S. Routray, A. Javali, Anindita Sahoo, Wogderes Semunigus, M. Pappa
{"title":"低带宽Io的无损压缩技术","authors":"S. Routray, A. Javali, Anindita Sahoo, Wogderes Semunigus, M. Pappa","doi":"10.1109/I-SMAC49090.2020.9243457","DOIUrl":null,"url":null,"abstract":"In the recent years, Internet of things (IoT) has become an integral part of the modern digital ecosystem. It has the ability to handle the tasks smartly for many different situations. Therefore, it is one of the main technologies for autonomous systems. These IoTs deal with a lot of information. As the resources of the IoT are limited, data compression is an essential need. Some of the information transmitted over the IoTs cannot be compromised at all. Any loss of such sensitive data may cause serious consequences. Therefore, lossless data compression techniques are preferred for such data so that the integrity can be maintained. The low bandwidth IoTs are very popular in the recent times. They provide services over large coverage area with limited resources. These networks are known as low power wide area networks (LPWANs). In the 3GPP framework, there are some popular LPWANs such as narrowband IoT (NBIoT), and LTE machine-type communication (LTE-M). This article focuses on the lossless compression techniques employed in these popular LPWANs. This research work shows the reasons why lossless compression techniques are needed in NBIoT and LTE-M. It also goes through the challenges posed by the low bandwidth IoTs. Further, the recently used compression techniques for these low bandwidth IoTs are also discussed.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Lossless Compression Techniques for Low Bandwidth Io Ts\",\"authors\":\"S. Routray, A. Javali, Anindita Sahoo, Wogderes Semunigus, M. Pappa\",\"doi\":\"10.1109/I-SMAC49090.2020.9243457\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the recent years, Internet of things (IoT) has become an integral part of the modern digital ecosystem. It has the ability to handle the tasks smartly for many different situations. Therefore, it is one of the main technologies for autonomous systems. These IoTs deal with a lot of information. As the resources of the IoT are limited, data compression is an essential need. Some of the information transmitted over the IoTs cannot be compromised at all. Any loss of such sensitive data may cause serious consequences. Therefore, lossless data compression techniques are preferred for such data so that the integrity can be maintained. The low bandwidth IoTs are very popular in the recent times. They provide services over large coverage area with limited resources. These networks are known as low power wide area networks (LPWANs). In the 3GPP framework, there are some popular LPWANs such as narrowband IoT (NBIoT), and LTE machine-type communication (LTE-M). This article focuses on the lossless compression techniques employed in these popular LPWANs. This research work shows the reasons why lossless compression techniques are needed in NBIoT and LTE-M. It also goes through the challenges posed by the low bandwidth IoTs. Further, the recently used compression techniques for these low bandwidth IoTs are also discussed.\",\"PeriodicalId\":432766,\"journal\":{\"name\":\"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SMAC49090.2020.9243457\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SMAC49090.2020.9243457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lossless Compression Techniques for Low Bandwidth Io Ts
In the recent years, Internet of things (IoT) has become an integral part of the modern digital ecosystem. It has the ability to handle the tasks smartly for many different situations. Therefore, it is one of the main technologies for autonomous systems. These IoTs deal with a lot of information. As the resources of the IoT are limited, data compression is an essential need. Some of the information transmitted over the IoTs cannot be compromised at all. Any loss of such sensitive data may cause serious consequences. Therefore, lossless data compression techniques are preferred for such data so that the integrity can be maintained. The low bandwidth IoTs are very popular in the recent times. They provide services over large coverage area with limited resources. These networks are known as low power wide area networks (LPWANs). In the 3GPP framework, there are some popular LPWANs such as narrowband IoT (NBIoT), and LTE machine-type communication (LTE-M). This article focuses on the lossless compression techniques employed in these popular LPWANs. This research work shows the reasons why lossless compression techniques are needed in NBIoT and LTE-M. It also goes through the challenges posed by the low bandwidth IoTs. Further, the recently used compression techniques for these low bandwidth IoTs are also discussed.