Abstract
In recent years, wireless sensor networks (WSNs) have experienced a significant growth as a fundamental part of the Internet of Things (IoT). WSNs nodes constitute part of the end-devices present in the IoT, and in many cases location data of these devices is expected by IoT applications. For this reason, many localization algorithms for WSNs have been developed in the last years, although in most cases the results provided are obtained from simulations that do not consider the resource constraints of the end-devices. Therefore, in this work we present an experimental evaluation of a received signal strength indicator (RSSI)-based localization algorithm implemented on IoT end-devices, comparing its results with those obtained from simulations. We have implemented the fuzzy ring-overlapping range-free (FRORF) algorithm with some modifications to make its operation feasible on resource-constrained devices. Multiple tests have been carried out to obtain the localization accuracy data in three different scenarios, showing the difference between simulation and real results. While the overall behaviour is similar in simulations and in real tests, important differences can be observed attending to quantitative accuracy results. In addition, the execution time of the algorithm running in the nodes has been evaluated. It ranges from less than 10 ms to more than 300 ms depending on the fuzzification level, which demonstrates the importance of evaluating localization algorithms in real nodes to prevent the introduction of large overheads that may not be affordable by resource-constrained nodes.
Highlights
Nowadays wireless sensor networks have become a key technology used in diverse applications such as environmental and disaster area monitoring, security, inventory management, healthcare monitoring, etc
We focus on the fuzzy ring-overlapping range-free (FRORF) [11] algorithm since simulation results demonstrate a good accuracy and a significant improvement compared to ring overlapping based on comparison of RSSI (ROCRSSI) [9] and trilateration [8] localization techniques
We implemented and evaluated a FRORF-based localization algorithm in a real outdoor deployment. This algorithm was modified in order to fit Internet of Things (IoT) end-device constraints, with low memory and computing capabilities
Summary
Nowadays wireless sensor networks have become a key technology used in diverse applications such as environmental and disaster area monitoring, security, inventory management, healthcare monitoring, etc. The resource-constrained sensors that compose these networks collect information about the environment that surrounds them and are interconnected with the rest of the nodes of the network, making this technology a fundamental part of the Internet of Things (IoT) [1]. The rise of IoT applications has caused the appearance of lots of interconnected devices that allow the compilation of large quantities of data using sensor nodes. WAL schemes provide global localization data that can be calculated by the network or by the node to be located. This scheme is Sensors 2019, 19, 3931; doi:10.3390/s19183931 www.mdpi.com/journal/sensors
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