Localization Algorithm Based on the Relationship Between Trapezoidal Trajectory and Energy Consumption of Mobile Anchor Nodes

IF 8.9 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Wenyan Liu;Xiangyang Luo;Shichang Ding;Shaoyong Du
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引用次数: 0

Abstract

Node localization technology is increasingly receiving extensive attention from academia and industry due to its strong concealment and high fault tolerance in wireless sensor networks (WSNs). Mobile anchor nodes (MANs) assisted localization is often used in existing WSNs. However, assisted localization based on MANs is still a challenging problem. On one hand, it is difficult to determine the number of anchor nodes (ANs) to support the energy required for the entire movement trajectory. On the other hand, unknown nodes (UNs) at the boundary region are difficult to obtain sufficient beacon information for localization. A localization algorithm based on the relationship between trapezoidal trajectory and energy consumption of MANs is proposed to solve this challenging problem in the current research. In the proposed algorithm, we design a trapezoidal trajectory based localization algorithm for MANs (TTLMA) to optimize the movement trajectory of ANs. At the same time, determine the number of ANs by analyzing the relationship between the initial energy of ANs and the energy required by the localization algorithm. Select an appropriate algorithm to locate UNs according to the number of beacon information received by them. We conducted multiple simulations to evaluate the proposed algorithm’s performance. The experimental results indicate that compared with five existing typical localization algorithms, the proposed algorithms have positive advantages in terms of localization error and coverage, with average localization error reduced by 0.15 m–1.16 m, average localization coverage improved by 8%–38%. Moreover, the energy consumption of the proposed algorithm is relatively low, requiring only one AN to traverse the designed trapezoidal trajectory.
基于梯形轨迹与移动锚节点能量消耗关系的定位算法
在无线传感器网络中,节点定位技术因其隐蔽性强、容错性高的特点,越来越受到学术界和工业界的广泛关注。在现有的无线传感器网络中,常用移动锚节点(MANs)辅助定位。然而,基于人工智能的辅助定位仍然是一个具有挑战性的问题。一方面,很难确定支持整个运动轨迹所需能量的锚节点(an)的数量。另一方面,边界区域的未知节点难以获得足够的信标信息进行定位。针对这一难题,提出了一种基于梯形轨迹与能量消耗关系的定位算法。在本算法中,我们设计了一种基于梯形轨迹的MANs定位算法(TTLMA)来优化ANs的运动轨迹,同时通过分析ANs的初始能量与定位算法所需能量的关系来确定ANs的数量。根据UNs接收到的信标信息的数量,选择合适的定位算法。我们进行了多次模拟来评估所提出算法的性能。实验结果表明,与现有的5种典型定位算法相比,本文算法在定位误差和覆盖范围方面具有积极的优势,平均定位误差降低0.15 m ~ 1.16 m,平均定位覆盖率提高8% ~ 38%。此外,该算法的能量消耗相对较低,只需一个AN即可遍历设计的梯形轨迹。
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来源期刊
IEEE Internet of Things Journal
IEEE Internet of Things Journal Computer Science-Information Systems
CiteScore
17.60
自引率
13.20%
发文量
1982
期刊介绍: The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.
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