Intersection and Complement Set (IACS) Method to Reduce Redundant Node in Mobile WSN Localization

Harith, Muhammad Zar Mohd Zaid and Noor, Noorzaily Mohamed and Idris, Mohd Yamani Idna and Tamil, Emran Mohd (2018) Intersection and Complement Set (IACS) Method to Reduce Redundant Node in Mobile WSN Localization. Sensors, 18 (7). p. 2344. ISSN 1424-8220, DOI

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The majority of the Wireless Sensor Network (WSN) localization methods utilize a large number of nodes to achieve high localization accuracy. However, there are many unnecessary data redundancies that contributes to high computation, communication, and energy cost between these nodes. Therefore, we propose the Intersection and Complement Set (IACS) method to reduce these redundant data by selecting the most significant neighbor nodes for the localization process. Through duplication cleaning and average filtering steps, the proposed IACS selects the normal nodes with unique intersection and complement sets in the first and second hop neighbors to localize the unknown node. If the intersection or complement sets of the normal nodes are duplicated, IACS only selects the node with the shortest distance to the blind node and nodes that have total elements larger than the average of the intersection or complement sets. The proposed IACS is tested in various simulation settings and compared with MSL* and LCC. The performance of all methods is investigated using the default settings and a different number of degree of irregularity, normal node density, maximum velocity of sensor node and number of samples. From the simulation, IACS successfully reduced 25% of computation cost, 25% of communication cost and 6% of energy consumption compared to MSL*, while 15% of computation cost, 13% of communication cost and 3% of energy consumption compared to LCC.

Item Type: Article
Funders: University of Malaya for the financial support (University Malaya Research Grant (RP036 (A, B, C)-15AET)
Uncontrolled Keywords: computation cost; communication cost; energy; localization; Monte Carlo; WSN
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 19 Aug 2019 01:34
Last Modified: 19 Aug 2019 01:34

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