{"title":"利用双阶段无标度拓扑演化模型增强集群无线传感器网络的入侵容错能力","authors":"Xiuwen Fu;Ye Wang;Xiong Huang;Wenfeng Li","doi":"10.1109/JSEN.2024.3422183","DOIUrl":null,"url":null,"abstract":"Constructing a scale-free topology is an effective method to improve the fault tolerance of wireless sensor networks (WSNs). However, when deploying WSNs in high-value applications, ensuring that the scale-free structure can effectively withstand malicious attacks becomes a major challenge. Therefore, it is necessary to develop a scale-free WSN that not only demonstrates excellent fault tolerance but also exhibits outstanding intrusion tolerance. Based on these considerations, this study proposes a reliable scale-free topology evolution model (STEM) for WSNs. This model consists of two phases: the topology generation phase and the topology optimization phase. In the topology generation phase, STEM generates a scale-free clustered WSN topology to ensure the network’s fault tolerance. In the topology optimization phase, wireless links are rearranged to enhance the network’s intrusion tolerance. It is worth noting that the topology structure constructed by STEM is organized through clustering to ensure its suitability for various task scenarios. Experimental results show that compared to existing scale-free WSN optimization algorithms, the network topology generated by STEM not only enhances the network’s reliability against random faults but also effectively improves the network’s reliability when facing malicious attacks.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing Intrusion Tolerance of Clustered Wireless Sensor Networks Using a Double-Stage Scale-Free Topology Evolution Model\",\"authors\":\"Xiuwen Fu;Ye Wang;Xiong Huang;Wenfeng Li\",\"doi\":\"10.1109/JSEN.2024.3422183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Constructing a scale-free topology is an effective method to improve the fault tolerance of wireless sensor networks (WSNs). However, when deploying WSNs in high-value applications, ensuring that the scale-free structure can effectively withstand malicious attacks becomes a major challenge. Therefore, it is necessary to develop a scale-free WSN that not only demonstrates excellent fault tolerance but also exhibits outstanding intrusion tolerance. Based on these considerations, this study proposes a reliable scale-free topology evolution model (STEM) for WSNs. This model consists of two phases: the topology generation phase and the topology optimization phase. In the topology generation phase, STEM generates a scale-free clustered WSN topology to ensure the network’s fault tolerance. In the topology optimization phase, wireless links are rearranged to enhance the network’s intrusion tolerance. It is worth noting that the topology structure constructed by STEM is organized through clustering to ensure its suitability for various task scenarios. Experimental results show that compared to existing scale-free WSN optimization algorithms, the network topology generated by STEM not only enhances the network’s reliability against random faults but also effectively improves the network’s reliability when facing malicious attacks.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10594744/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10594744/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Enhancing Intrusion Tolerance of Clustered Wireless Sensor Networks Using a Double-Stage Scale-Free Topology Evolution Model
Constructing a scale-free topology is an effective method to improve the fault tolerance of wireless sensor networks (WSNs). However, when deploying WSNs in high-value applications, ensuring that the scale-free structure can effectively withstand malicious attacks becomes a major challenge. Therefore, it is necessary to develop a scale-free WSN that not only demonstrates excellent fault tolerance but also exhibits outstanding intrusion tolerance. Based on these considerations, this study proposes a reliable scale-free topology evolution model (STEM) for WSNs. This model consists of two phases: the topology generation phase and the topology optimization phase. In the topology generation phase, STEM generates a scale-free clustered WSN topology to ensure the network’s fault tolerance. In the topology optimization phase, wireless links are rearranged to enhance the network’s intrusion tolerance. It is worth noting that the topology structure constructed by STEM is organized through clustering to ensure its suitability for various task scenarios. Experimental results show that compared to existing scale-free WSN optimization algorithms, the network topology generated by STEM not only enhances the network’s reliability against random faults but also effectively improves the network’s reliability when facing malicious attacks.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice