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

Submit your paper
Know more
Reseach Article

An Efficient Clustering of Sensors using a Meta Heuristic Algorithm for IoT

by Varsha Deshpande
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 173 - Number 8
Year of Publication: 2017
Authors: Varsha Deshpande
10.5120/ijca2017915388

Varsha Deshpande . An Efficient Clustering of Sensors using a Meta Heuristic Algorithm for IoT. International Journal of Computer Applications. 173, 8 ( Sep 2017), 30-35. DOI=10.5120/ijca2017915388

@article{ 10.5120/ijca2017915388,
author = { Varsha Deshpande },
title = { An Efficient Clustering of Sensors using a Meta Heuristic Algorithm for IoT },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2017 },
volume = { 173 },
number = { 8 },
month = { Sep },
year = { 2017 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume173/number8/28357-2017915388/ },
doi = { 10.5120/ijca2017915388 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:20:45.005365+05:30
%A Varsha Deshpande
%T An Efficient Clustering of Sensors using a Meta Heuristic Algorithm for IoT
%J International Journal of Computer Applications
%@ 0975-8887
%V 173
%N 8
%P 30-35
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, with the increase in the devices like Smartphone’s, Global Positioning System (GPS) monitoring devices, tablets, surveillance cameras etc...The numbers of devices that have been connected to the Internet have crossed the world population. The decrease in the cost of the devices, with increase in their capability was one of the major reasons for this change. With the increase in the devices connected to the network, there is enormous data that is produced by the devices on daily basis which has caused problem of selecting the devices (sensors) based on the data produced by them. The users have to face the problem of manually selecting the set of sensors required by them. To target this problem, the proposed work has implemented, the ant based clustering algorithm with some novel changes in order to provide the user with the optimal set of sensors. The algorithm intakes the whole sensor space and outputs the clusters from which the user can choose the one which is most optimal according to the user needs. The antclust algorithm strives to provide optimal solution and maintain its performance while fighting the dynamicity of the Internet. The proposed work shows better scalability and adaptability. Also has faster search of the sensors than the other works previously proposed.

References
  1. J. Cooper, A. James, Challenges for database management in the internet of things, IETE Tech. Rev. 26 (5) (2009) 320–329.
  2. J. Holler, V. Tsiatsis, C. Mulligan, S. Avesand, S. Karnouskos, D. Boyle, From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence, Academic Press, 2014.
  3. Mohammad Ebrahimi , Elaheh ShafieiBavani , Raymond K. Wonga, Simon Fong and Jinan Fiaidhi “An adaptive meta-heuristic search for the internet of things” accepted on December 2015. Springer.
  4. B.M. Elahi, K. Romer, B. Ostermaier, M. Fahrmair, W. Kellerer, Sensor ranking: A primitive for efficient content-based sensor search, in: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks, IEEE Computer Society, 2009, pp. 217– 228.
  5. B. Ostermaier, K. Romer, F. Mattern, M. Fahrmair, W. Kellerer, A real-time search engine for the web of things, in: Internet of Things (IOT), 2010, IEEE, 2010, pp. 1–8.
  6. C. Truong, K. Romer, K. Chen, Fuzzy-based sensor search in the web of things, in: 2012 3rd International Conference on the Internet of Things (IOT), IEEE, 2012, pp. 127–134
  7. J.-P. Calbimonte, H. Jeung, O. Corcho, K. Aberer, Semantic sensor data search in a large-scale federated sensor network.
  8. D. Le-Phuoc, H.N.M. Quoc, J.X. Parreira, M. Hauswirth, The linked sensor middleware-connecting the real world and the semantic web, in: Proceedings of the Semantic Web Challenge 152
  9. K. Aberer, M. Hauswirth, A. Salehi, Infrastructure for data processing in largescale interconnected sensor networks, in: 2007 International Conference on Mobile Data Management, IEEE, 2007, pp. 198–205.
  10. S. Nath, J. Liu, F. Zhao, Sensormap for wide-area sensor webs, computer 40 (7) (2007) 90–93.
  11. C. Perera, A. Zaslavsky, C.H. Liu, M. Compton, P. Christen, D. Georgakopoulos, Sensor search techniques for sensing as a servicearchitecture for the internet of things, IEEE Sens. J. 14 (2) (2014) 406–420.
  12. Monika, Sneha Chauhan, Nishi Yadav LEACH-I Algorithm for WSN 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015)
  13. Rohini Sharma, Narendra Mishra and Dr. Sumit SrivastavabA proposed energy efficient distance based cluster head (DBCH) Algorithm: An Improvement over LEACH. Elsevier, Procedia Computer Science 57 ( 2015 ) 807 – 814
  14. E.D. Lumer, B. Faieta, Diversity and adaptation in populations of clustering ants, in: Proceedings of the Third International Conference on Simulation1 of Adaptive Behavior: From Animals to Animats 3: From Animals to Animats 3, SAB94, MIT Press, Cambridge, MA,USA,1994,pp.501–508.URL http://dl.acm.org/citation.cfm?id=189829.190043
  15. A.P. Sheth, and J.A. Larson, "Federated database systems and managing distributed, heterogeneous and autonomous databases", ACM ComputingSurveys, vol. 22, 3, 1990, pp. 183-226.
  16. A.L. Vizine, L.N. de Castro, E. Hrusch, Towards improving clustering ants: an adaptive ant clustering algorithm, Informatica 29 (2) (2005).
  17. J.-L. Deneubourg, S. Goss, N. Franks, A. Sendova-Franks, C. Detrain, L.Chrétien, The dynamics of collective sorting robot-like ants and ant-like robots, in: Proceedings of the First International Conference on Simulation of Adaptive Behavior on From Animals to Animats, 1991, pp.356–363.
Index Terms

Computer Science
Information Sciences

Keywords

AntClust Contiki Cooja Internet of Things (IoT)