IAETSD

1. ANALYSIS ON PACKET SIZE OPTIMIZATION
TECHNIQUES IN WIRELESS SENSOR
NETWORKS
1
P. Venkatesh, PG Scholar,
Department of CSE,
Adhiyamaan College of Engineering,
Hosur-635109, Tamil Nadu, India.
1
venkimahalakshmi10@gmail.com
Abstract--The foremost and important issue in wireless Sensor
networks is energy constrained. Packet Size plays an important
role in Wireless Sensor Networks. Large Packet Size may cause
data bit error and also needs higher frequency for Re-transmission
in Wireless Sensor Networks. Compared to large packet size, small
packet size is quite easy-way and also produces an efficient result in
Wireless Sensor Networks. But creation of short packet size might
cause problems like higher overhead and startup energy
consumption for each packet. Consecutively to develop energy
efficient Wireless Sensor Networks, an optimal packet size must be
chosen. In this paper short analysis of various techniques developed
by researchers in this area and computing the performance of
Wireless Sensor Networks has been carried out.
Index Terms--Packet length optimization, link estimation,
aggregation, fragmentation, wireless sensor networks.
I. INTRODUCTION
Wireless Sensor Networks is collection of sensing devices that
can communicate wirelessly. Each device can perform three
important tasks such as, Sense, process and talk to its peers.
Hence it has centralized Collection point (sink or base station).
A WSN can be defined as network devices, denoted as node,
which can sense the environment and communicate through
wireless links. The data is forwarded, possibly via multiple hops
to sink, that can use it’s locally or is connected to other network
(e.g. internet) through gateway. The node can be Stationary or
moving. They can be homogeneous or not [1].
The traditional single-sink WSN may suffer from lack of
scalability. So by increasing large number of nodes, amount of
data gathered by sink increases and once its capacity is reached,
the network cannot be increased. Furthermore, for reasons
related to MAC and routing aspects, network performance
cannot be considered independent from the network size.
Dr. M. Prabu, Professor
Department of CSE,
Adhiyamaan College of Engineering,
Hosur-635109, Tamil Nadu, India
2
prabu_pdas@yahoo.co.in
Fig.1. Architecture of wireless sensor network
As there are many problems in the single sink scenario,
moving to multiple sink scenario can be scalable and also
increase the performance of the WSN in terms of increasing the
number of the nodes, which it not possible in the single sink
scenario. In many cases nodes send the collected data to one
sink, select among many, which forward data to the gateway,
towards the final user. The selection of sink is based on certain
suitable criteria that could be, for example, minimum delay,
maximum throughput, minimum number of hops etc., Hence the
presence of multiple sink ensures better network performance
with respect to single sink case where designing part is more
complex for communication protocol and must design
according to suitable criteria[2].
The WSN can be used for a variety of applications such as
Environment monitoring [3], healthcare, positing [4]and
tracking [5] etc., The applications of the wireless sensor network
can be classified according to the Event Detection (ED) and the
Spatial Process Estimation (SPE) .
INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ENGINEERING RESEARCH, ICDER - 2014
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT www.iaetsd.in
35

2. Fig. 2. Left side Single-sink scenario and Right side Multi-sink-scenario] [2]
In the ED scenario, the sensor is deployed to detect the events
such as, fire in the forest, Earthquake. In SPE scenario it is
deployed to monitor the physical phenomenon (for example
atmospheric pressure in a wide area or temperature variation in a
small volcanic site), which can be modeled as a bi-dimensional
random process (generally non-stationary).
Power consumption plays an important role in the WSN, so the
designers are now mainly focusing on the power aware- protocol
and algorithm for design of energy efficient sensor network. For
all the operations to be performed in the network, such as
sensing information, processing the information and forwarding
to the sink node. Hence the power consumption and power
management are more important in the wireless sensor networks
[1].
II. RELATED WORK
In the WSN packet size is a major problem, which will directly
affect the reliability and the performance of communication
between the nodes. However choosing the packet size must be
optimal. According to the first scenario the packet size is long in
WSN that causes data bit corruption and data packet re-
transmission [6]. Power consumption is also high during the
transmission of data packet to the sink which in turn ultimately
loses the performance of the WSN when the packet size is long.
In second scenario the packet size is small, which increase the
data transmission reliability and reduces the data bit error. But
short packet size degrades the performance of the WSN. Also
management of packet at each node will become complicated.
So many techniques were developed so far to get an optimal
packet size for the WSN, but most of the researchers suggest
fixed packet size [7].The minority researchers are promoting the
use of the dynamic packet length [8] i.e. variable size of data
packets in WSN. In this survey report numbers of techniques
have been discussed to obtain an appropriate data packet size in
WSN and finally the conclusion for each technique.
III. DISCUSSION AND RESULT
Various techniques are used for packet size optimization for
wireless sensor networks. A range of techniques were developed
by the different researcher for the packet size optimization in
WSN.The researchers have majorly focus on the two approaches
which is, either fixed packet size or variable packet size
approach. In this section we discuss those approaches and
results.
A. Fixed size packet in WSN
In the [7] they have used the fixed packet size in WSN rather
than the variable packet size. Even though the variable packet
size will increase the throughput of the channel and enhance the
wireless sensor network transmission mechanism the simplicity
of such independent system is also compromised. Since
choosing the variable packet size leads to the resource
management overhead they choose the fixed size data packets
for energy efficient WSN. Basically, there are three fields in the
data packet.
1) Packet header.
2) Payload/Data Segment.
3) Packet Trailer.
The packet header contains many fields that are usually less
important for WSN nodes and removing those will help us to
reduce the packet size in the WSNs. Those fields include current
segment number, total number of segments, packet identifiers,
source and destination identifiers [7].By employing these
method the overall throughput and efficiency is increased.
Fig 3. Packet format [7]
INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ENGINEERING RESEARCH, ICDER - 2014
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT www.iaetsd.in
36

3. B. Variable Size packet in WSNs
In the [8] variable packet size in WSNs plays a vital role and
this paper describes the creation of packet size according to the
channel condition i.e. in a dynamic manner, they developed a
scheme called dynamic packet length control. In the WSNs if
the channel is noisy or busy (means it is congested having lots
of packets) it will automatically create small packets. When the
channel is empty or channel if it is capable of processing large
packet means it will automatically generate the large packet
size. By using this method they are increasing the overall
throughput and efficiency.
C. Framework for optimization of packet size
There are various researchers who developed lot of frameworks
for creating or generating an optimal packet size for reducing
the energy consumption and to increase the throughput and
energy efficiency in WSN. In this framework [9] for packet
optimization in WSNs, they are describing that the longer packet
size is more appropriate than the shorter packet size in some
case. In certain situation this may lead to inefficiency in the
WSNs. The framework must be employed there to find an
appropriate method for optimal solution to the problem in
wireless sensor networks. The paper [9] used a framework to
find the optimal packet size based on some performance metric.
The metric consists of the throughput, energy consumption per
bit, latency, and packet error rate.
D. Various packet size used in different techniques
In this paper [10], they describe that if small packet size
produces more energy efficient in WSN, overhead of each
packet is ignored. Tracking per packet overhead created in WSN
will lead to favor large size packet for this type of resource
constrained in tiny sensor node. So it depends on overhead
produced by each packet generation in WSN. There are some
suggested packet sizes as follows
Fig. 4. Effect of packet size on the ESB [10]
There are some other packet formats designed by the researchers
for energy efficiency in wireless sensor networks. In the paper
[11] they describe different header formats and researchers
could use predefined formats for designing their own packets.
Designers have to design their packet header using common
header format that is shown in the figure below
Fig. 5. Packet header format [11]
INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ENGINEERING RESEARCH, ICDER - 2014
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT www.iaetsd.in
37

4. In the paper [12], they describe the Dynamic Packet length
control scheme that provides more efficient terms of channel
utilization than the paper [8]. They provide two services, i.e.,
small message aggregation and large message Fragmentation.
By using those services they provide better performance
compared to the previous works. The two service are shown
clearly in the below figure.
Fig. 6. DPLC overview [12]
IV. PROPOSED WORK
The proposed work describes and improves the data aggregation
i.e. decrease the power consumption and increase the life time of
packet send between the two nodes using BEAR protocol. The
data aggregation scheme is used to improve the network
functionality with energy competence. Each and every sensor is
used to minimize the energy consumption. In data aggregation
there are various algorithms used to measure the performance
such as lifetime, data accuracy and latency. To improve the
lifetime of the mobility nodes based on the centralized and
localized algorithm by using the BEAR [A Balanced Energy
Aware Routing] Protocols, the dynamic fixed length packets
lifetime is measured and this protocol increases the coverage
areas to get better performance and where large nodes are to be
used.
Wireless sensor network latency refers to data transmission, data
aggregation and routing. It defines the time delay between the
sink and destination. This paper decides to improve the coverage
areas, lifetime and also decreases the power consumptions by
the protocol. Source node sends packet to destination node
where the source node has the backup and increases the
networks lifetime generated and maintain by the centralized and
localized algorithm. While sending the source node is in off
mode and after receiving the acknowledgement it moves to on
mode so, in this way the energy consumption is minimized,
increases the data size and lifetime and avoids the latency.
V. CONCLUSION
In the Wireless Sensor Networks major factor deciding the
performance, i.e. to choose the packet size leads to efficiency in
energy. There are so many researchers who proposed packet size
format and there are also some framework approaches for the
same. According to above analysis some of the researcher have
encouraged fixed size packet for the data transmission in the
sensor node, whereas at the same time other researchers
encourage variable size packet for data transmission in the
sensor node according to the channel capacity. The former
approaches are easy to implement and process less overhead but
they are inefficient with regards to energy efficiency, overall
throughput and performance. Next approaches are capable with
respect to energy efficiency, throughput and performance but
major drawback is it possess a lot of overhead at each node.
Each and every approaches and framework has their own
negative aspect and the positive aspect. Yet we develop an
optimal approach which combines the advantages of the
previous approach and avoids the drawbacks in those
approaches.
REFERENCES
1. I.F.Akyildiz, W.Su, Y.Sankarasubramaniam and E. Cayirci,
“A Survey on Sensor Networks”, IEEE Communications
Magazine, pp. 102-114, August 2002.
2. Lin, C.; Tseng, Y.; Lai, T. Message-Efficient In-Network
Location Management in a Multi-sink Wireless Sensor
Network. In Proceedings of IEEE International Conference
on Sensor Networks, Ubiquitous, and Trustworthy
Computing, Taichung, Taiwan, 2006; pp. 1–8.
3. Ong, J.; You, Y.Z.; Mills-Beale, J.; Tan, E.L.; Pereles, B.;
Ghee, K. A wireless, passive embedded sensor for real-time
monitoring of water content in civil engineering materials.
IEEE Sensors J.2008, 8, 2053–2058
4. Lee, D.-S.; Lee, Y.-D.; Chung, W.-Y.; Myllyla, R. Vital
sign monitoring system with life emergency event detection
using wireless sensor network. In Proceedings of IEEE
Conference on Sensors, Daegu, Korea, 2006.
5. Hao, J.; Brady, J.; Guenther, B.; Burchett, J.; Shankar, M.;
Feller, S. Human tracking with wireless distributed
pyroelectric sensors. IEEE Sensors J. 2006, 6, 1683–1696.
INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ENGINEERING RESEARCH, ICDER - 2014
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT www.iaetsd.in
38

5. 6. Low Tang Jung, Azween Abdullah, “Wireless Sensor
Networks: Data Packet Size Optimization”, Universiti
Teknologi PETRONAS, Malaysia, 2012.
7. Y. Sankarasubramaniam, I. E Akyildiz and S. W.
Mchughlin, “Energy Efficiency based Packet Size
Optimization in Wireless Sensor Networks”, School of
Electrical & Computer Engineering Georgia, Institute of
Technology, Atlanta, GA 30332, 2003.
8. Wei Dong, Xue Liu, Chun Chen, Yuan He, Gong Chen,
Yunhao Liu, and Jiajun Bu,and Zhejiang Key, “DPLC:
Dynamic Packet Length Control in Wireless Sensor
Networks”, Lab. of Service Robot, College of Comp. Sci.,
Zhejiang University School of Comp. Sci., McGill
University 2010.
9. Vuran, M.C.; Akyildiz, I.F.;, "Cross-Layer Packet Size
Optimization for Wireless Terrestrial, Underwater, and
Underground Sensor Networks," INFOCOM 2008. The 27th
Conference on Computer Communications. IEEE, vol., no.,
pp.226-230, 13-18 April 2008.
10. Matthew Holland, Tianqi Wang, Bulent Tavli, Alireza
Seyedi, and Wendi Heinzelman, “Optimizing physical-layer
parameters for wireless sensor networks”, ACM Trans. Sen.
Netw. 7, 4, Article 28 (February 2011), 20 pages.
DOI=10.1145/1921621.1921622
http://doi.acm.org/10.1145/1921621.1921622.
11. Haboub, Rachid, and Mohammed Ouzzif. "SECURE
ROUTING IN WSN."International Journal 2 (2011).
12. Wei Dong, Member, IEEE, Chun Chen, Member, IEEE,
Xue Liu, Member, IEEE, Yuan He, Member, IEEE, Yunhao
Liu, Senior Member, IEEE, Jiajun Bu, Member, IEEE, and
Xianghua Xu, Member, IEEE” Dynamic Packet Length
Control in Wireless Sensor Networks” IEEE
TRANSACTIONS ON WIRELESS
COMMUNICATIONS, VOL. 13, NO. 3, MARCH 2014.
INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ENGINEERING RESEARCH, ICDER - 2014
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT www.iaetsd.in
39