A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A Reverse Localization Scheme for Underwater Acoustic Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time

Research Trend Topic Area on Mobile Anchor Localization: A Systematic Mapping Study

Localization in a dynamic environment is one of the challenges in WSN localization involving dynamic sensor nodes or anchor nodes. Mobile anchors can be an efficient solution for the number of anchors in a 3-dimensional environment requiring more local anchors. The reliability of a localization system using mobile anchors is determined by various parameters such as energy efficiency, coverage, computational complexity, and cost. Various methods have been proposed by researchers to build a reliable mobile anchor localization system. This certainly shows the many research opportunities that can be carried out in mobile anchor localization. The many opportunities in this topic will be very confusing for researchers who want to research in this field in choosing a topic area early. However, until now there is still no paper that discusses systematic mapping studies that can provide information on topic areas and trends in the field of mobile anchor localization. A systematic Mapping Study (SMS) was conducted to determine the topic area and its trends, influential authors, and produce modeling topics and trends from the resulting modeling topics. This SMS can be a solution for researchers who are interested in research in the field of mobile anchor localization in determining the research topics they are interested in for further research. This paper gives information on the mobile anchor research area, the author who has influenced mobile anchor localization research, and the topic modeling and trend that potentially promissing research in the future. The SMS includes a chronology of publications from 2017-2022, bibliometric co-occurrence, co-author analysis, topic modeling, and trends. The results show that the development of mobile anchor localization publications is still developing until 2022. There are 10 topic models with 6 of them included in the promising topic. The results of this SMS can be used as preliminary research from the literacy stage, namely Systematic Literature Review (SLR)

Node localization in underwater sensor networks (UWSN)

This dissertation focuses on node localization in underwater wireless sensor networks (UWSNs) where anchor nodes have knowledge of their own locations and communicate with sensor nodes in acoustic or magnetic induction (MI) means. The sensor nodes utilize the communication signals and the locations of anchor nodes to locate themselves and propagate their locations through the network. For UWSN using MI communications, this dissertation proposes two localization methods: rotation matrix (RM)-based method and the distance-based method. Both methods require only two anchor nodes with arbitrarily oriented tri-directional coils to locate one sensor node in the 3-D space, thus having advantages in a sparse network. Simulation studies show that the RM-based method achieves high localization accuracy, while the distance-based method exhibits less computational complexity. For UWSN using acoustic communications, this dissertation proposes a novel multi-hop node localization method in the 2-D and 3-D spaces, respectively. The proposed method estimates Euclidean distances to anchor nodes via multi-hop propagations with the help of angle of arrival (AoA) measurements. Simulation results show that the proposed method achieves better localization accuracy than existing multi-hop methods, with high localization coverage. This dissertation also investigates the hardware implementation of acoustic transmitter and receiver, and conducted field experiments with the hardware to estimate ToA using single pseudo-noise (PN) and dual PN(DPN) sequences. Both simulation and field test results show that the DPN sequences outperform the single PNs in severely dispersive channels and when the carrier frequency offset (CFO) is high --Abstract, page iv