{"title":"一种基于优先级的医疗保健无线传感器网络拥塞避免方案","authors":"Neda Mazloomi, Majid Gholipour, Arash Zaretalab","doi":"10.1049/wss2.12046","DOIUrl":null,"url":null,"abstract":"<p>One of the most important challenges of wireless sensor networks is controlling network congestion and transmitting data in a way that improves the quality of service (QoS) parameters. Thus, it increases network performance and reduces energy consumption. Energy consumption increases due to various reasons, such as unsuccessful delivery of packets to the receiver, congestion in the network, retransmission of packets, delay in delivering packets to the base station, and so on. Given the importance of some data in the field of health, congestion should be avoided and secure data transmission should be ensured. This study divides the collected data into two groups based on their intrinsic characteristics by presenting a congestion management protocol: (1) critical data and (2) non-critical data. The proposed protocol provides a dynamic routing algorithm based on the TOPSIS model for non-critical data transmission. In addition, an algorithm for transmitting critical data through the shortest possible path is also provided based on support vector machines (SVMs). This improves the network performance through using multi-classification that is obtained from SVMs. The simulation results indicate that the proposed method works better than other methods and leads to better performance in delay, network performance, and power consumption.</p>","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12046","citationCount":"1","resultStr":"{\"title\":\"A priority-based congestion avoidance scheme for healthcare wireless sensor networks\",\"authors\":\"Neda Mazloomi, Majid Gholipour, Arash Zaretalab\",\"doi\":\"10.1049/wss2.12046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>One of the most important challenges of wireless sensor networks is controlling network congestion and transmitting data in a way that improves the quality of service (QoS) parameters. Thus, it increases network performance and reduces energy consumption. Energy consumption increases due to various reasons, such as unsuccessful delivery of packets to the receiver, congestion in the network, retransmission of packets, delay in delivering packets to the base station, and so on. Given the importance of some data in the field of health, congestion should be avoided and secure data transmission should be ensured. This study divides the collected data into two groups based on their intrinsic characteristics by presenting a congestion management protocol: (1) critical data and (2) non-critical data. The proposed protocol provides a dynamic routing algorithm based on the TOPSIS model for non-critical data transmission. In addition, an algorithm for transmitting critical data through the shortest possible path is also provided based on support vector machines (SVMs). This improves the network performance through using multi-classification that is obtained from SVMs. The simulation results indicate that the proposed method works better than other methods and leads to better performance in delay, network performance, and power consumption.</p>\",\"PeriodicalId\":51726,\"journal\":{\"name\":\"IET Wireless Sensor Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12046\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Wireless Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/wss2.12046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Wireless Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/wss2.12046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
A priority-based congestion avoidance scheme for healthcare wireless sensor networks
One of the most important challenges of wireless sensor networks is controlling network congestion and transmitting data in a way that improves the quality of service (QoS) parameters. Thus, it increases network performance and reduces energy consumption. Energy consumption increases due to various reasons, such as unsuccessful delivery of packets to the receiver, congestion in the network, retransmission of packets, delay in delivering packets to the base station, and so on. Given the importance of some data in the field of health, congestion should be avoided and secure data transmission should be ensured. This study divides the collected data into two groups based on their intrinsic characteristics by presenting a congestion management protocol: (1) critical data and (2) non-critical data. The proposed protocol provides a dynamic routing algorithm based on the TOPSIS model for non-critical data transmission. In addition, an algorithm for transmitting critical data through the shortest possible path is also provided based on support vector machines (SVMs). This improves the network performance through using multi-classification that is obtained from SVMs. The simulation results indicate that the proposed method works better than other methods and leads to better performance in delay, network performance, and power consumption.
期刊介绍:
IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.