Optimization Algorithm to Control Interference-based Topology Control for Delay-Constrained Mobile Ad-hoc Networks

Abstract—To increase the network capacity, there is
need to minimize the interference among nodes and
optimum control of topology in the foundation of
network. Recently, technological development helps to
build of mobile ad-hoc networks (MANETs) in order to
improve the quality of service (QoS) in terms of delay. In
contradictory to the objective of minimizing interference,
it is important to concern topology control in delay
constrained environment. The present research work
attempts to control the delay-constrained topology with
jointly considering delay and interference concept.
Additionally, the study proposed an interference oriented
topology control algorithm for delay-constrained
MANETs by taking account of both the interference
constraint and the delay constraint under the specific
condition of transmission delay, contention delay and the
queuing delay. Further, the study investigated the impact
of node mobility on the interference oriented topology
control algorithm. Finally, the results of the present
study shows that the proposed algorithm controls the
topology to convince the interference constraint, and
increases the transmit range to congregate the delay
requirement. Also, the study conclude that the algorithm
could effectively reduce the delay protocol and improve
the performance effectively in delay-constrained mobile
ad hoc networks.
Keywords: ad-hoc networks, topology, interference,
algorithm, optimization
I. INTRODUCTION
Conventionally, most of digital components which
necessitate network connections in order to provide
data services which in turn connected through
permanent infrastructures like base stations. Various
practical constrains are incorporated in communication
services in the locations without predetermined
infrastructures. Particularly, heterogeneous ad hoc
networks consist of different types of terminal
accessories, access technologies, number of receiver
(antennas), rate of transmission and power at different
terminal nodes. This sort of provision could provide
suppleness for wireless communication, which results
in new challenges for network design and optimization.
Zhang et al. (2015) attempted to compute the average
end-to-end delay of CBR packets established at the
target spots with increasing traffic pack. In this study,
the author focused mainly on delay concern.
Additionally, the transmission power in ITCD is
minimized while keeping the connectivity and packet
collisions are taken into account and also the mobility
is also considered to remove un-stable links in the
topology. ITCD can guarantee terminal destination
nodes to receive data packets successfully with a large
probability and make end-to-end delay within a
threshold by adjusting transmission power. Li and
Eryilmaz (2012) proposed an algorithm to describe the
challenging problem of designing a scheduling policy
for end-to-end deadline constrained traffic with
reliability requirements in a multi-hop network. In their
research work, the main objectives is framed
orientating towards scheduling alone. Li et al. (2009)
revealed that an optical network is too costly to act as a
broadband access network. On the other hand, a pure
wireless ad-hoc network with different nodes may not
provide satisfactory broadband services since the per
node throughput diminishes as the number of users
increase. In this case, hybrid wireless networks have
greater throughput capacity and smaller average packet
delay than pure ad hoc networks. The present study
proposed three different algorithms with different
complexity and characteristics. The throughput
capacity and the average packet delay are taken into
account and the proposed protocol focuses at
minimizing the overall network overhead and energy
expenditure associated with the multihop data retrieval
process while also ensuring balanced energy
consumption among SNs and prolonged network
lifetime. This is achieved through building cluster
Optimization Algorithm to Control
Interference-based Topology Control for
Delay-Constrained Mobile Ad-hoc Networks
Selvakumar1
, S. Selvakumar2
1
Research Scholar, Department of Computer Science and Engineering, SRM Institute of Science and
Technology, E-mail id: selvakumar1985s@rediffmail.com
2
Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and
Technology, E-mail id: selvakumar.s@ktr.srmuniv.ac.in
International Journal of Computer Science and Information Security (IJCSIS),
Vol. 16, No. 5, May 2018
16 https://sites.google.com/site/ijcsis/
ISSN 1947-5500

structures consisted of member nodes that route their
measured data to their assigned cluster head (CH).
Also, clustering has proven to be an effective approach
for organizing the network in the above context.
Besides achieving energy efficiency, clustering also
reduces channel contention and packet collisions,
resulting in improved network throughput under high
load.
II. RELATED WORKS
In wireless communications, the goal of the medium
access control (MANET) protocol is to efficiently
utilize the wireless medium, which is a limited
resource. The effective use of the channel strongly
determines the ability of the network to meet
application requirements such as quality of service
(QoS), energy dissipation, fairness, stability, and
robustness (Rahnem, 1993). Based on the collaboration
level, MANET protocols can be classified into two
categories: coordinated and non-coordinated
(Numanoglu et al., 2005). Channel access in non-
coordinated protocols is typically based on a
contention mechanism between the nodes. IEEE
802.11 (Huang and Lai, 2002) is an example of a non-
coordinated protocol. Although it is easier to support
non-uniform traffic with non-coordinated protocols,
these protocols are unsuitable for highly loaded
networks due to the contention mechanism. On the
other hand, in coordinated channel access protocols,
the medium access is regulated, making them better
suited for networks where the network load is high.
IEEE 802.15.3 , IEEE 802.15.4 , and MH-TRACE
(Cooklev, 2004) are examples of such coordinated
protocols. Coordinated channel access schemes
provide support for QoS which in turn reduce energy
dissipation, and increase throughput for low-to-mid
noise levels and for dense networks. However, these
protocols perform poorly under non-uniform traffic
loads. MH-TRACE further uses a soft clustering
approach where the clustering mechanism is utilized
only for providing channel access to the member
nodes. Hence, each node is capable of communicating
directly with every other node provided that they are
within communication range of each other.
The main consideration in forming clusters is the
load distribution in the network. Clusters should be
formed in such a way that they are able to meet the
demand for channel access of the nodes in the cluster
as much as possible. When the cluster is not able to
meet the demand, either some of the transmissions are
deferred (better suited for guaranteed delivery traffic)
or the packets are dropped (better suited for best effort
traffic). Thus, while designing a protocol or
determining the performance of a specific protocol, the
load distribution has crucial importance. Clustering
approaches may be classified as soft and hard
clustering. In hard clustering approaches, such as GSM
networks (Mohapatra et al., 2003), nodes belong to the
cluster in which they operate.
Due to fading, two distinct transmissions may
successfully operate over the same frequency, code
and time range if they are well separated spatially. A
successful protocol should employ this kind of
spatial reuse for the sake of efficient use of the
channel resources. Clustering protocols, aim to
maximize the distance between the clusters using the
same portion of the channel. In cellular networks,
the same set of frequencies may be assigned to cells
(clusters) that are separated well enough depending
on the frequency reuse factor employed (Goldsmith
et al., 2011). Analogously, in MH-TRACE, each
cluster operates in one of several frames separated in
time. MH-TRACE has internal mechanisms that
maximize the distance between clusters operating in
the same frame (co-frame clusters). To analyze the
performance of soft clustering protocols to
determine how to best set their parameters for
efficient use of the channel resources. Specifically,
the clustering mechanisms of MH-TRACE is
described in detail as shown in the figure 1.
Diamonds represent selected clusterheads (CH) and
dots represent the nodes in the network. CH frame
matching, together with the contents of each frame,
is depicted. There are randomly chosen clusterheads
that regulate the channel and provide channel access
for the nodes in their communication range. Each
clusterhead (CH) operates using one of the frames in
the superframe structure. There is also a spatial reuse
mechanism that allows more than one CH to operate
in the same time frame provided that the interference
is low.
Each frame in the superframe is further
divided into sub-frames. The control sub-frame
constitutes the management overhead. Beacon,
cluster announcement(CA), and header slots of the
control sub-frame are used by the CHs, whereas
contention slots and information summarization (IS)
slots are used by the ordinary nodes. At the
beginning of the frame, the CH announces itself to
the nearby nodes by sending a beacon message in
the beacon slot of the control sub-frame. The CA
slot is used for interference estimation for CHs
operating in the same frame (co-frame CHs). During
the CA slot, the CH transmits a message with a
given probability and listens to the medium to
calculate interference caused by other CHs operating
in the same frame.
Vol. 16, No. 5, May 2018
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Figure 1: A snapshot of MH-TRACE clustering
and medium access
Contention slots are utilized by the nodes to pass
their channel access requests to the CH. A node that
wants to access to the channel selects a contention slot
randomly among the contention slots and sends a
contention message in that slot. After listening to the
medium during the contention slots, the CH becomes
aware of the nodes that request channel access and
forms the transmission schedule by assigning available
data slots to the nodes. After that, the CH sends a
header message that includes the transmission schedule
that will be followed for the rest of the frame. There
are an equal number of IS slots and data slots in the
remainder of the frame. During the IS slots, nodes send
short packets summarizing the information that they
are going to be sending in the order announced in the
Header. By listening to the relatively shorter IS
packets, nodes become aware of the information that
are going to be sent and may choose to sleep during the
corresponding data slots if they are not interested in (or
the recipient of) the data.
The most direct approach to determine the
MANET performance is to obtain samples of field
measurements on the performance metrics (Redi et
al., 2006). However, the difficulty in implementation
on real hardware and taking a large set of field
measurements make this method impractical for
most cases, and not the best approach in the protocol
design stage. It is easier and more convenient to
implement a protocol on a simulation platform.
Thus, simulation studies are the most widely used
methods to evaluate the performance of protocols
(Wang et al., 2012). However, it is impractical to
determine the performance of a protocol for large
sets of conditions as simulations require excessive
amounts of processing power and time. Analytical
models are the most suitable tools to obtain insight
into the performance of a MANET protocol. Various
analytical studies of protocol performance exist in
the literature. These studies range from detailed
protocol specific models to more general models that
can be applied to a group of protocols.
III. PROBLEM FORMULATION
The present study aims to achieve efficient
bandwidth and energy utilization for MANETs and
specifically focuses on the MANET and the routing
layers. The key challenges in effective MANET
protocol design are the maximization of spatial reuse
and providing support for non-uniform load
distributions. Spatial reuse is tightly linked to the
bandwidth efficiency. Due to the noisy nature of the
propagation medium, the same channel resources can
be used in spatially remote locations simultaneously
without affecting each other. Incorporating spatial
reuse into the MANET protocol drastically increases
bandwidth efficiency. On the other hand, due to the
dynamic behavior in MANETs, the traffic load may be
highly non-uniform over the network area. Thus, it is
crucial that the MANET protocol be able to efficiently
handle spatially non-uniform traffic loads.
Uncoordinated protocols intrinsically incorporate
spatial reuse and adapt to the changes in load
distribution through the carrier sensing mechanism.
However, coordinated protocols require careful design
at the MANET layer allowing the channel controllers
to utilize spatial reuse and accommodate any changes
in the traffic distribution.
IV.SYSTEM ARCHITECTURE
The present study adapted the following system
architecture (Figure 2) to overcome the above
statement of problems in effective MANET protocol
design.
In the node distribution changes and packet
generation patterns result in a non-uniform load
distribution. Similar to cellular systems, coordinated
MANET protocols need specialized spatial reuse and
channel borrowing mechanisms that address the unique
characteristics of MANETs in order to provide as high
bandwidth efficiency as their uncoordinated
counterparts.
Vol. 16, No. 5, May 2018
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Figure 2: System Architecture
Figure 3 explains the data flow pattern in the
proposed protocol design. Due to node mobility and
the dynamic nature of the sources in a MANET, the
network load oftentimes is not uniformly distributed.
The proposed algorithm for managing non-uniform
load distribution in MANETs into the MH-TRACE
framework and it incorporates spatial reuse which
does not provide any channel borrowing or load
balancing mechanisms. Thus, it does not provide
optimal support to dynamically changing conditions
and non-uniform loads. Hence, intentionally the
present study applies the dynamic channel allocation
and cooperative load balancing algorithms to MH-
TRACE, creating the new protocols of DCA-
TRACE, CMH-TRACE and the combined CDCA-
TRACE.
V. USER INTERFACE
In order to implement the design, the study
considered the internal and external agents as actors.
Figure 4 explains user case diagram which consists of
actors and their relationships. The diagram represents
the system/subsystem of an application. A single user
case diagram captures a particular functionality of a
system. The class diagram (Figure 5) is the main
building block of object oriented modelling. It is used
both for general conceptual modelling of the
systematic of the application, and for detailed
modelling translating the models into programming
code. Class diagrams can also be used for data
modeling.
Figure 3: Data flow diagram
Figure 4: User Case Diagram
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Figure 5: Class Diagram
VI.IMPLEMENTATION PHASE
The performance of reliability of the system was
tested and it gained good level of acceptance. During
the implementation stage a live demon was undertaken
and and made in front of end-users. The stage consists
of the following steps.
• Testing the developed program with sample
data
• Detection and correction of internal error
• Testing the system to meet the user
requirement
• Feeding the real time data and retesting
• Making necessary change as described by the
user
Figure 6 shows the sequence of process operates with
one another and in what order. It is a construct of
a message sequence chart. It also shows object
interactions arranged in time sequence. It depicts the
objects and classes involved in the scenario and the
sequence of messages exchanged between the objects
needed to carry out the functionality of the scenario.
Sequence diagrams are typically associated with use
case realizations in the Logical View of the system
under development. Sequence diagrams are sometimes
called event diagrams or event scenarios.
VII.
Figure 6: Sequence of Process
Figure 7 resembles a flowchart that portrays the roles,
functionality and behavior of individual objects as well
as the overall operation of the system in real time.
Objects are shown as rectangles with naming labels
inside. These labels are preceded by colons and may be
underlined. The relationships between the objects are
shown as lines connecting the rectangles.
The messages between objects are shown as arrows
connecting the relevant rectangles along with labels
that define the message sequencing.
Figure 7: Collaboration Diagram
sendersender RouterRouter ReceiverReceiver
1:senddata
2: Allocatethechannelandchecktheanyoverloadoccureornot
3:overloadoccuredchannelistobedynamicalychanged
4:aftersenddatatoreceiver
5:senddata
Routersender
Receiver
1:senddata
2: Allocatethechannelandchecktheanyoverloadoccureornot
3:overloadoccuredchannelistobedynamicalychanged
4:aftersenddatatoreceiver
5:senddata
Vol. 16, No. 5, May 2018
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VIII.SYSTEM TESTING
As a preliminary testing, the study conducted
the behavioral testing which focuses on the functional
requirements of the software. It enables the software
engineer to derive sets of input conditions that will
fully exercise all functional requirements for a
program. The study attempts to find errors in the
following categories.
• Functional Testing and black box type testing
geared to functional requirements of an
application. This type of testing should be done by
testers. Our project does the functional testing of
what input given and what output should be
obtained.
• System Testing-black box type testing that is based
on overall requirements specifications; covers all
combined parts of a system. The system testing to
be done here is that to check with all the
peripherals used in the project.
• Stress Testing-term often used interchangeably
with ‘load’ and ‘performance’ testing. Also used to
describe such tests as system functional testing
while under unusually heavy loads, heavy repletion
of certain actions or inputs, input of large
numerical values.
• Performance Testing-term often used
interchangeably with ‘stresses’ and ‘load’ testing.
Ideally ‘performance’ testing is defined in
requirements documentation or QA or Test Plans.
Additionally, the study conducted test case design
method which uses the control structure of the
procedural design to derive test cases.. Exercise all
logical decisions on their true and false sides. Execute
all loops at their boundaries and within their
operational bounds. Exercise internal data structures to
ensure their validity. Finally, the study implemented
the most ‘micro’ scale of testing to test particular
functions or code modules. Not always easily done
unless the application has a well designed architecture
with tight code; may require developing test modules
or test harnesses.
IX.LIMITATIONS
The crucial challenges of implementing a MANET
protocol on real hardware. The study simulation do not
accurately reflect many of the challenges encountered
in real implementations such as limited processing
power, clock drift, synchronization, imperfect physical
layers, and cross band interference. The present
research work develops a reusable hardware
framework to evaluate the performance of 10 wireless
protocols, in particular the TRACE protocol for real-
time communication in mobile ad hoc networks. Also,
the testing of TRACE implementation for packet losses
and operation of the TRACE protocol depends on the
cooperation and control information exchange between
the nodes in the network. On the other hand, packet
losses in the system disrupt the availability of such
information. As an attempt, the current study adds
packet loss compensation systems in the TRACE
implementation to increase the robustness of the
implementation against packet losses.
X. CONCLUSION
In the present study did not investigate the effects of
upper layers such as the routing layer and instead
focused on the MANET layer capability and local
broadcasting service. The study concluded that the
packet routing has a significant impact on the load
distribution. Moreover, it can be used alongside with
network coding and simultaneous transmission
techniques for cooperative diversity. In general, joint
optimization of the MANET and routing layers may
enable even more efficient solutions. The investigation
of the effects of routing would be considered as a
future work.
REFERENCES
1. Andrews, J., Shakkottai, S., Heath, R., Jindal, N., Haenggi, M.,
Berry, R., et al. (2008). Rethinking information theory for mobile ad
hoc networks. IEEE Communications Magazine, 46(12), 94–101.
2. Wang, Z., Chen, Y., & Li, C. (2012). Corman: A novel cooperative
opportunistic routing scheme in mobile ad hoc networks. IEEE
Journal on Selected Areas in Communications, 30(2), 289–296.
3. Goldsmith, A., Effros, M., Koetter, R., Medard,
M., Ozdaglar, A., & Zheng, L. (2011). Beyond
shannon: The quest for fundamental performance
limits of wireless ad hoc networks. IEEE
Communications Magazine, 49(5), 195–205.
4. Kannhavong, B., Nakayama, H., Nemoto, Y.,
Kato, N., &Jamalipour, A. (2007). A survey of
routing attacks in mobile ad hoc networks. IEEE
Wireless Communications Magazine, 14(5), 85–
91.
5. Kannhavong, B., Nakayama, H., Kato, N.,
Jamalipour, A., &Nemoto, Y. (2007). A study of a
routing attack in olsr‐based mobile ad hoc
networks. International Journal of
Communication Systems, 20(11), 1245–1261.
Vol. 16, No. 5, May 2018
ISSN 1947-5500

6. Zhou, Y., Zhang, Y., Xie, Y., Zhang, H., Yang,
L. T., & Min, G. (2014). TransCom: A virtual
disk-based cloud computing platform for
heterogeneous services. IEEE Transactions on
Network and Service Management, 11(1), 46–
59.
7. T. Numanoglu, B. Tavli, and W. Heinzelman.
An analysis of coordinated and non-coordinated
medium access control protocols under channel
noise. Military Communications Conference,
2005. MILCOM 2005. IEEE, pages 2642–2648
Vol. 4, Oct. 2005.
8. A. Chandra, V. Gummalla, and J. O. Limb.
Wireless medium access control protocols. IEEE
Communications Surveys and Tutorials, 3:2–15,
2000.
9. P. Mohapatra, J. Li, and C. Gui. Qos in mobile
ad hoc networks. IEEE Wireless
Communications Magazine, 10:44–52, 2003.
10. B. Tavli and W. B. Heinzelman. MH-TRACE:
Multi hop time reservation using adaptive
control for energy efficiency. IEEE Journal on
Selected Areas of Communications, 22(5):942–
953, June 2004.
11. T. Cooklev. Wireless Communication Standarts.
IEEE Press, 2004.
12. J. Karaoguz. High-rate wireless personal area
networks. Communications Magazine, IEEE,
39(12):96–102, Dec 2001.
13. T. Numanoglu, B. Tavli, and W. B. Heinzelman.
The effects of channel errors on coordinated and
non-coordinated medium access control
protocols. In Proceedings of IEEE International
Conference on Wireless and Mobile Computing,
volume 1, pages 58–65, Aug 2005. 261.
14. Bora Karaoglu, Tolga Numanoglu, and Wendi
Heinzelman. Analytical performance of soft
clustering protocols. Ad Hoc Networks, 9(4):635
– 651, 2011.
15. Lifei Huang and Ten-Hwang Lai. On the
scalability of ieee 802.11 ad hoc networks. In
Proceedings of the 3rd ACM international
symposium on Mobile ad hoc networking &
computing, MobiHoc ’02, pages 173–182, New
York, NY, USA, 2002. ACM.
16. IEEE 802.15.3 Working Group. Part 15.3:
Wireless medium access control (MANET) and
physical layer (PHY) specifications for high rate
wireless personal area networks (WPAN). IEEE
Draft Standard, Draft P802.15.3/D16, Feb 2003.
17. Mikko Kohvakka, MauriKuorilehto, Marko
Hännikäinen, and Timo D. Hämäläinen.
Performance analysis of ieee 802.15.4 and
zigbee for largescale wireless sensor network
applications. In Proceedings of the 3rd ACM
international workshop on Performance
evaluation of wireless ad hoc, sensor and
ubiquitous networks, PE-WASUN ’06, pages
48–57, New York, NY, USA, 2006. ACM.
18. M. Rahnema. Overview of the gsm system and
protocol architecture. Communications
Magazine, IEEE, 31(4):92–100, Apr 1993.
19. T. S. Rappaport. Wireless Communications:
Principles and Practice. Prentice Hall, Upper
Saddle River, NJ, USA, 2002.
20. Jason Redi, Bill Watson, Ram Ramanathan,
PrithwishBasu, FabriceTchakountio, Michael
Girone, and Martha Steenstrup. Design and
implementation of a mimo MANET protocol for
ad hoc networking. volume 6248, page 624802.
SPIE, 2006. 262
21. V. Tippanagoudar, I. Mahgoub, and A. Badi.
Implementation of the sensorMANET protocol
for the jist/swans simulator. In Computer
Systems and Applications, 2007. AICCSA ’07.
IEEE/ACS International Conference on, pages
225 –232, may 2007.
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Optimization Algorithm to Control Interference-based Topology Control for Delay-Constrained Mobile Ad-hoc Networks

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