CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance

by A. H. Mohamed, A. M. Nassar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 170 - Number 8
Year of Publication: 2017
Authors: A. H. Mohamed, A. M. Nassar
10.5120/ijca2017914927

A. H. Mohamed, A. M. Nassar . Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance. International Journal of Computer Applications. 170, 8 ( Jul 2017), 20-24. DOI=10.5120/ijca2017914927

@article{ 10.5120/ijca2017914927,
author = { A. H. Mohamed, A. M. Nassar },
title = { Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2017 },
volume = { 170 },
number = { 8 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 20-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume170/number8/28090-2017914927/ },
doi = { 10.5120/ijca2017914927 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:17:56.404720+05:30
%A A. H. Mohamed
%A A. M. Nassar
%T Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance
%J International Journal of Computer Applications
%@ 0975-8887
%V 170
%N 8
%P 20-24
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the recent years, wireless sensor networks (WSNs), have become essential part in a huge number of the modern applications. Researchers have developed a lot of work to improve their performance. But, practically WSNs still face with different kinds of obstacles those cause main challenges for their reliability. Therefore, finding an optimum obstacle-avoiding route path for the WSNs is considered an important research problem. The present work introduces a new optimum routing algorithm based on the cluster-based method for the WSNs with obstacles. The proposed system uses the cluster-based method and the mobile sink to decrease the power consumptions and increase the lifetime of the WSNs. Besides, it uses the genetic algorithm to optimize the avoiding-obstacles routing path. Suggested system has been applied for a WSN used to communicate between a discovery-radiation robot and its operating system as a case of study. Simulation results for the tested WSN and their comparison with three other route algorithms have proved the effectiveness of the proposed novel method.

References
  1. J. C. Cuevas-Martinez, J. Canada-Bago, J. A. Fernandez-Prieto, and M. A. Gadeo-Martos, (2013), "Knowledge-based duty cycle estimation in wireless sensor networks: Application for sound pressure monitoring'', Applied Soft Computing, vol. 13, no. 2, pp. 967-980.
  2. H.-L. Fu, H.-C. Chen, and P. Lin; (2012), “Aps: Distributed air pollution sensing system on wireless sensor and robot networks”, Computing Communication, vol. 35, no. 9, pp. 1141-1150.
  3. Z. Shen et al.; (2013), “Energy consumption monitoring for sensor nodes in snap'', International Journal Sensor Network, vol. 13, no. 2, pp. 112-120.
  4. B. Zhou, S. Yang, T. H. Nguyen, T. Sun, and K. T. V. Grattan, (Apr. 2014), ''Wireless sensor network platform for intrinsic optical fiber pH sensors'', IEEE Sensors Journal, vol. 14, no. 4, pp. 1313-1320.
  5. M. Dong, X. Liu, Z. Qian, A. Liu, and T. Wang; (Aug. 2015), “QoE-ensured price competition model for emerging mobile networks'', IEEE Wireless Communication., vol. 22, no. 4, pp. 50-57.
  6. P. Chanak, I. Banerjee, J. Wang, and S. Sherratt ; (2014), “ Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices”, IEEE Transactions on Consumer Electronics, 60 (4), pp. 596-604.
  7. GUANGQIAN XIE and FENG PAN, “Cluster-Based Routing for the Mobile Sink in Wireless Sensor Networks With Obstacles“, Vol. 4, 2016, pp. 2019-2028.
  8. Walaa AbdElrouf , Adil Yousif and Mohammed Bakri Bashir, " High Exploitation Genetic Algorithm for Job Scheduling on Grid Computing", International Journal of Grid and Distributed Computing Vol. 9, No. 3, 2016, pp.221-228.
  9. H. M. Sani, and M. M. Yabo", Solving Timetabling problems using Genetic Algorithm Technique", International Journal of Computer Applications (0975 – 8887) Volume 134 – No.15, January 2016.
  10. Veenu Yadav, and Shikha Singh, " Genetic Algorithms Based Approach to Solve 0-1 Knapsack Problem Optimization Problem", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 5, May 2016.
  11. A. Tripathi, P. Gupta, A. Trivedi and R. Kala, “Wireless Sensor Node Placement using Hybrid Genetic Programming and Genetic Algorithms,” International Journal of Intelligent Information Technologies, Vol. 7, No. 2, 2011, pp. 63-83.
  12. G. K. Shwetha, S. Behera, and J. Mungara, ``Energy-balanced dispatch of mobile sensors in hybrid wireless sensor network with obstacles'', IOSR Journal of Computer Engineering, 2012, vol. 2, no. 1, pp. 47-51.
  13. Stojmenovic and X. Lin, “GEDIR: loop-free location-based routing in wireless networks,” in Proc. 11th IASTED Int. Conf. on Parallel and Distributed Computing and Systems, Boston, MA., Nov. 1999, pp. 1025-1028,
  14. B. Karp and H. T. Kung, “GPSR: Greedy perimeter stateless routing for wireless networks,” in Proc. 6th ACM Annu. Int. Conf. Mobile Comput. Boston, MA., pp. 243-254, Aug. 2000.
  15. L. Zou, M. Lu, and Z. Xiong, “A distributed algorithm for the dead-end problem of location-based routing in sensor networks,” IEEE Trans. On vehicular technology, vol. 54, no. 4, July 2005, pp. 1509-1522.
  16. C.-Y. Chang, C.-T. Chang, Y.-C. Chen, and S.-C. Lee, “Active route-guiding protocols for resisting obstacles in wireless sensor networks,” IEEE Trans. on vehicular technology, vol. 59, no. 9, pp. 4425-4442, Nov. 2010.
  17. B. S. Choi and J.-J. Lee, “Sensor network based localization algorithm using fusion sensor-agent for indoor service robot,” IEEE Trans. on consumer electronics, vol. 56, no. 3, pp. 1457-1465, Aug. 2010.
  18. T.Amulya, M.Vedachary, P. Srilaxmi, “Implementation of Surveillance robot with the feature of semi automatic recharging capability,” International Journal of Engineering And Computer Science, Vol. 4, Issue 10, Oct 2015, pp. 14856-14860
  19. C. Sahin, et al., “Design of Genetic Algorithms for Topology Control of Unmanned Vehicles,” International Journal of Applied Decision Sciences, Vol. 3, No. 3, 2010, pp. 221-238.
  20. Y. Qu and S. Georgakopoulos, “Relocation of Wireless Sensor Network Nodes using a Genetic Algorithm,” Proceedings of 12th Annual IEEE Wireless and Microwave Technology Conference (WAMICON), Clearwater Beach, 18-19 April 2011, pp. 1-5.
  21. F. Nematy, N. Rahmani and R. Yagouti, “An Evolutionary Approach for Relocating Cluster Heads in Wireless Sensor Networks,” Proceedings of International Conference on Computational Intelligence and Communication Networks (CICN), Bhopal, 26-28 November 2010, pp. 323-326. http://dx.doi.org/10.1109/CICN.2010.76
  22. N. Rahmani, F. Nematy, A. Rahmani and M. Hossein- zadeh, “Node Placement for Maximum Coverage Based on Voronoi Diagram using Genetic Algorithm in Wireless Sensor Networks,” Australian Journal of Basic and Applied Sciences, Vol. 5, No. 12, 2011, pp. 3221-3232.
  23. L. Cheng, C.-D. Wu, and Y.-Z. Zhang, “Indoor robot localization based on wireless sensor networks,” IEEE Trans. Consum. Electron, vol. 57, no. 3, Aug. 2011, pp. 1099-1104.
  24. Xiaolong Ma and Jie Zhou , " An Extended Shortest Path Problem with Switch Cost Between Arcs", Proceedings of the International MultiConference of Engineers and Computer Scientists 2008 Vol I, IMECS 2008, 19-21 March, 2008, Hong Kong.
  25. O. J. Smith, N. Boland, and Hamish Waterer, " Solving shortest path problems with a weight constraint and replenishment arcs", Computers and Operations Research Journal, Vol. 39 Issue 5, 2012, pp. 964-984.
  26. P. C. S. Rao, P. K. Jana, and H. Banka, "A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks" , Wireless Network, 2016, pp.1-16.
Index Terms

Computer Science
Information Sciences

Keywords

Wireless sensor networks obstacles energy-efficient routing cluster-based genetic algorithm.

Powered by PhDFocusTM