A Data Collection Strategy for Heterogeneous Wireless Sensor Networks Based on Energy Efficiency and Collaborative Optimization

Wang, Zhaoxia; Yue, Yinggao; Zhang, Yong

doi:10.1155/2021/9808449

Cited by 5 publications

(2 citation statements)

References 41 publications

(59 reference statements)

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“…Parameter I 2 is the network connectivity rate calculated by formula (23). The network capacity I 3 is the network survival probability, which generally represents the ratio of the current network node survival nodes to the number of all nodes [ 38 ]. The comparison of the network reliability of the four algorithms is shown in Figure 10 .…”

Section: Experimental Simulation Comparison and Analysismentioning

confidence: 99%

A Data Collection Method for Mobile Wireless Sensor Networks Based on Improved Dragonfly Algorithm

Yue

Zhang

et al. 2022

Computational Intelligence and Neuroscience

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For the sensing layer of the Internet of Things, the mobile wireless sensor network has problems such as limited energy of the sensor nodes, unbalanced energy consumption, unreliability, and long transmission delay in the data collection process. It is proved by mathematical derivation and theory that this is a typical multiobjective optimization problem. In this paper, the optimization goal is to minimize the energy consumption and improve the reliability under time-delay constraints and propose a path optimization mechanism to optimize the mobile Sink of mobile wireless sensor networks based on the improved dragonfly optimization algorithm. The algorithm takes full advantage of the abundant storage space, sufficient energy, and strong computing power of the mobile Sink to ensure network connectivity and improve network communication efficiency. Through simulation comparison and analysis, compared with random movement method, artificial bee colony algorithm, and basic dragonfly optimization algorithm, the energy consumption of the network is reduced, the lifespan of the network is increased, and the connectivity and transmission delay of the network are improved. The proposed algorithm balances the energy consumption of the sensors nodes to meet the network service quality and improve the reliability of the network.

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Section: Experimental Simulation Comparison and Analysismentioning

confidence: 99%

A Data Collection Method for Mobile Wireless Sensor Networks Based on Improved Dragonfly Algorithm

Yue

Zhang

et al. 2022

Computational Intelligence and Neuroscience

Self Cite

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“…As the most flexible and extensible network structure in the wireless communication technologies, WSNs can support potential surveillance and control applications throughout the power network [ 12 – 14 ]. For example, on the generation side of the power system, the applications for WSNs include the monitoring thermal power plants, wind farms, photovoltaic panels, and various types of distributed generation equipment [ 15 , 16 ]. In the power transmission, substation, and distribution side of power systems, the applications of WSNs include the monitoring overhead transmission lines, the underground transmission lines, wire towers, utility poles, and various substations and substation equipment.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Prospect of the Application of Wireless Sensor Networks in Ubiquitous Power Internet of Things

Wang

Yue

2022

Computational Intelligence and Neuroscience

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With the rapid development of the economy and society, the low efficiency and high loss of the traditional power grid can no longer meet the growing social demand, and the power grid market is facing a reform. Smart grid, as a next-generation power system, it can effectively improve the performance of traditional power grids. The ubiquitous power Internet of Things (UPIOT) replaces the traditional grids with efficient, safe, reliable, and flexible new grids, improves the utilization efficiency of the grid, reduces the loss of the power grid in the transmission process, and can meet the needs of different types of markets and users. As an advanced information acquisition and processing technology, wireless sensor networks have been widely used in medical, industrial, agricultural, commercial, and public management fields. It is an important means to promote future economic development and build a harmonious society. In the power system, wireless sensor network technology can be widely used in many fields such as line fault location, real-time monitoring, smart meter reading, and relay protection. In this paper, the basic concepts and overall architecture of ubiquitous power Internet of Things are summarized. Then, we summarize the research status of the wireless sensor network in smart grid, including power equipment, line monitoring, smart grid wireless automatic meter reading, distribution network relay protection, power assets life-cycle management, power grid fault location, and power grid fault diagnosis. In view of the technical characteristics of wireless sensor networks, combined with the production links of power systems, the application framework of wireless sensor network technology in the power systems is constructed. The application of wireless sensor networks is prospected from the aspects of network development of relay protection, application research of smart substation, application research of power grid catastrophe, security protection of power system, and deep-seated ubiquitous power Internet of Things.

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A Data Collection Strategy for Heterogeneous Wireless Sensor Networks Based on Energy Efficiency and Collaborative Optimization

Cited by 5 publications

References 41 publications

A Data Collection Method for Mobile Wireless Sensor Networks Based on Improved Dragonfly Algorithm

A Data Collection Method for Mobile Wireless Sensor Networks Based on Improved Dragonfly Algorithm

Analysis and Prospect of the Application of Wireless Sensor Networks in Ubiquitous Power Internet of Things

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