Minimizing mobiles communication time using modified binary exponential backoff algorithm

International Journal of Computer Networks & Communications (IJCNC) Vol.5, No.6, November 2013

MINIMIZING MOBILES COMMUNICATION TIME
USING MODIFIED BINARY EXPONENTIAL BACKOFF
ALGORITHM
Ibrahim Sayed Ahmad1, Ali Kalakech1, Seifedine Kadry2
1

Arts, Sciences and Technologies University, Lebanon
2

American University of the Middle East, Kuwait

ABSTRACT
The domain of wireless Local Area Networks (WLANs) is growing speedily as a consequence of
developments in digital communications technology. The early adopters of this technology have mainly
been vertical application that places a premium on the mobility offered by such systems. Examples of these
types of applications consist of stocking control in depot environments, point of sale terminals, and rental
car check-in. Furthermore to the mobility that becomes possible with wireless LANs; these systems have
also been used in environments where cable installation is expensive or impractical. Such environments
include manufacturing floors, trading floors on stock exchanges, conventions and trade shows, and historic
buildings. With the increasing propagation of wireless LANs comes the need for standardization so as to
allow interoperability for an increasingly mobile workforce. Despite all the advantages and facilities that
Wi-FI offers, there is still the delay problem that is due to many reasons that are introduced in details in
our case study which also presents the solutions and simulation that can reduce this delay for better
performance of the wireless networks.
Binary Exponential Backoff (BEB) refers to a collision resolution mechanism used in random access MAC
protocols. This algorithm is used in Ethernet (IEEE 802.3) wired LANs. In Ethernet networks, this
algorithm is commonly used to schedule retransmissions after collisions.
The paper’s goal is to minimize the time transmission cycle of the information between mobiles moving in a
Wi-Fi by changing the BEB algorithm. The Protocol CSMA / CA manage access to the radio channel by
performing an arbitration based on time. This causes many problems in relation to time transmission
between mobiles moving in a cell 802.11. what we have done show that the protocol using CSMA / CA
access time believed rapidly when the number of stations and / or the network load increases or other
circumstances affects the network.

KEYWORDS
Network Protocols, Wireless Network, Binary Exponential Backoff.

1. INTRODUCTION
With wireless networking, you don’t need cables to connect your mobile devices. Instead,
wireless networks use radio waves to send and receive network signals. As a result, a mobile
device can connect to a wireless network at any location in your office.

DOI : 10.5121/ijcnc.2013.5605

85


Wireless networks are especially useful for laptops, smartphones, and tablets. After all, the main
benefit of these devices is you can carry them around with you wherever you go. For example, at
work, you can use your laptop at your desk, in the conference room, in the break room, or even
out in the parking lot. With wireless networking, your portable devices can be connected to the
network no matter where you take it.
A wireless network is a network that uses radio signals rather than direct cable connections to
exchange information. An example of this kind of network includes devices from Dell’s
PowerConnect W-Series, powered by Aruba.
A computer with a wireless network connection is like a cellphone. Just as you don’t have to be
connected to a phone line to use a cell phone, you don’t have to be connected to a network cable
to use a wireless mobile device.

2. BINARY EXPONENTIAL BACKOFF
Classic Ethernet uses the 1-persistent CSMA/CD algorithm, this descriptor just means that
stations sense the medium when they have a frame to send and send the frame as soon as the
medium becomes idle. They monitor the channel for collisions as they send. If there is a collision,
they abort the transmission with a short jam signal and retransmit after a random interval. Let us
now see how the random interval is determined when a collision occurs, as it is a new method.
After a collision, time is divided into discrete slots whose length is equal to the worst-case
roundtrip propagation time on the ether (2τ). To accommodate the longest path allowed by
Ethernet, the slot time has been set to 512 bit times, or 51.2 µsec.
After the first collision, each station waits either 0 or 1 slot times at random before trying again. If
two stations collide and each one picks the same random number, they will collide again. After
the second collision, each one picks 0, 1, 2, or 3 at random and waits that number of slot times. If
a third collision occurs (the probability of this happening is 0.25), the next time the number of
slots to wait is chosen at random from the interval 0 to 23 − 1.
In general, after i collisions, a random number between 0 and 2i − 1 is chosen, and that number of
slots is skipped. However, after 10 collisions have been reached, the randomization interval is
frozen at a maximum of 1023 slots. After 16 collisions, the controller throws in the towel and
reports failure back to the computer. Further recovery is up to higher layers. This algorithm,
called binary exponential backoff, was chosen to dynamically adapt to the number of stations
trying to send. If the randomization interval for all collisions were 1023, the chance of two
stations colliding for a second time would be negligible, but the average wait after a collision
would be hundreds of slot times, introducing significant delay. On the other hand, if each station
always delayed for either 0 or 1 slot, then if 100 stations ever tried to send at once they would
collide over and over until 99 of them picked 1 and the remaining station picked 0. This might
take years. By having the randomization interval grow exponentially as more and more
consecutive collisions occur, the algorithm ensures a low delay when only a few stations collide
but also ensures that the collisions are resolved in a reasonable interval when many stations
collide. Truncating the backoff at 1023 keeps the bound from growing too large. If there is no
collision, the sender assumes that the frame was probably successfully delivered. That is, neither
CSMA/CD nor Ethernet provides acknowledgements. This choice is appropriate for wired and
optical fiber channels that have low error rates. Any errors that do occur must then be detected by
the CRC and recovered by higher layers. For wireless channels that have more errors, we will see
that acknowledgements are used. A flowchart representing the binary exponential back off
algorithm is given in Fig. 2
86


Figure 2: Binary exponential back off algorithm used in CSMA/CD

3. MODIFIED BEB ALGORITHM AND TOOLS USED
In this section, we will present tools used in our simulation and the implementation of the
changed BEB algorithm.
NS2 Simulator
Our simulation is done on NS2. Network simulator 2 or NS2 is an object-oriented discrete event
allows us to study the design and protocols for computer networks. It offers various facilities for
simulation of the protocols based on TCP, UDP, routing and multi-distribution (broadcast and
multicast) in the (wired or wireless) networks. This simulator is a free open source. NS2 is
developed in C++ which is a part of the VINT project (Virtual InterNetwork Testbed) is a joint
effort led by the University of Berkeley, USC / ISI (University of Southern California's
Information Sciences Institute), the LBL (Lawrence Berkeley National Laboratory) and Xerox
PARC. It is supported by DARPA (Defense Advanced Research Projects Agency). It uses IU
OTCL interpret. Through this language, the user can describe conditions of the simulation:
network topology, selected from a lot of physical links, used protocols, communications done,
etc.. The user can also create new objects in C++ and use them in NS by instantiations with
OTCL, the two languages C++ and OTCL have both very close hierarchies to each other. In NS2
several libraries are available and there are some specific needs for simulation of wireless
network and "multicast" communication [Opn07][Ane99][Ns07][Ns06][Luc03]. In our work we
use NS2 for its flexibility and the availability of its code [Ben07].

87


Communication entity in NS2
The node (communicating entity) is the basic element of our model. A node in NS2 is a class
defined in OTCL which has three entities containing: the classifier, the link and the agent.
The classifier
The function of a node of the fields is examined by received packet, and more specifically, the
source address and destination address. According to contention losses, the node sends the packet
on its outgoing interfaces (Fig. 3). In NS2, then this is performed by an object called "Classifier".
There are several types of classification that are used for different purposes:
- "Address classifiers" is used to treat with unicast packets, and its role is directly to select
packets addresses, direct the node, and select the link to the next node.
- "Port classifier" its role is to select the agent to the packet which is intended.
- "Multicast classifier" is used to classify multicast packets.
The link
It is used to connect the nodes by each other (Fig. 3). A link is defined by several parameters
including: bandwidth, entry point, the lifetime of each packet, etc.. NS2 has several types of links,
so we can distinguish unidirectional links from bidirectional links and wired links to wireless
networks model without sound.
The Agent
Agents represent endpoints where packets in network layer are constructed and consumed. These
agents are the third component of the node. In NS2, the agent's role is to provide the destination
address; its function is to generate the packets and the interface to the application class (Fig. 3).
In NS2 there are several types of agents, each has a specifying role:
- TCP agent: for emitting TCP traffic
- UDP agent: for emitting UDP traffic
- TCPSink agent: for the receipt of TCP traffic
- NULL Agent for receiving UDP packets.
Figure 3 shows the Existing entities in a node and the links between ITS entities.

88


Figure 3: Diagram of a node in NS2.

4. TCL LANGUAGE
Tcl (originally from "Tool Command Language") is two things: a scripting language, and an
interpreter for that language that is designed to be easy to embed into our application. Tcl and its
associated graphical user-interface toolkit, Tk, were designed and crafted by Professor John
Ousterhout of the University of California, Berkeley. The Tcl interpreter has been ported from
UNIX to DOS, Windows, OS/2, NT, and Macintosh environments. The Tk toolkit has been
ported from the X window system to Windows and Macintosh.

5. AWK LANGUAGE
Awk is a programming language that handles several tasks, like mechanical data manipulation changing the format of data, checking its validity, finding items with some property, adding up
numbers, printing reports, and the like, with very short programs, often only one or two lines
long. An awk program is a sequence of patterns and actions that tell what to look for in the input
data and what to do when it's found. Awk examines a set of files for lines matched by any of the
patterns; when a corresponding line is found, the corresponding action is performed. A pattern
can select lines by combinations of regular expressions and comparison operations on strings,
numbers, fields, variables, and array elements.
Actions may perform arbitrary processing on selected lines; the action language looks like C but
there are no declarations, and strings and numbers are built-in data types.

6. SIMULATIONS
Configuration of communicating entities
Configuration of access point
The base station is configured as follows (Fig. 4)
89


$ Ns_ node-config-adhocRouting DSDV
•
•
•
•
•
•
•

llType-LL / / LL layertype
macType Mac/802_11 / / type of the MAC layer
IfqLen 800 / / length of the tail
antType Antenna / OmniAntenna / / type of antenna
phyType Phy / WirelessPhy / / type of physical layer
channelType Channel / WirelessChannel / / type of channel
wiredRouting ON / / Wired link with other AP's.

In this list we find the basic configurations of the AP. (Type of MAC and physical layer,
antenna type...). Figure 4 describes entities used for the AP (agents, links, and classifiers).

Figure 4: Figure of base station

Configuration of mobile nodes
The nodes are moving in the Mi cell base station where each node has a unicast address and
exchange packets with other mobile station through the base station. In each node there exist
a single wireless link but there are two agents (Fig. 5):
•
•

An agent to send UDP packets (UDP Because in Our case, we use UDP only)
A null Agent to Receive UDP packets.

These nodes operates in the cell of an access point to which they are attached as shown in Fig
5.

90


Figure 5: Diagram of the mobile node

General parameters
The general parameters of this simulation are given in (table 1). These parameters for the
simulation model are compatible with the measure made.
Table 1: Simulation Parameters

CBR Packet Size

210 bytes

CWMin

31 ms

CWMax

1023 ms

SIFS

0.000010 s

SlotTime

0.000020 s

CBR rate

448Kb

7. MODELING THE METHODS OF BACK-OFF
We will now describe the numerical experiments to adjust the simulation parameters “a” and “b”
of the back-off algorithm.
The purpose of this simulation is to study the effect of the load (by changing the number of
mobiles) on the transmission time for different values of parameters: “a” and “b”. Our approach is
based on cooperation involving the mobiles in the cell, by pairs, and each pair in the cell transmits
CBR traffic to other one during a specified time.
Our simulation protocol is the following: We will evaluate the changes in throughput and end to
end delay while changing “a” and “b” and the number of nodes in the cell. To increase the cell
load, we increase the number of mobiles in introducing new pairs (the mobile communicates with
other in pairs), each forming a cooperation group. In the example in (Figure 6) it is pair M5 - M6.
For each simulation we vary the values of “a” and “b”. All these mobiles broadcast via the AP (in
pairs) according to NS2 simulation parameters mentioned above.
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If D is the transmission delay between mobile references, it can be defined as time between
sending the message (Temis) and corresponding time to receive the message by the mobile
receiver Trec: D= Max(Trec - Temis )
It should be noted that this simulation will help us to find the optimal values of “a” and “b” by
changing the Back-off algorithm.The figure below describes our work

Figure 6: Principle of simulation used to assess the changed Back-off

8. IMPLEMENTATION OF THE MODIFIED BEB
In fact the back-off algorithm BEB is implemented in standard NS2. To implement our
"modified" algorithm of Back-off algorithm it is sufficient to act on some files in the hierarchy of
NS2 MAC layer. We show this hierarchy in the (Figure 7).

92


Figure 7: Hierarchy of NS2 MAC layer [Ns06].

After the study of this hierarchy, we decided to modify the code in C++ functions included in in
the following files:
•
•
•
•
•

tcl/lan/ns-mac.tcl.
tcl/lib/ns-lib.tcl.
Mac/mac-802_11.h.
Mac/mac-802_11.cc.
tcl/lib/ns-default.tcl.

We want to change the formula of Back-off as follows:
On failure of transmission: CW = min (a.CW, CWmax)
and each successful transmission, we decrement the value of CW by value b.
CW = max (CW-b, CWmin)
To make these changes we use the C++ of NS2 and we change the File Mac/Mac-802_11.hh as
follows:
In
case
of
transmission
failure,
we
modified
the
inc_cw() function by setting CW=min(a* CW,CWmax), a is initialized with a value taken from
the interval [1,3].
Original Function:
inline void inc_cw()
{
cw_ = (cw_ << 1) + 1;
if(cw_ > phymib_.getCWMax())
cw_ = phymib_.getCWMax();
}
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Modified one:
inline void inc_cw()
{
cw_= min((u_int32_t)(phymib_.geta()*cw_),phymib_.getCWMax());
}
In case of successful transmission, we modified the rst_cw() method by setting
CW=max(CWmin, CW-b) instead of CW = CWmin.
Original Function:
inline void rst_cw()
{
cw_ = phymib_.getCWMin();
}
Modified Function:
inline void rst_cw()
{
cw_= max(phymib_.getCWMin(),(u_int32_t)(cw_- phymib_.getb()));
}

9. SCENARIO OF SIMULATION
We calculate the average transmission time between all mobiles during a time interval T = 120s
for which the cell load remains constant.
To find the best values of “a” and “b”, we vary b in the interval [0, 10] steping 1 each time and
for each b, value varies in interval [1, 3] steping 0.1 each time. The results obtained at the end of
the simulations corresponding to different values of “a” and “b” will allow us to choose their
optimal values. The optimum means here leading the minimum transmission delay, and
maximum throughput.
The following flowchart (Figure 8) describes the scenario simulation and the increment of “a”
and “b”.

94


B=0
B+=1
B<1
1
A=1
A<3.

A+=0.

Figure 8: Algorithm of evaluating (a, b) values of Back-off changed.

9. ANALYSIS OF RESULTS AND VALIDATION
In this section, we present the results obtained by changing the mechanism of Back-off. First we
present test result for base BEB and the modified BEB with the same scenario mentioned in
chapter 3 but during a period of 2s and not 120s for testing purposes. Second we present the
results of our end simulation and obtaining the optimum values of “a” and “b”.
Before applying the new algorithm we make a simulation test to get results in order to proof that
the new added parameters in ns2 files takes effect. The test is applied with the parameters
mentioned in the previous chapter but during a period of 2 s only. The BEB algorithm without
change has a=2 since when a failer transmission happens the contention window is doubled that’s
means multiplied by 2 leading to a=2 but when a successful transmission occur cw returns to
cwmin and in our algorithm cw will be the maximum between cwmin and cw-b for this reason we
cannot deduce b but we will do the simulation assuming b is 0 and table 5.1 shows the results
which proves the effect of the new algorithm on throughput and delay.

95

Table 2: Comparing results between old and new algorithm

Throughput Modified
Algorithm

n=6
n=10
n=30
Delay Modified Algorithm

n=6
n=10
n=30
Throughput UNModified
Algorithm

n=6
n=10
n=30
Delay UNModified
Algorithm

n=6
n=10
n=30

b
0
0
0

T.
RecvByte
6.64
6.79
4.64

Throuput
435.63
445.97
304.84

r/s
0.19
0.11
0.02

a
2
2
2

b
0
0
0

Packet
Delivery
Ratio
19.3
10.98
2.33

Total
Dropped
Packets
177
453
2531

Average End-to-End
Delay
308.33 ms
317.53 ms
335.18 ms

a
2
2
2

b
0
0
0

T.
RecvByte
7
6.9
4.61

Throuput
459.83
452.06
302.61

r/s
0.2
0.11
0.02

b
0
0
0

Packet
Delivery
Ratio
20.34
11.14
2.32

Total
Dropped
Packets
174
544
2573

Average End-to-End
Delay
355.53 ms
388.19 ms
417.30 ms

a
2
2
2

a
2
2
2

10. NEW BEB ANALYSIS AND RESULT
Our goal is to make several simulations by changing the values of “a” and “b” in modified Backoff mechanism. In each simulation, we measure the transmission time between each two mobiles
and calculate the average end to end delay of communicating mobiles, besides we calculate the
throughput by measuring the total transmitted bits during a specified period of time (simulation
period).
Our goal is to choose the optimal values of “a” and “b”, which gives:
- The minimum transmission time
- Maximum capacity.
For this, we made 21 x 11 simulations for the values of “a” and “b”. We present in the appendix
A the tables of the results obtained for throughput and for end to end delay for which we can
choose the optimal values of “a” and “b”. Figurs 9, 10, 11, 12, 13, 14 shows these results
graphicaly.
96


Figure 9: Throughput for no. of nodes =6


97



Figure 12: End to end Delay for no. of nodes =6

98




According to the graphs shown and the tables in Appendix A we deduce that the optimum values
of “a” and “b” are:
According to throughput measurement:
1
2

For n=6: a=1.1, b=1
For n=10: a=1.2, b=3
99


3
For n=30: a=1.4, b=6
According to delay measurement:
1
For n=6: a=1.2, b=2
2
For n=10: a=1.2, b=2
3
For n=30: a=1.1, b=4
The simuation result lead us to more than one optimum values of “a” and “b” according to
circumstances the network based on.

11. GENERAL CONCLUSION
This paper aims to minimize the delay time through wireless communication by changing the
BEB algorithm. The Protocol CSMA / CA is a protocol that manages access to the radio channel
by performing an arbitration based on time. This causes many problems in relation to time
transmission between mobiles moving in a cell 802.11. what we have done show that the protocol
using CSMA / CA access time believed rapidly when the number of stations and / or the network
load increases or other circumstances affects the network.
Our objective is to minimize the time transmission cycle of the information between mobiles
moving in a Wi-Fi. We reach our solution by changing two main functions in the BEB algorithm
and our study proves that the changes we made give an acceptable result. We made the simulation
according to variable number of nodes and for each one we get a new values of “a” and “b”.
Future studies will be to create a fuzzy logic function to make choice of the optimum values of
“a” and “b” according to specific rules and parameters.

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