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Cluster Based Energy Routing System for
Wireless Sensor Networks
Ifrah Farrukh Khan and Muhammad Younus Javed Department of Computer Engineering, National University of Sciences & Technology (NUST), College of Electrical
and Mechanical Engineering, Rawalpindi, Pakistan.
Email: {ifrahkhan, myjaved }@ceme.nust.edu.pk
Abstract—Wireless Sensor Network has become part of
everyday life. Due to very small size of sensor nodes and
their limited battery power a lot of work has been done in
the area of energy management. Many routing protocols
have been developed for using battery power efficiently but
these protocols sacrifice QoS for this energy efficiency.
Energy Harvesting technologies have been proposed to
improve the lifetime of sensor nodes. Sensor nodes are
charged by using environmental sources such as light, wind,
vibration etc. These energy harvesting technologies have
been combined with energy transference methods for
transference of energy from one node to another. The new
area of research is multi hop energy transference and
algorithms for energy routing. This research paper is about
a cluster based architecture that can help in transporting
energy easily and efficiently from one node to another; an
algorithm has been designed for charging the nodes before
depleting their entire energy.
Index Terms—battery charging, energy efficiency, routing,
wireless sensor networks.
I. INTRODUCTION
Wireless Sensor Networks (WSNs) are composed of
tiny autonomous sensor nodes. These sensor nodes have
different sensing capabilities such as vibration sensing,
temperature sensing, light sensing etc. Sensor networks
are rapidly becoming part of everyday life. Main
applications of WSNs are military deployment, security
surveillance, patient information (Body area networks),
weather forecasting system etc. Due to the smaller size of
a sensor node it has limited processing capabilities, small
storage space and very limited battery power. Main
research area of WSN is energy efficiency. Many
researchers have developed different energy efficient
routing protocols, to increase the network life time [1]-[8].
Creation of routing holes [9], [10] show that energy
efficient routing is not adequate, so the new research area
i.e energy harvesting emerged. Many researchers have
proposed different methods of energy harvesting from the
sources such as wind, light, vibration, solar energy etc.
[11], [12], [13]. Energy harvesting only gives support to
the nodes present in energy rich areas and the nodes in
poor environmental conditions suffer from total energy
drainage. Energy transfer mechanism has been proposed
Manuscript received July 30, 2013; revised October 11, 2013
to provide energy to the neighbor nodes that are unable to
harvest energy for themselves [14]-[16]. Only one hop
energy transfer is not the complete solution because many
nodes farther from the transference node cannot survive.
Energy routing [17], [18] is the new research area that
can provide energy to all the nodes present in the network.
In this research paper a cluster based approach is
presented in which clusters are created on the basis of the
availability of transference node. A hybrid energy
transference technology is implemented i.e sunlight
reflection and magnetic resonance. Rest of the paper is
organized as follows, section 2 explains the available
energy transference techniques, section 3 is about the
research work done by other researchers, section 4 is
about the proposed system and the last section is about
the conclusions drawn and the planned future work.
II. ENERGY TRANSFERENCE TECHNIQUES
Energy can be easily transferred from one node to
another by using wires but in case of WSN it is not
suitable. In WSNs nodes are deployed in a random
topology and they can also be dropped using aircraft. The
nodes may be present in uneven places and at different
distances from each other. Hence wireless energy
transference is preferred in these kinds of networks.
Wireless energy transference is of different types such as
microwave, magnetic resonance, Laser/ LED light and
Reflected sunlight. All of these techniques have their pros
and cons.
Microwaves are the electromagnetic waves,
wavelength of these electromagnetic waves is between
0.01m and 3m. Frequency of these waves is between 30
GHz and 0.1 GHz. Microwaves can charge battery at
distances more than 2km and upto 80% charging
efficiency can be achieved. But due to safety hazards for
human life these waves are not used in most of the
scenarios.
Electromagnetic resonance is transference of energy
using coils. In this technique electromagnetic field is
created in one coil by passing electric current through it
while the second coil being affected by this
electromagnetic field produces induced current.
Electromagnetic resonance is safe for human life. Upto
90% charging efficiency can be achieved and the
effective distance is about 1 to 2 km. Reflected sunlight is
energy harvesting by using sunlight and transferring it to
International Journal of Materials Science and Engineering Vol. 1, No. 2 December 2013
harvesting panel and also provide extra input for another
energy harvester.
V. CONCLUSION AND FUTURE WORK
Working of wireless sensor network can be improved by providing charging nodes to the energy deficient nodes of the network. Sunlight is the most powerful source of energy for charging the battery of the sensor nodes. But few nodes cannot be charged by using this
source of energy so the next most suitable option is magnetic resonance. High charging efficiency can be attained by using the combination of these two techniques. Life time of wireless sensor network can be considerably improved. Implementation of simulation of this proposed system using a suitable network simulator is in progress and results will be published as soon as they are produced. Implementation of this system on real sensor network is in future consideration.
APPENDIX A FLOW DIAGRAM
REFERENCES
[1] K. Akkaya and M. Younis, “A Survey on routing protocols for wireless sensor networks,” Elsevier Journal of Ad Hoc Networks.
vol. 3 i3. pp. 325-349.
[2] K. Akkaya and M. Younis, “Energy and QOS aware routing in wireless sensor networks,” Source Cluster Computing Archive, vol.
8, no. 2-3, pp. 179 – 188, 2005. [3] V. Rahunathan, C. Schurgers, S. Park, and Mani B. Srivastava,
“Energy aware wireless sensor networks,” Dept of Elec Eng, Uni
of California, L. A, 2004, pp. 1-17. [4] Y. Yu, D. Estrin, and R. Govindan, “Geographical and energy
aware routing: A recursive data dissemination algorithm for wireless sensor networks,” UCLA-CSD, Technical Report TR- 01-
0023, May 2001.
[5] R. Haider and Dr. M. Younas Javed, “EAGR: Energy aware greedy routing in sensor networks,” Future Generation
Communication and Networking, vol. 2, pp. 344349-344349, Dec.
2007.
[6] B. Karp and H. Kung, “Gpsr: Greedy perimeter stateless routing
for wireless networks,” in ACM MOBICOM, Boston, August 2000.
[7] H. Hassanein and J. Luo, “Reliable energy aware routing in
wireless sensor networks,” in Proc. Second IEEE Workshop on Dependability and Security in Sensor Networks and Systems, 2006,
pp. 54-64. [8] J. Chen, R. Lin, Y. Li, and Y. Sun, “LQER: A link quality based
routing for wireless sensor networks,” Sensors, vol. 8, pp. 1025-
1038, 2008. [9] N. Ahmed, Salil S. Kanhere, and S Jha, “The holes problem in
wireless sensor networks a survey,” SIGMOBILE Mob. Comp. Comm. Rev., vol. 9, no. 2, pp. 4-18, 2005.
[10] Q. Fang, J. Gao, and L. J. Guibas, “Locating and bypassing
routing holes in sensor networks,” IEEE INFOCOM, 2004. [11] X. F. Jiang, J. Polastre, and D. Culler. “Perpetual environmentally
powered sensor networks,” in Proc. 4th International Symposium on Information Processing in Sensor Networks, Piscataway, IEEE
Press, NJ, USA, 2005, pp. 65.
[12] A. Kansal and M. B. Srivastava, “An environmental energy harvesting framework for sensor networks,” in Proc. 2003
International Symposium on Low Power Electronics and Design,
Seoul, Korea, ACMPress, 2003, pp. 481-486.
[13] C. Park and P. H. Chou, “AmbiMax: Autonomous energy
harvesting platform for multi-supply wireless sensor nodes,” IEEE SECON, vol. 1, pp. 168-177, September 2006.
International Journal of Materials Science and Engineering Vol. 1, No. 2 December 2013