{"title":"CBDS2R:一种基于集群的水下无线传感器网络深度源选择路由","authors":"Shahrokh Vahabi;Ali Daneshvar;Mohammadreza Eslaminejad;Seyed Ebrahim Dashti","doi":"10.1109/TSIPN.2023.3299108","DOIUrl":null,"url":null,"abstract":"Underwater wireless sensor network (UWSN) is one of the kinds of wireless sensor network (WSN). This type of network is suitable for underwater areas such as pools, rivers, seas, and oceans. In UWSN, the energy of nodes is more depletes compared to WSN. As more energy in nodes depletes for transmitting data, therefore routing is the most important issue for UWSN. Sensor nodes in water use acoustic waves to transmit data packets contrary to sensor nodes in WSN which are used radio waves for this purpose, hence the link quality of the acoustic and radio waves is different. Therefore, it is impossible to use routing methods and protocols based on WSN for UWSN. This article focuses on routing in UWSN and proposes a depth source selection phase via link quality between sensor nodes with mobile sink(s) for improving energy-saving and network lifetime. The new proposed algorithm contains six phases are as follows: network architecture, calculating link quality, clustering, source selection, mobile sink mechanism, and transmitting data packets phase. Also, the new approach is suitable for small and large networks. Results of experimental simulation clearly show that this new proposed algorithm improves residual energy and network lifetime by at least 40.28% and 58.88% respectively.","PeriodicalId":56268,"journal":{"name":"IEEE Transactions on Signal and Information Processing over Networks","volume":"9 ","pages":"468-476"},"PeriodicalIF":3.0000,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CBDS2R: A Cluster-Based Depth Source Selection Routing for Underwater Wireless Sensor Network\",\"authors\":\"Shahrokh Vahabi;Ali Daneshvar;Mohammadreza Eslaminejad;Seyed Ebrahim Dashti\",\"doi\":\"10.1109/TSIPN.2023.3299108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Underwater wireless sensor network (UWSN) is one of the kinds of wireless sensor network (WSN). This type of network is suitable for underwater areas such as pools, rivers, seas, and oceans. In UWSN, the energy of nodes is more depletes compared to WSN. As more energy in nodes depletes for transmitting data, therefore routing is the most important issue for UWSN. Sensor nodes in water use acoustic waves to transmit data packets contrary to sensor nodes in WSN which are used radio waves for this purpose, hence the link quality of the acoustic and radio waves is different. Therefore, it is impossible to use routing methods and protocols based on WSN for UWSN. This article focuses on routing in UWSN and proposes a depth source selection phase via link quality between sensor nodes with mobile sink(s) for improving energy-saving and network lifetime. The new proposed algorithm contains six phases are as follows: network architecture, calculating link quality, clustering, source selection, mobile sink mechanism, and transmitting data packets phase. Also, the new approach is suitable for small and large networks. Results of experimental simulation clearly show that this new proposed algorithm improves residual energy and network lifetime by at least 40.28% and 58.88% respectively.\",\"PeriodicalId\":56268,\"journal\":{\"name\":\"IEEE Transactions on Signal and Information Processing over Networks\",\"volume\":\"9 \",\"pages\":\"468-476\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Signal and Information Processing over Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10197249/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal and Information Processing over Networks","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10197249/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
CBDS2R: A Cluster-Based Depth Source Selection Routing for Underwater Wireless Sensor Network
Underwater wireless sensor network (UWSN) is one of the kinds of wireless sensor network (WSN). This type of network is suitable for underwater areas such as pools, rivers, seas, and oceans. In UWSN, the energy of nodes is more depletes compared to WSN. As more energy in nodes depletes for transmitting data, therefore routing is the most important issue for UWSN. Sensor nodes in water use acoustic waves to transmit data packets contrary to sensor nodes in WSN which are used radio waves for this purpose, hence the link quality of the acoustic and radio waves is different. Therefore, it is impossible to use routing methods and protocols based on WSN for UWSN. This article focuses on routing in UWSN and proposes a depth source selection phase via link quality between sensor nodes with mobile sink(s) for improving energy-saving and network lifetime. The new proposed algorithm contains six phases are as follows: network architecture, calculating link quality, clustering, source selection, mobile sink mechanism, and transmitting data packets phase. Also, the new approach is suitable for small and large networks. Results of experimental simulation clearly show that this new proposed algorithm improves residual energy and network lifetime by at least 40.28% and 58.88% respectively.
期刊介绍:
The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.