Increase in lifetime by harvested energy and analysis of RC5 along with efficient energy consumption in WBAN

Increase in lifetime by harvested energy and analysis of RC5 along with efficient energy consumption in WBAN

Jayanti P. RudraMrittika Chakraborty 

Department of Information Technology MCKVIE, Howrah 711204, India

Corresponding Author Email: 
pathak.jayanti@rediffmail.com
Page: 
39-44
|
DOI: 
https://doi.org/10.18280/eesrj.040203
Received: 
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Accepted: 
|
Published: 
30 June 2017
| Citation

OPEN ACCESS

Abstract: 

Wireless Body Area Networks (WBANs) have emerged as a new technology for health care systems. It allows the data of a patient’s vital body parameters and movements to be collected by small wearable or implantable sensors and communicated using short-range wireless communication techniques. Limited energy capacity to sustain the WBAN nodes for an extended period of time has always been a matter of concern. In this paper, we compare and analyze different types of standard symmetric cryptography based algorithms to be implemented in WBANs for security purpose. RC5 being a highly efficient and flexible cryptographic algorithm, with many flexible parameters (key size, block size, number of rounds) can be adjusted to tradeoff security strength with power consumption and computational overhead. Thus, RC5 with suitable parameters may perform well for WBAN applications with different data size. We propose an algorithm comprising of operating the sensor nodes in rest modes that is both in sleep as well as active mode accordingly, based on sets of data transmissions. Equal priority is set for all the cluster members (CMs) along with a fixed cluster head (CH). The concept of energy harvesting has also been implemented in our algorithm to maximize the power supply. Increase in the network lifetime using both rest mode and increased energy supply has been observed using different case studies.

Keywords: 

Cluster Head, Cluster Members, Cryptography, Health Care.

1. Introduction
2. RC5 As a Security Solution
3. Concept of Energy Harvesting in WBAN
4. Proposed Algorithm
5. Evaluation of Proposed Algorithm
6. Results
7. Discussions and Analysis
8. Conclusions
Acknowledgement
  References

[1] Kumar J., Ezhilarasi M. (2012). Adaptive security mechanism for PEAS in wireless sensor networks, International Conference on Computing and Control Engineering (ICCCE 2012), ISBN 978-1-4675-2248-9 © 2012.

[2] Qiu M.K., Gao W.Z., Chen M., Niu J.W., Zhang L. (2011). Energy efficient security algorithm for power grid wide area monitoring system, IEEE Transactions on Smart Grid, Vol. 2, No. 4, pp. 715-723.

[3] Rivest R.L. (1994). The RC5 encryption algorithm, Proc. 2nd International Workshop on Fast Software Encryption, Leuven, Belgium, pp. 86-96. DOI: 10.1007/3-540-60590-8_7

[4] Mohammad A.R., Rjoub A., Baset A. (2009). A low-energy security algorithm for exchanging information in wireless sensor networks, Journal of Information Assurance and Security, pp. 48-59.

[5] Vermaand H.K., Singh R.K. (2012). Performance analysis of RC5, blowfish and des block cipher algorithms, International Journal of Computer Applications (0975 – 8887), Vol. 42, No.16.

[6] Yang Z., Mohammed A. (2013). Self-organization and green applications in cognitive radio networks, Al-Dulaimi A., Cosmas J., Mohammed A., Eds, IGI Global, pp. 290-300. DOI: 10.4018/978-1-4666-2812-0

[7] Roundy S., Leland E.S., Baker J., Carleton E., Reilly E., Lai E., Otis B., Rabaey J.M., Wright P.K., Sundararajan V. (2005). Improving power output for vibration-based energy scavengers, IEEE Pervasive Compute., Vol. 4, No. 1, pp. 28-36. DOI: 10.1109/MPRV.2005.14

[8] Hoang D.C., Tan Y.K., Chang H.B., Panda S.K. (2009). Thermal energy harvesting from human warmth for wireless body area network in medical healthcare system, IEEE. DOI: 10.1109/PEDS.2009.5385814

[9] Sohraby K., Minoli D., Znati T. (2007). Wireless sensor networks: technology, protocols, and applications, Lecture Notes in Computer Science, pp. 129-139. DOI: 10.1002/047011276X

[10] Zhang Y., Xiong P., Luo Y., Li L. (2011). Design of remote home environment monitoring and health care monitoring system based on data confusion, 2011 IEEE International Conference on Automation and Logistics (ICAL). DOI: 10.1109/ICAL.2011.6024680 

[11] Hanson M.A., Powell H.C. Jr., Barth A.T., Ringgenberg K., Calhoun B.H., Aylor J.H., Lach J. (2009). Body area sensor networks: challenges and opportunities, Computer, Vol. 42, No. 1, pp. 58-65. DOI: 10.1109/MC.2009.5 

[12] Chen H., Liu M., Hao W., Chen Y., Jia C., Zhang C., Wang Z. (2009). Low-power circuits for the bidirectional wireless monitoring system of the orthopedic implants, IEEE Transactions on Biomedical Circuits and Systems, Vol. 3, No. 6, p.437. DOI: 10.1109/TBCAS.2009.2026283