{"title":"基于携带抗加法的Booth Recoder (CRABRA)优化基于物联网的无线传感器网络组件的能源效率,以实现元宇宙可持续发展","authors":"C. Kumar. J, M. Majid","doi":"10.1109/LT58159.2023.10092334","DOIUrl":null,"url":null,"abstract":"Wireless sensing is now the spine of diverse Internet of Things (IoT) applications. In the Metaverse, the Internet of Things (IoT) can offer wireless and seamlessly integrated immersive digital experiences. Because the Metaverse's enabling technologies are considered to be energy-hungry, questions have been raised concerning the sustainability of its widespread adoption and development. IoT-based wireless sensor networks (WSN) readings are contaminated and distorted by noise. The noise in the signal causes the sensor node's (SN) computations and power consumption to rise, shortening the sensor node's longevity. To reduce noise, an efficient technique is therefore crucial. Finite-impulse response (FIR) filter is commonly employed in IoT-based WSN as a signal pre-processing stage in eliminating noise from the sensor measurements. The multiplication operation's number of adders (logic operators) and the adder steps (logic depths) determine the hardware complexities of FIR filters. The speed of the related application is determined by the multiplier's speed. By reducing the partial product (PP) row, the Booth method speeds up multiplication. The coefficients used by R8BR are ±0,±1 ,±2,±3,and ±4. As a result of the formation of odd multiples ±3, there will be a delay. The adder is required to add ±1 and ±2 for its calculations. This slowdown the multiplication procedures and reduces the recoding performance. To reduce the delay brought on by the creation of odd multiples, a carry resists adder (CRA) is used. CRA was explicitly built to achieve adding of ±2 and ±1 without carry propagation. Theoretically, it is observed that the CRA minimizes delay to 86.26% compared to carry propagation adder (CPA) approaches. Additionally, compared to a typical R8BR multiplier, the experimental findings indicated delay, area, and power reductions of 48.98%, 56.66%, and 31.2%, respectively. Without carry propagating, the CRA does addition faster, with less energy, and occupies less area.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimizing Energy Efficiencies of IoT-based Wireless Sensor Network Components for Metaverse Sustainable Development using Carry Resist Adder based Booth Recoder (CRABRA)\",\"authors\":\"C. Kumar. J, M. Majid\",\"doi\":\"10.1109/LT58159.2023.10092334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless sensing is now the spine of diverse Internet of Things (IoT) applications. In the Metaverse, the Internet of Things (IoT) can offer wireless and seamlessly integrated immersive digital experiences. Because the Metaverse's enabling technologies are considered to be energy-hungry, questions have been raised concerning the sustainability of its widespread adoption and development. IoT-based wireless sensor networks (WSN) readings are contaminated and distorted by noise. The noise in the signal causes the sensor node's (SN) computations and power consumption to rise, shortening the sensor node's longevity. To reduce noise, an efficient technique is therefore crucial. Finite-impulse response (FIR) filter is commonly employed in IoT-based WSN as a signal pre-processing stage in eliminating noise from the sensor measurements. The multiplication operation's number of adders (logic operators) and the adder steps (logic depths) determine the hardware complexities of FIR filters. The speed of the related application is determined by the multiplier's speed. By reducing the partial product (PP) row, the Booth method speeds up multiplication. The coefficients used by R8BR are ±0,±1 ,±2,±3,and ±4. As a result of the formation of odd multiples ±3, there will be a delay. The adder is required to add ±1 and ±2 for its calculations. This slowdown the multiplication procedures and reduces the recoding performance. To reduce the delay brought on by the creation of odd multiples, a carry resists adder (CRA) is used. CRA was explicitly built to achieve adding of ±2 and ±1 without carry propagation. Theoretically, it is observed that the CRA minimizes delay to 86.26% compared to carry propagation adder (CPA) approaches. Additionally, compared to a typical R8BR multiplier, the experimental findings indicated delay, area, and power reductions of 48.98%, 56.66%, and 31.2%, respectively. Without carry propagating, the CRA does addition faster, with less energy, and occupies less area.\",\"PeriodicalId\":142898,\"journal\":{\"name\":\"2023 20th Learning and Technology Conference (L&T)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 20th Learning and Technology Conference (L&T)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LT58159.2023.10092334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 20th Learning and Technology Conference (L&T)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LT58159.2023.10092334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing Energy Efficiencies of IoT-based Wireless Sensor Network Components for Metaverse Sustainable Development using Carry Resist Adder based Booth Recoder (CRABRA)
Wireless sensing is now the spine of diverse Internet of Things (IoT) applications. In the Metaverse, the Internet of Things (IoT) can offer wireless and seamlessly integrated immersive digital experiences. Because the Metaverse's enabling technologies are considered to be energy-hungry, questions have been raised concerning the sustainability of its widespread adoption and development. IoT-based wireless sensor networks (WSN) readings are contaminated and distorted by noise. The noise in the signal causes the sensor node's (SN) computations and power consumption to rise, shortening the sensor node's longevity. To reduce noise, an efficient technique is therefore crucial. Finite-impulse response (FIR) filter is commonly employed in IoT-based WSN as a signal pre-processing stage in eliminating noise from the sensor measurements. The multiplication operation's number of adders (logic operators) and the adder steps (logic depths) determine the hardware complexities of FIR filters. The speed of the related application is determined by the multiplier's speed. By reducing the partial product (PP) row, the Booth method speeds up multiplication. The coefficients used by R8BR are ±0,±1 ,±2,±3,and ±4. As a result of the formation of odd multiples ±3, there will be a delay. The adder is required to add ±1 and ±2 for its calculations. This slowdown the multiplication procedures and reduces the recoding performance. To reduce the delay brought on by the creation of odd multiples, a carry resists adder (CRA) is used. CRA was explicitly built to achieve adding of ±2 and ±1 without carry propagation. Theoretically, it is observed that the CRA minimizes delay to 86.26% compared to carry propagation adder (CPA) approaches. Additionally, compared to a typical R8BR multiplier, the experimental findings indicated delay, area, and power reductions of 48.98%, 56.66%, and 31.2%, respectively. Without carry propagating, the CRA does addition faster, with less energy, and occupies less area.