{"title":"一种物联网信息压缩方法","authors":"Yu. Manzhos, Yevheniia Sokolova","doi":"10.47839/ijc.21.1.2523","DOIUrl":null,"url":null,"abstract":"The Internet of Things (IoT) is a modern paradigm that consists of heterogeneous intercommunicated devices that send and receive messages in various formats through different protocols. Thanks to the smart things mainstream, it is becoming common to collect large quantities of data generated by resource-constrained, distributed devices at one or more servers. However, the wireless transmitting of data is very expensive. For example, in IoT, Bluetooth Low Energy using costs tens of millijoules per connection, while computing at full energy costs only tens of micrjoules, and sitting idle costs close to 1 microjoules per second for STM processors. We need compression of data on smart devices. We introduce an IoT compression method based on the concurrent Cosine and Chebyshev Discrete Transforms. For performance increasing, the modification of Transforms algorithms is proposed. This method is suitable not only for IoT devices collecting data but also for the big servers.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A Method of IoT Information Compression\",\"authors\":\"Yu. Manzhos, Yevheniia Sokolova\",\"doi\":\"10.47839/ijc.21.1.2523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Internet of Things (IoT) is a modern paradigm that consists of heterogeneous intercommunicated devices that send and receive messages in various formats through different protocols. Thanks to the smart things mainstream, it is becoming common to collect large quantities of data generated by resource-constrained, distributed devices at one or more servers. However, the wireless transmitting of data is very expensive. For example, in IoT, Bluetooth Low Energy using costs tens of millijoules per connection, while computing at full energy costs only tens of micrjoules, and sitting idle costs close to 1 microjoules per second for STM processors. We need compression of data on smart devices. We introduce an IoT compression method based on the concurrent Cosine and Chebyshev Discrete Transforms. For performance increasing, the modification of Transforms algorithms is proposed. This method is suitable not only for IoT devices collecting data but also for the big servers.\",\"PeriodicalId\":37669,\"journal\":{\"name\":\"International Journal of Computing\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47839/ijc.21.1.2523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47839/ijc.21.1.2523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
The Internet of Things (IoT) is a modern paradigm that consists of heterogeneous intercommunicated devices that send and receive messages in various formats through different protocols. Thanks to the smart things mainstream, it is becoming common to collect large quantities of data generated by resource-constrained, distributed devices at one or more servers. However, the wireless transmitting of data is very expensive. For example, in IoT, Bluetooth Low Energy using costs tens of millijoules per connection, while computing at full energy costs only tens of micrjoules, and sitting idle costs close to 1 microjoules per second for STM processors. We need compression of data on smart devices. We introduce an IoT compression method based on the concurrent Cosine and Chebyshev Discrete Transforms. For performance increasing, the modification of Transforms algorithms is proposed. This method is suitable not only for IoT devices collecting data but also for the big servers.
期刊介绍:
The International Journal of Computing Journal was established in 2002 on the base of Branch Research Laboratory for Automated Systems and Networks, since 2005 it’s renamed as Research Institute of Intelligent Computer Systems. A goal of the Journal is to publish papers with the novel results in Computing Science and Computer Engineering and Information Technologies and Software Engineering and Information Systems within the Journal topics. The official language of the Journal is English; also papers abstracts in both Ukrainian and Russian languages are published there. The issues of the Journal are published quarterly. The Editorial Board consists of about 30 recognized worldwide scientists.