An Implementation of Grouping Nodes in Wireless Sensor Network Based on Distance by Using k-Means Clustering
DOI:
https://doi.org/10.21512/commit.v12i2.4714Keywords:
Wireless Sensor Network, Cluster- Based, k-Nearest NeighbourAbstract
Wireless Sensor Network (WSN) is a network consisting of several sensor nodes that communicate with each other and work together to collect data from the surrounding environment. One of the WSN problems is the limited available power. Therefore, nodes on WSN need to communicate by using a cluster-based routing protocol. To solve this, the researchers propose a node grouping based on distance by using k-means clustering with a hardware implementation. Cluster formation and member node selection are performed based on the nearest device of the sensor node to the cluster head. The k-means algorithm utilizes Euclidean distance as the main grouping nodes parameter obtained from the conversion of the Received Signal Strength Indication (RSSI) into the distance estimation between nodes. RSSI as the parameter of nearest neighbor nodes uses lognormal shadowing channel modeling method that can be used to get the path loss exponent in an observation area. The estimated distance in the observation area has 27.9% error. The average time required for grouping is 58.54 s. Meanwhile, the average time used to retrieve coordinate data on each cluster to the database is 45.54 s. In the system, the most time-consuming process is the PAN ID change process with an average time of 14.20 s for each change of PAN ID. The grouping nodes in WSN using k-means clustering algorithm can improve the power efficiency by 6.5%.
Plum Analytics
References
K. Kaur, R. Sethi, and A. Kaur, “Power efficiency in agriculture using wireless sensor network,” International Journal of Computer Science and Information Technologies, vol. 5, no. 3, pp. 3791–3793, 2014.
N. Pachori and V. Suryawanshi, “Cluster head selection prediction in wireless sensor networks,” International Journal of Computer Science and Information Technologies, vol. 6, no. 2, pp. 1033–1035, 2015.
H. Taheri, P. Neamatollahi, O. M. Younis, S. Naghibzadeh, and M. H. Yaghmaee, “An energy aware distributed clustering protocol in wireless sensor networks using fuzzy logic,” Ad Hoc Networks,
vol. 10, no. 7, pp. 1469–1481, 2012.
W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 660–670, 2002.
M. Razzaq, D. D. Ningombam, and S. Shin, “Energy efficient k-means clustering-based routing protocol for WSN using optimal packet size,” in International Conference on Information Networking (ICOIN). Chiang Mai, Thailand: IEEE, 2018, pp. 632–635.
H. Echoukairi, A. Kada, K. Bouragba, and M. Ouzzif, “A novel centralized clustering approach based on k-means algorithm for wireless sensor network,” in Computing Conference. London,
UK: IEEE, 2017, pp. 1259–1262.
M. Lehsaini and M. B. Benmahdi, “An improved k-means cluster-based routing scheme for wireless sensor networks,” in International Symposium on Programming and Systems (ISPS). Algiers, Algeria: IEEE, 2018, pp. 1–6.
J. Yu, Y. Qi, G. Wang, and X. Gu, “A cluster-based routing protocol for wireless sensor networks with nonuniform node distribution,” AEU – International Journal of Electronics and Communications, vol. 66, no. 1, pp. 54–61, 2012.
R. Patil and V. V. Kohir, “Energy efficient flat and hierarchical routing protocols in wireless sensor networks: A survey,” IOSR Journal of Electronics and Communication Engineering (IOSR–JECE), vol. 11, no. 6, pp. 24–32, 2016.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
a. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License - Share Alike that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
USER RIGHTS
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options, currently being defined for this journal as follows: Creative Commons Attribution-Share Alike (CC BY-SA)
