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

Abstract

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.

A Rescue-Assistance Navigation Method by Using the Underground Location of WSN after Disasters

“…As shown in Figure 6, the ADXL345 is a 3-axis accelerometer with 13bit resolution measurement at up to ±16 g. The ADXL345 is connected to the microprocessor of the sensor node via the SPI bus. The microprocessor receives data through the SPI bus and obtains three acceleration information in the vertical direction, which is used to calculate the sum magnitude vector (SMV) [34], as shown in Equation (12).…”

“…The node localization methods are classified into range-based methods [12] and range-free methods [13]. Generally, range-based methods can provide more accurate location information by using the distance measurement technologies, such as the angle of arrival (AoA), the received signal strength indication (RSSI) and the time of arrival (ToA), which both need to find the mechanisms transferring the measuring angles, strength or time to physical distances.…”