Call for Paper - January 2019 Edition
IJCA solicits original research papers for the January 2019 Edition. Last date of manuscript submission is December 20, 2018. Read More

Optimal Duty Cycling with Sleep-wake Schedule between Paired Nodes and Flexible Routing across Pairs

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Ginish, Munish Kumar, Amit Grover
10.5120/ijca2016910419

Ginish, Munish Kumar and Amit Grover. Optimal Duty Cycling with Sleep-wake Schedule between Paired Nodes and Flexible Routing across Pairs. International Journal of Computer Applications 144(8):20-24, June 2016. BibTeX

@article{10.5120/ijca2016910419,
	author = {Ginish and Munish Kumar and Amit Grover},
	title = {Optimal Duty Cycling with Sleep-wake Schedule between Paired Nodes and Flexible Routing across Pairs},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {144},
	number = {8},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {20-24},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume144/number8/25200-2016910419},
	doi = {10.5120/ijca2016910419},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The sensor networks consist of the smaller sensor nodes which automatically constructs the routes between themselves to form the data delivery paths.There are several methods of energy conservation such as clustering, routing, duty cycling and many others. The duty cycling or sleep wake cycling is incorporated for the minimization for energy consumption. The effective duty cycling procedure requires the optimal selection of the sleep wake pairs adaptively constructed between the nodes, out of which one node goes sleep and another stays wake a particular point of time. In this paper, the adaptive optimal pairing with flexible routing has been utilized for the purpose of duty cycling in the sensor nodes. The proposed model has undergone several experiments and performed to be efficient enough. The proposed model has outperformed the previous models for duty cycling.

References

  1. Zhu, Chunsheng, Victor Leung, Laurence T. Yang, and Lei Shu. "Collaborative location-based sleep scheduling for wireless sensor networks integrated with mobile cloud computing." (2014).
  2. H. T. Dinh, C. Lee, D. Niyato, and P. Wang, “A survey of mobile cloud computing: Architecture, applications, and approaches,” Wireless Commun. Mobile Comput. vol. 13, no. 18, pp. 1587–1611, Dec. 2013.
  3. S. Wang and S. Dey, “Adaptive mobile cloud computing to enable rich mobile multimedia applications,” IEEE Trans. Multimedia, vol. 15, no. 4, pp. 870–883, Jun. 2013.
  4. R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, “Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility,” Future Generation Comput. Syst., vol. 25, no. 6, pp. 599–616, Jun. 2009.
  5. C. Zhu, L. Shu, T. Hara, L. Wang, S. Nishio, and L. T. Yang, “A survey on communication and data management issues in mobile sensor networks,” Wirel. Commun. Mob. Comput., vol. 14, no. 1, pp. 19–36, Jan. 2014.
  6. M. Li and Y. Liu, “.Underground coal mine monitoring with wireless sensor networks,” ACM Trans. Sens. Netw, vol. 5, no. 2, Mar. 2009
  7. M. Yuriyama and T. Kushida, “Sensor-cloud infrastructure - physical sensor management with virtualized sensors on cloud computing,” in Proc. 13th Int. Conf. Netw.-Based Inf. Sys. (NBiS), 2010, pp. 1–8.
  8. G. Fortino, M. Pathan, and G. D. Fatta, “Bodycloud: Integration of cloud computing and body sensor networks,” in Proc. IEEE 4th Int. Conf. Cloud Comput. Technol. Sci. (CloudCom), 2012, pp. 851–856.
  9. R. Hummen, M. Henze, D. Catrein, and K. Wehrle, “A cloud design for user-controlled storage and processing of sensor data,” in Proc. IEEE 4th Int. Conf. Cloud Comput. Technol. Sci. (CloudCom), 2012, pp. 232–240.
  10. Y. Takabe, K. Matsumoto, M. Yamagiwa, and M. Uehara, “Proposed sensor network for living environments using cloud computing,” in Proc. 15th Int. Conf. Netw.-Based Inf. Sys. (NBiS), 2012, pp. 838–843.

Keywords

Sleep wake scheduling, duty cycling, smart routing, and flexible routing across pairs.