Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review

Gumaida, Bassam and Ibrahim, Adamu Abubakar (2025) Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review. International Journal of Innovative Computing, 15 (1). pp. 1-15. ISSN 2180-4370

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Abstract

During the last two decades, Wireless Sensor Networks (WSNs) have attracted significant attention from researchers and sensor manufacturing companies alike. WSNs find applications in various environmental monitoring tasks such as weather monitoring, temperature observation, humidity measurement, and military surveillance. These networks typically consist of hundreds to thousands of sensor nodes deployed across the target area. Each sensor node is responsible for collecting specific data and transmitting it to the processing center. However, several constraints, including power consumption, energy-saving measures, and deployment costs, limit the functionality of sensor nodes. Additionally, the accuracy of transmitted data is influenced by the surrounding environment. This paper provides an overview of localization algorithms, including centralized and distributed algorithms. It also delves into distance measurement techniques such as Time of Arrival (ToA), Time Difference of Arrival (TDoA), Angle of Arrival (AoA), and Received Signal Strength Indicator (RSSI). Methodologies of localization, such as range-based and range-free approaches, are discussed, along with various range-based localization techniques like Sum-Dist-Min-Max, Bounding box, geometric methods, and general techniques. The paper also examines influencing factors such as noise, path loss, propagation model, connectivity, and device limitations and their impact on localization measurements. The primary objective of this paper isto review localization algorithms based on metaheuristic optimization techniques to improve localization accuracy. This paper serves as a comprehensive background on localization algorithms and methods used in wireless sensor networks, offering insights for researchers to develop efficient localization algorithms tailored to specific application requirements in diverse work environments.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Wireless Sensor Networks, Ranging Model, RSSI, Optimization Techniques, Localization Techniques, Measurement influencing factorsI. INTRODUCTIONThe development of Wireless Sensor Networks (WSNs) has seen rapid growth over the past two decades, driven by advancements in wireless communication and sensing devices. WSNs, comprising distributed nodes numbering from hundreds to thousands, find applications in various environments such as environment monitoring, wildlife tracking, healthcare, military surveillance, and infrastructure maintenance in factories [1], [2], [3]. Despite their wide-ranging applications, WSNs face several limitations including node battery depletion, hardwareissues, node detection, node position estimation, network expansion, and deployment costs. One significant challenge is the coverage capacity of sensor nodes.Localization, or determining the location information of sensed data, is crucial for many WSN applications to make the collected data meaningful. Localization algorithms play a vital role in applications such as monitoring, tracking, and geographic routing, which require accurate node coordinates. These algorithms aim to assign geographic coordinates to all sensed data collected from sensor nodes within the WSN area to effectively manage and respond to them [4], [5]. The growing reliance on devices and sensed data necessitates more efficient and accurate localization methods. Traditional localization techniques face challenges in accurately and cost-effectively localizing all devices and Sensor Nodes (SNs), particularly in large deployment areas common in Internet of Things (IoT) applications. To address these challenges, optimization techniques and mobile anchors have been proposed to estimate device positions more effectively.
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Dr Adamu Abubakar
Date Deposited:	13 Oct 2025 15:28
Last Modified:	13 Oct 2025 15:28
URI:	http://irep.iium.edu.my/id/eprint/123682

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