JACIII Vol.17 No.4 pp. 622-627
doi: 10.20965/jaciii.2013.p0622


Resource-Aware Clustering Based AODVjr Routing Protocol in the Internet of Things

Xiaoni Wang*,**

*School of Applied Science, Beijing Information Science and Technology University, No.12, Qing He Xiao Ying East Road, Haidian District, Beijing, China

**Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing, China

October 28, 2012
May 6, 2013
July 20, 2013
internet of things, resource-aware, clustering, RA-cluster, AODVjr

Through ad hoc routing protocol AODVjr and resource-aware data mining algorithms research, a resource-aware clustering based routing protocol in the Internet of Things, RA-AODVjr, is proposed. It solves the short comings of the constrained resources of memory, computing power, and the power energy of the wireless sensor’s terminal node in the Internet of Things. RA-AODVjr protocol is designed combining with the RA-cluster and AODVjr routing protocol. This protocol selects the best neighbor in the terminal node and balances the network traffic when terminal node resource is constrained, using the relevance of the ad hoc network. The simulation results show that the agreement achieves load balancing of energy constrained nodes to a certain extent. Compared with the original AODVjr protocol, due to the best neighbor node delivery technology, the local network traffic gets a better balance and less time delay means better choice of routing.

Cite this article as:
X. Wang, “Resource-Aware Clustering Based AODVjr Routing Protocol in the Internet of Things,” J. Adv. Comput. Intell. Intell. Inform., Vol.17, No.4, pp. 622-627, 2013.
Data files:
  1. [1] M.M. Gaber and P. S. Yu, “A framework for resource-aware knowledge discovery in data streams: A holistic approach with its application,” Proc. of the ACM Symp. on Applied Computing, ACM Press, pp. 649-656, 2006.
  2. [2] N. D. Phung, M. M. Gaber, and U. Roehm, “Resource-aware Online Data Mining in Wireless Sensor Networks,” Proc. of the IEEE Symp. Computational Intelligence and Data Mining, Honolulu, USA, pp. 139-146, 2007.
  3. [3] C. E. Perkins, E. M. Royer, and S. R. Das, “Ad Hoc On Demand Distance Vector(AODV) Routing,” RFC, 3561, July 2003.
  4. [4] S.-J. Lee, E. M. Belding-Royer, and C. E. Perkins, “Scalability Study of the Ad hoc on-demand Distance Vector Routing Protocol,” Int. J. of Network Management, Vol.13, Iss. 2, pp. 97-114, 2003.
  5. [5] I. D. Chakeres and L. Klein-Bemdt, “AODVjr, AODV simplified,” Mobile Computing and Communication Review, Vol.6, Iss.3, pp. 100-101, 2002.
  6. [6] F. Wang, Q.-L. Chai, and Y.-L. Ban, “Improved routing algorithm for ZigBee mesh networks,” J. of Computer Applications, Vol.28, No.11, pp. 2788-2790, 2008.
  7. [7] X.-L. Zhang, and W. Zeng, “Research and advances of real-time data stream clustering,” Computer Engineering and Design, Vol.30, No.9, pp. 2177-2181, 2009.
  8. [8] K. Fall and K. Varadhan, “The NS Manual,” California: UC Berkeley Press, 2007.

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Last updated on Jun. 18, 2019