].
Nodes of traditional cellular wireless networks are maintained
by a base station manager (BSM) or server for routing. On the
other hand, nodes of purely ad-hoc networks behave as routers
by relaying messages in order to improve the performance of the
network. One of the most important issues in providing
ubiquitous communication is mobility management [13], which
primarily concern effectively tracking the locations of the nodes.
In case of hybrid networks, BSM can be used for effective
mobility management, which can be otherwise more challenging
in ad-hoc networks, because of their lack in using a dedicated
router/server having a network-wide knowledge of the location
of the nodes. In the case of pure cellular wireless networks, the
goal of adaptive call admission control is to ensure that there is
sufficient bandwidth reservation for handoff, i.e., for
transferring an ongoing call in a cell to another. The reserved
bandwidth in a target cell is proportional to the traffic intensity
in the surrounding cells [3]. In the absence of sufficient
bandwidth for handoff, new connections are subject to getting
dropped. One common approach used to reduce the connection
dropping rate (CDR) is to reserve some bandwidth solely for
handoff use [4]. [1]
In a cellular network, a mobile user may visit different cells in
his lifetime. In each of these cells, resources must be made
available to support the mobile user else the user will suffer a
forced termination of his call in progress. Therefore, careful
resource allocation along with call admission control is required
to mitigate the chances of forced termination or dropping of a
call. Keeping the probability of a user getting dropped (Pdrop)
below a pre-specified target value is considered as a practical
design goal of any resource allocation scheme. Achieving the
above goal provides the probablistic quality of service (QoS)
guarantee as desired by a mobile user. [9]
Early work in handoff prioritization proposes the static
reservation of bandwidth at each BS as a solution [14], in which
a fixed portion of the radio capacity is permanently reserved for
handoffs. However, such a static approach is unable to handle
variable traffic load and mobility [15]. [10]
2. BACKGROUND
Bandwidth reservation is an important issue to improve the
performance of cellular networks. There are proposals for
bandwidth reservation for both cellular networks and ad-hoc
networks, where we present some of the relevant pieces of work.
In the case of pure cellular wireless networks, the goal of
adaptive call admission control is to ensure that there is
sufficient bandwidth reservation for handoff, i.e., for
transferring an ongoing call in a cell to another. The reserved
bandwidth in a target cell is proportional to the traffic intensity
in the surrounding cells [3]. In the absence of sufficient

International Journal of Computer Applications (0975 – 8887)
Volume 25– No.5, July 2011
41
bandwidth for handoff, new connections are subject to getting
dropped. One common approach used to reduce the connection
dropping rate (CDR) is to reserve some bandwidth solely for
handoff use [4].
A cross-layer-based QoS model is proposed in [6] to categorize
various flows for service differentiation as well as reservation.
The primary focus of this work is to reserve the bandwidth for
real-time and non-real-time (best effort) flows. The proposed
architecture in [1] aims to provide CLIASM [6] to the network
layer and to its lower and higher layers. The network layer
collects the information from the application layer and forms the
ad-hoc network. The ad-hoc network is further classified into
hierarchical regions based on mobility, and then these regions
are mapped to the BSM of a cellular network.
An efficient Hash Table-Based Node Identification (HTNI)
Method using which bandwidth for various flows can be
reserved is proposed in [1]. Bandwidth reservation depends on
the type of the traffic and its priorities. Bandwidth reservation
factor is defined for use in hybrid network environments. A
cross-layer-based architecture for bandwidth reservation is
proposed to maintain Quality-of-Service (QoS). A priority re-
allocation method for flows which starve for long time is done
in [1].
An algorithm for channel allocation is proposed in [2] which
uses the system model where channels are reserved for
originating calls, handoff calls separately and some channels are
left free which can be used by both originating and handoff
calls. The system is modeled using Markov model. The channel
allocation procedure is done based on distributed dynamic
allocation procedure. Reusability concept is used and the
channels are divided into different groups. The groups are
allocated to BS’s based on mutual exclusion paradigm. The QoS
parameters like blocking probability and dropping probability is
examined.
3. SYSTEM MODEL
In the Bandwidth reservation based on user mobility scheme, we
assume that base stations are equipped with road-map
information and that mobile stations are equipped with global
positioning systems (GPS) devices. Mobile stations periodically
report their GPS location information to their base stations.
Based on the location information of the mobile stations at two
consecutive epochs, the base stations estimate the speed and
moving direction of the mobile stations. Furthermore, the base
stations estimate the probability that the mobile stations will
enter the neighboring cells based on their velocity and the road-
map information stored in the base stations. The base stations
then compute the amount of bandwidth to be reserved, based on
such estimation. With the road-map information, the base
stations can make a more-accurate prediction on the user’s
mobility and, hence, reduce unnecessary bandwidth reservation.
The structure of the cellular network estimated is shown in Fig.
1.
Indicates road
MH Mobile Host
Fig.1: Structure of Cellular Network
Mobile user’s motion pattern is mostly restricted by man-made
constructions, such as roads. Obviously, mobile users who are
making handoff requests are in motion; most are either walking
or riding in automobiles on the roads. That is to say, mobility is
always restricted by the layout of the roads. A mobile user’s
mobility is restricted in the sense that mobile users can only
move on the roads. We propose a new mobility prediction and
bandwidth-reservation method called “bandwidth reservation
based on user mobility”. This scheme makes use of a mobile
user’s moving speed, direction, and the road information stored
in the base stations to predict the handoff probabilities to
neighboring cells. The amount of reserved bandwidth is
dynamically adjusted according to the handoff probability and
the traffic load in each cell.
3.1 Measuring Traffic Intensity to Know
How Many Channels to Reserve at Each Base
Station
The intensity of the traffic varies during the day. It is normally
high in morning business hours and less in afternoon during
lunchtime and again goes high in evening. The traffic in busiest
periods are called busy-hour traffic. The intensity of the busy-
hour traffic again varies also depending on the day of the week.
During weekends traffic in morning time may be less and
evening time will be high. The network operator needs to meet
the demands of the average busy-hour traffic.
Traffic intensity can be measured using two dimensionless units
1.) Erlang
2.) Circuit Centum Seconds (CCS)
One Erlang is equivalent to number of calls (made in one hour)
multiplied by the duration of these calls (in hours). Each call has
a different duration or a different call holding time: for traffic
intensity measurements the average call holding time is taken
into account[7][8]. The typical values for average call holding
time vary between 120 and 180 seconds. Therefore, the traffic
intensity in Erlangs can be defined as:
MH3
MH4
MH1
MH5
MH
2
.
.
.
.
.
.

International Journal of Computer Applications (0975 – 8887)
Volume 25– No.5, July 2011
42
T (inErlangs) = Number of call in an hour * average call
holding time in sec / 3600 (1)
If a call attempt is made when all channels in cellular networks
are serving other calls, the call attempt will be blocked. The
probability of call blocking in a telecommunication network is
call Grade of Service (GoS). The Grade of Service of a
telecommunication network varies between zero and one. A
GoS of 0.02 is normally taken as acceptable for communication
systems.
3.2 Estimating the Number of Subscribers in
the Cellular System
The number of subscribers in the system can be estimated
assuming the relation between the number of subscribers in the
busy hour (n) and the number of calls per hour per cell. The
maximum number of calls per hour that a cell can take depends
on the number of channels allocated for that cell based on traffic
conditions under its geographic area. The estimated number of
subscribers in the system M is
M = ∑ maximum number of calls per cell / n (2)
In this paper, we consider the flows to be as originating and
handoff flows. The originating flows are the flows which
originated in a particular cell and the handoff flows are
generated when a mobile user moves from one cell location to
another. The cross layer architecture proposed in [6] is been
used for bandwidth reservation scheme proposed in this paper.
We also use the architecture proposed in [1]. In this architecture,
the call admission control estimates the available bandwidth and
reserves the same for handoff flows. In this paper, we propose
the bandwidth reservation scheme which reserves some amount
of bandwidth for handoff flows and some amount of bandwidth
for originating flows and keeps some amount of bandwidth
which can be used by both handoff flows and originating flows
[2].
Fig. 2 System Model
The proposed system model is shown in Fig. 2. In Fig. 2, BW
O
represents the bandwidth reserved for originating flows, BW
C
represents the bandwidth which can be utilized by both
originating and handoff flows and BW
H
represents the
bandwidth which can be utilized by only handoff flows. The
bandwidth procedure defined in this paper is fair-fair reservation
which maintains the minimum delay and provide high
throughput. To allocate the bandwidth for originating flow, the
BW
O
region is verified. If bandwidth can be allocated, it is done
otherwise the BW
C
is checked and bandwidth is allocated.
Finally if the bandwidth cannot be allocated the originating flow
is blocked. To allocate the bandwidth for handoff flow, the BW
H
region is verified. If bandwidth can be allocated, it is done
otherwise the BW
C
is checked and bandwidth is allocated.
Finally if the bandwidth cannot be allocated the handoff flow is
dropped. This procedure is explained below.
3.3 Bandwidth Reservation Procedure
4. PERFORMANCE ANALYSIS
The performance of the proposed system is estimated using the
following metrics:
• Packet Delivery Throughput:
The ratio of the number of packets received by the destinations
to the number of packets sent by the CBR sources is defined as
packet delivery throughput.
• End-to-End Delay of Data Packets:
The difference between the time at which the packet is received
by the destination and the time at which the packet is sent by the
source is defined as end to end delay of data packets. The
packets lost in the journey from source to destination are not
considered. The delay metric do not includes the delay related to
the route discovery, queuing and retransmissions.
The proposed system performance is compared with the RSVP
and EDCF reservation policies. Fig. 3 and Fig. 4 shows the
performance results of comparison in terms of throughput and
delay respectively and can be observed that the performance is
1. For originating flow
a. if bandwidth can be allocated from
BWO then
i. bandwidth is allocated from
BWO
b. else
i. if bandwidth can be allocated
from BWC then
1. bandwidth is
allocated from
BWC
ii. else
1. call is blocked
2. else
3. For handoff flow
a. if bandwidth can be allocated from
BWH then
i. bandwidth is allocated from
BWH
b. else
if bandwidth can be allocated from BWC
then
bandwidth is allocated from BWC
else
call is dropped

International Journal of Computer Applications (0975 – 8887)
Volume 25– No.5, July 2011
43
improved by the proposed system with respect to the legacy
systems.
The QoS parameters specified above are examined by
simulation. Analytically they are examined by using the
blocking and dropping probabilities formulae [2] given below.
The blocking probability for an originating call is given as
∑
+=
=
S
Si
O
C
iPB
1
)(
(3)
The dropping probability for a handoff call is given as
(
)
)0(
!P
S
B
S
SS
H
SS
HO
H
C
OC
µ
λλ
λ
−
−
+
=
(4)
Where,
S = Total Bandwidth
S
R
= Bandwidth reserved for handoff flows.
S
O
= Bandwidth reserved for only originating calls.
The steady state probability P(i) can be obtained:
Where,
( )
( )
1
1
10
!
!!
)0(
−
+=
−
−
+=
−
=














+
+
+
+
=
∑
∑∑
S
Si
i
Si
H
S
O
SS
HO
S
Si
i
S
O
Si
HO
S
i
i
i
O
C
CO
OC
C
O
O
O
O
i
ii
P
µ
λλ
µ
λλ
µ
λλ
λλ
(6)
5.2 Simulation Results
The performance of the proposed system is evaluated by
comparing the performance of the proposed system with the
performance of RSVP and EDCF reservation policies. Fig. 3
shows the comparison of the performance of the proposed
system to the RSVP and EDCF in terms of throughput and can
be observed that the throughput is high for the proposed system.
The experiment is carried out for 35 runs for various flows
between the number of flows and the number of packets
transmitted successfully. It is observed that the throughput of the
proposed system improves when compared with the
performance of RSVP, EDCF methods. Fig. 4 shows the
comparison of the performance of the proposed system to the
RSVP and EDCF in terms of end to end delay of data packets
and can be observed that the delay is low for the proposed
system. The experiment is carried out for 35 runs for various
flows between the number of flows and the time taken to
successfully deliver the total flows. It is observed that the delay
of the proposed system is low when compared with the
performance of RSVP, EDCF methods.
Packet Delive ry Throughput
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2 4 6 8 10 12 14
Number of Flows
Throughput
RSVP
EDCF
Proposed System
Fig. 3 Comparison of packet delivery throughput
End to End Delay
0
5
10
15
20
25
30
35
0 2 4 6 8 10 12 14 16
Number of Fl ows
Delay (10e-3)
EDCF
RSVP
Proposed System
Fig. 4 Comparison of End to End Delay
5. CONCLUSIONS
A new efficient cross layer based bandwidth reservation scheme
is proposed in this paper. The amount of bandwidth to be

International Journal of Computer Applications (0975 – 8887)
Volume 25– No.5, July 2011
44
reserved at each base station was calculated dynamically based
on the user mobility and the traffic intensity of mobile users.
This paper assumes several probabilities that the user may move
left, right, straight and backwards. The analysis of the QoS
performance metrics like packet throughput and end to end
packet delay is carried out and observed that the proposed
system is better in performance in terms of delay and throughput
metrics.
6. ACKNOWLEDGMENTS
Our thanks to the experts who have contributed towards
development of this paper.
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