EBCD: A ROUTING ALGORITHM BASED ON BEE COLONY FOR ENERGY CONSUMPTION REDUCTION IN WIRELESS RELAY NETWORKS

International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.3, No.4, August 2012
DOI : 10.5121/ijasuc.2012.3401 1
EBCD: A ROUTING ALGORITHM BASED ON BEE
COLONY FOR ENERGY CONSUMPTION REDUCTION
IN WIRELESS RELAY NETWORKS
Arash Ghorbannia Delavar1
and Elham Javiz2
1
Department of Computer Engineering and Information Technology,
Payam Noor University, Tehran, Iran
a_Ghorbannia@pnu.ac.ir
2
Department of Computer Engineering and Information Technology,
Payam Noor University, Tehran, Iran
javiz.ssg@gmail.com
ABSTRACT
One of the important issues in wireless networks is the Routing problem that is effective on system
performance, in this article the attempt is made to propose a routing algorithm using the bee colony in
order to reduce energy consumption in wireless relay networks. In EBCD algorithm, through combined of
energy, distance and traffic parameters a routing algorithm for wireless networks is presented with more
efficiency than its predecessor. Applying the bee colony method would allow the placement of the
parameters under conventional conditions and to get closer to a mechanism with a better adaptability
than that of the existing algorithm. According to the parameters considered, the proposed algorithm
provides a fitness function that can be applied as a multi-hop. Unlike other algorithms of its kind this can
increase service quality based on environmental conditions through its multiple services. This new
method can store the energy accumulated in the nodes and reduce the hop restrictions.
KEYWORDS
Wireless relay networks, IEEE 802.16j, Multi-hop relay, Routing, Bee colony algorithm, Energy
consumption
1. INTRODUCTION
Multi hop wireless systems have the potential to offer more coverage and capacity over single-
hop radio access systems. There are a number of different types of multi hop wireless networks,
notably the ad hoc networks, sensor networks, and wireless mesh networks. Each one of these
network types has different characteristics that results having different systems in design and
routing protocols. Another type of the multi hop wireless networks that is a subject of focus is
based on relay architecture [2]. In the recent years, many studies have been conducted on the
wireless communication via relays. The relays have their essential input in future
communication networks. Relay-based systems are typically composed of small form factor
low-cost relays, which are associated with specific base stations (BSs). In general , the relays
could be used in the initial layers of the network to provide more coverage and cover vast areas
at lower cost than that of the BS; they can also be used in providing increased capacity in more
developed networks and cover the holes such as the shaded areas of the buildings. The IEEE
802.16 standard is developed to provide broadband wireless access in 4G systems. Its physical
layer adopts the OFDMA technique, where a base station (BS) can communicate with multiple
mobile stations (MSs) simultaneously via orthogonal channels. Since the typical PMP (point-to-
multi-point) operation could face several problems such as holes coverage and network
congestion at the BS, 802.16j has developed a standard to support relay mode function and

2
solve these problems in 802.16 systems [1]. IEEE 802.16j network includes one Base Station
(BS), multiple Relay Stations (RSs) and Mobile Stations (MSs). All MSs are under the BS’s
signal coverage and RSs are located in the BS’s coverage boundary in order to relay data
between MSs and the BS. There are two types of relays: transparent and non-transparent. The
transparent relays are used in increasing the capacity within the BS coverage area. These relays
have low complexity and serve in topologies up to two hops. The non-transparent relays are
used in increasing the coverage areas. These relays have different levels of complexity and are
used in topologies with more than two hops. Since the 802.16j relay networks have multi hop
paths between the BS and MS, naturally issues regarding routing and path management rise.
Routing and path management functions manage the Multi-hop paths between the BS and MS.
Routing is based on a tree structure where the BS is root and the MSs are the leaves. Although
routing is tree-based the decisions could be made regarding which RS is associated with which
MS [2].
Generally there exist three scenarios in IEEE 802.16j relay networks that include [13]:
1. The MS is connected directly to BS
2. The MS is connected to BS through a transparent relay
3. The MS is connected to BS through one or more non-transparent relay
As shown in Figure 1, this newly introduced routing algorithm works on all three scenarios. In
practice, much research have worked in the two-hop relays but have not supported the ability to
increase the capacity of relays, although the two-hop cannot full fill the objective of having
mobile users. This point is considered in the proposed algorithm here.
Figure 1: An example of usage scenario
2. RELATED WORKS
So far, several algorithms for routing in Wireless Multi-Hop Relay networks are presented. C.
Hong et.al [6] has proposed a routing algorithm based on linear programming. In this algorithm,
the routing is based on the total time to send and receive data from source to destination. K.
Wang et.al [7] has presented a route selection based on the optimum throughput. This algorithm
is focused on two-hop networks. D.J. Son et.al [8] has offered a route selection scheme based on

3
Spectral Efficiency and load traffic for IEEE802.16j networks. K.P. Shih et.al [9] has
introduced a new parameter called SEL for evaluating the optimal path. SEL considers the
Spectral Efficiency parameters and link load. In their article the focus is only on the Two-Hop
Relay Networks [4].
3. THE BEE COLONY ALGORITHM
Considering the use of biological ideas in routing algorithms is an almost new concept. The idea
of these algorithms was initialled in wired networks and then extended to wireless networks.
One of these ideas is inspired from bees search in routing that is copied in wireless networks
[3], [14], [16], [17]. In a bee colony a strange phenomenon is observed which is characterized
by the behavioural manner of every individual bee under different circumstances. Although
every bee follow simple rules, their collective behaviour is very intelligent; therefore, this aspect
of the bee colony is applied in wireless relay networks.
1.3. Characteristics of a bee colony
The study conducted upon bee colonies and their inter communication system by Karl Frisch
has revealed many aspects of their communicative system. Every bee return to the hive conveys
for information on distance, direction and quality of food to the other bees through specific
dance [15]. By applying this mechanism the bees in the hive begin their journey to collect their
food. Bee colonies have unique characteristics like:
• appropriate and efficient distribution of bees among different food sources
• the appropriate division of labor
• testing and estimating the quality of food by every bee and sending the appropriate
number of bees to the food source based on its quality through the dance
• no central control system
• decision making about the suitability of a food source considering the energy required
for food collection
In a bee colony, bees have the same behavioral structure, but every bee according to colony’s
needs is equipped with different skills over time. For example, a bee may be required to collect
food and in other time phase it might be required for storing the food. This type of behavior
causes the colony to be flexible against the environmental changes. A very intriguing and subtle
point in the duty distribution system in a bee hive is that the bee in getting information from the
other bees in a close circuit. This fact prevents that sudden swarming all the bees don’t bring an
influx to the best source, a common effort for the colony’s welfare.
4. PROBLEM DEFINITION
The data transmission among stations in the Wireless relay networks is synchronized on frame
basis. Every frame consists of several time slots defined as a basic time unit for transmission in
the system [6]. To every MS a burst is assigned for data transmission to its uplinks that include
many time slots and multiple slots associated with the MCS (Modulation and Coding Schema)
level. Based on the MCS level the amount of transferable data (in bits) is determined, in each
slot [1]. Energy consumption during each frame for data transmission between MSi and RSj is
obtained through the following equation [1]:

4
(1)
Where, di is the number of bits in a request at the current frame, D(k) is the amount of bits
transmitted by a slot, τ is the length of a slot (in seconds), B is effective channel bandwidth, Gi
is antenna gains at MSi, Gj is antenna gains at RSj, No is the thermal noise level.
I (i, j) is the interference of the simultaneously transmitted, calculated through the following
equation [1]:
(2)
When MSi sends data to an RSj by using the transmission power Pi and MCS level Mi , the
received signal power P(i, j) at RSj is presented as [1]:
)
,
(
)
(
)
,
(
j
i
L
M
P
G
G
j
i
P
i
i
j
i ⋅
⋅
=
(3)
Where, L (i, j) is the path loss from MSi to RSj, which is calculated based on SUI (Stanford
university interim) path loss model [11], [12]. There exists a direct relation between distance
increase and the amount of BS path- loss.
5. PROPOSED ALGORITHM
The flexible nature and the ability to adopt with new environment and the bee colony’s decision
making features regarding a specific food source-with respect to the quantitative and qualitative
aspects of the food source- and the energy needed to reach to the source are considered here in
developing a routing algorithm with the less energy consumption objective.. In this article the
up Link traffic is evaluated. The Down Link traffic is calculated in a similar approach where the
details are ignored. The Non-transparent relay for communication support over a two-hop and
transparent relay for increased capacity within the two-hop are considered here and the BS is
evaluated as a specific RS.
In this algorithm, first an initial population of random solutions is considered; then for each
solution all useful paths are evaluated by F fitness function and through Elitism Selection
method a route is chosen, this process is repeated until the maximum number of allowable steps
are obtained; then the objective function value of each of the solutions is evaluated through the
following equation:
(4)
Here, the algorithm steps are repeated until the stopping condition is fulfilled .As mentioned
before, in order to assess the routes of every solution the fitness function F is applied which is
obtained by the following equation:
(5)
j
i
k
d
MR
G
G
j
i
L
j
i
I
N
B
k
D
E i
⋅
⋅
+
⋅
×
×






=
)
,
(
))
,
(
(
10
)
)
(
( 0
10
)
(
δ
τ
)
,
(
)
,
( j
i
P
j
i
I
i
i
′
= ∑′
≠
Dist
T
E
F
1
+
+
=
∑
=
= n
k
k
i
i
f
f
p
1

5
The parameters used in the fitness function consist of:
A- E is the total amount of energy consumed for data transmission from MS to the BS
(6)
Where, EMR is the amount of energy consumed for data transmission from MS to the RS, ERR is
the amount of energy consumed for data transmission from RS to the RS, ERB is the amount of
energy consumed for data transmission from RS to the BS, EMR, E RR and E RB are calculated
through equation (1)
B- T is the data transmission cost or traffic that is obtained through the following equation:
(7)
C-Dist is the distance parameter considered as equal to the received signal power in this realm.
The less the distance the more signal receiving power. This parameter is calculated through
equation (3)
Chart 1shows the flowchart of this proposed routing algorithm which is based on the bee colony
optimization algorithm.
Chart1. Proposed Algorithm Flowchart
BW
d
T i
=
RB
RR
MR E
E
E
E +
+
=

6
6. SIMULATION
The MATLAB software is used here in order to simulate the proposed algorithm. In this
conducted simulation nodes are deployed in the environment randomly and the run time is 10
seconds (2000 frames).The simulation parameters are presented in Table 1.
Table1: Simulation Parameters
Parameter Value
Channel Bandwidth(BW) Rand[3.5,10]MHZ
di Rand[900,2000] bits/frame
Antenna height BS:30m,RS:10m,MS:2m
(N0)Thermal Noise -100dBm
max
i
p 1000mw
BS,RS antenna gain Rand[5,20]dB
MS antenna gain Rand[1,10]dB
d Rand[200,2000]m
Frame Duration 5ms
Slots Per Frame 48
a) In the different number of MSs and 10 RSs b) In the different number of RSs and 100 MSs
Figure2: The energy consumption in the Network with 3 -hops

7
a) In the different number of MSs and 20 RSs b) In the different number of RSs
and 100 MSs
a) In the different number of MSs and 30 RSs b) In the different number of RSs
and 100 MSs
This proposed algorithm is compared with the Dijkstra’s shortest-path algorithm. Here three
scenarios are considered for Comparisons. In the first, the network topology is of 3 hop
maximum i.e.2 relay layers between MS and BS. The total energy in each frame is calculated by
having different number of MSs, where there are 10 RSs. As shown in Figure 2(a). The y-axis is
presented in an exponential scale. Indicating that here, the energy saving is approximately
optimized by 4.8% in comparison with that of the Dijkstra’s shortest-path algorithm. Then the
total energy with respect to different numbers of RSs and 100 MSs in Figure 2(b) are calculated.
Here a 5% optimization in energy consumption is. The topology used in the second scenario is
evident up to 4 steps. According to Figure 3(a) the total energy consumed with a number of
different MSs and 20 RSs in this proposed algorithm is reduced up to 5.1%. Figure 3(b)
indicates that with a variable number of RSs and 100 MSs the total energy consumed in EBCD
is approximately improved by 3.9%. In the third scenario, the steps are of 5 hop maximum. The
total energy consumed in this algorithm with variable number of MSs and 30 RSs in figure 4(a)
is about 4% less than that of the Dijkstra’s shortest-path. In figure 4(b) with 100 MSs and a
variable number of RSs the total energy consumed in EBCD is approximately improved by

8
3.4%. In general the Numerical results of the simulations indicate that this proposed routing
algorithm is efficient in terms of reducing energy consumption.
7. CONCLUSION
In this article a new algorithm for routing in the relay networks using the properties of the bee
colony with an emphasis on reducing energy consumption is presented. Unlike most works in
this field that have been working with the two-step, here the number of hops is extended to 5.
For the measuring function and evaluating the effective environmental parameters of energy, the
distance and traffic are considered. This Proposed algorithm compared to other known
algorithms called Dijkstra’s Shortest path algorithm indicate that EBCD is about 4.3% more
efficient than the Dijkstra’s shortest-path in energy consumption.
REFERENCES
[1] Jia.Ming Liang, You.Chiun Wang, Jen.Jee Chen, Jui.Hsiang Liu& Yu-Chee Tseng, (2010)
“Efficient resource allocation for energy conservation in uplink transmissions of IEEE 802.16j
transparent relay networks”, MSWiM 187-194.
[2] V.Genc, S.Murphy, Y. Yu, J.Murphy, (2008) “IEEE 802.16J relay-based wireless access
networks: an overview”, IEEE Wireless Communications, Vol. 15, Issue5, pp. 56 – 63, Oct.
[3] D. Teodorovi, T. Davidovi, M.Selmi(2011) “Bee Colony Optimization: The Applications
Survey”, ACM Transactions on Computational Logic.
[4] N.Satiman, A.I.A. Zamani, N. Fisal, S.K.S. Yusuf, S.H.S. Ariffin, N.M.A. Latiff,( 2010) “Joint
Routing and Scheduling in Multi-hop Relay Network: A Survey Paper”, published in
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[5] N.Satiman, N.Fisal, N. N. M. I. Maarof, A. I. A. Zamani, S. K. S. Yusof ,M. Abbas,( 2011) ”An
Efficient Link Aware Route Selection Algorithm for WiMAX Mobile Multi-hop Relay
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[6] C.Y. Hong, and A.C. Pang (2009) “3-Approximation Algorithm for Joint Routing and Link
Scheduling in Wireless Relay Networks”, published in IEEE Transactions on Wireless
Communications, Vol.8, No.2, pp:856- 861, February.
[7] K. Wang, M. Peng and W. Wang, (2007) “Channel aware Adaptive Resource Allocation in
Two- hop Wireless Relay Networks”, appeared in PIMRC’07, September.
[8] D.J. Son, J.W. Jang,( 2010) “A Path Selection Scheme Considering Traffic Load for IEEE
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[9] K. P. Shih, S.S. Wan, C.Y. Lien, (2009) “A high Spectral Efficiency and Load-Aware Metric for
Path Selection in IEEE 802.16j Multi-hop Relay Networks”, In IEEE Symposium on Computers
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[10] Arash Ghorbannia Delavar, Amir Abbas Baradaran, javad Artin, (2011) “RGWSN: Presenting a
genetic-based algorithm to reduce energy consumption in wireless sensor
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[13] D. Ghosh, A. Gupta, P. Mohapatra, (2009) “Adaptive Scheduling of Prioritized Traffic in IEEE
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[14] Muddassar Farooq, (2006) “From the wisdom of the hive to intelligent routing in
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Authors
Arash Ghorbannia Delavar received the MSc and Ph.D. degrees in computer
engineering from Sciences and Research University, Tehran, IRAN, in 2002 and
2007. He obtained the top student award in Ph.D. course. He is currently an
assistant professor in the Department of Computer Science, Payam Noor
University, Tehran, IRAN. He is also the Director of Virtual University and
Multimedia Training Department of Payam Noor University in IRAN. Dr. Arash
Ghorbannia Delavar is currently editor of many computer science journals in
IRAN. His research interests are in the areas of computer networks,
microprocessors, data mining, Information Technology, and E-Learning.
Elham Javiz received the B.Sc. in computer engineering from Azad University,
najafabad, IRAN, in 2004. She is M.Sc. student in computer engineering in
Payam Noor University. Her research interests include computer networks,
wireless communication, wireless multi hop networks and Bee colony algorithm.

EBCD: A ROUTING ALGORITHM BASED ON BEE COLONY FOR ENERGY CONSUMPTION REDUCTION IN WIRELESS RELAY NETWORKS

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