{"title":"DaRe:通过应用层编码实现LoRaWAN的数据恢复","authors":"P. Marcelis, V. Rao, R. V. Prasad","doi":"10.1145/3054977.3054978","DOIUrl":null,"url":null,"abstract":"Internet of Things (IoT) solutions are increasingly being deployed for smart applications. To provide good communication for the increasing number of smart applications, there is a need for low cost and long range Low Power Wide Area Network (LPWAN) technologies. LoRaWAN is an energy efficient and inexpensive LPWAN solution that is rapidly being adopted all around the world. However, LoRaWAN does not guarantee reliable communication in its basic configuration. Transmitted frames can be lost due to the channel effects and mobility of the end-devices. In this study, we perform extensive measurements on a new LoRaWAN network to characterise spatial and temporal properties of the LoRaWAN channel. The empirical outage probability for the farthest measured distance from the closest gateway of 7.5km in our deployment is as low as 0.004, but the frame loss measured at this distance was up to 70%. Furthermore, we show that burstiness in frame loss can be expected for both mobile and stationary scenarios. Frame loss results in data loss, since in the basic configuration frames are only transmitted once. To reduce data loss in LoRaWAN, we design a novel coding scheme for data recovery called DaRe, which extends frames with redundant information that is calculated from the data from previous frames. DaRe combines techniques from convolutional codes and fountain codes. We develop an implementation for DaRe and show that 99% of the data can be recovered with a code rate of 1/2 for up to 40% frame loss. Compared to repetition coding DaRe provides 21% more data recovery, and can save up to 42% energy consumption on transmission for 10 byte data units. DaRe also provides better resilience to bursty frame loss. This study provides useful results to both LoRaWAN network operators as well as developers of LoRaWAN applications. Network operators can use the characterisation results to identify possible weaknesses in the network, and application developers are offered a tool to prevent possible data loss.","PeriodicalId":179120,"journal":{"name":"2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"75","resultStr":"{\"title\":\"DaRe: Data Recovery through Application Layer Coding for LoRaWAN\",\"authors\":\"P. Marcelis, V. Rao, R. V. Prasad\",\"doi\":\"10.1145/3054977.3054978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Internet of Things (IoT) solutions are increasingly being deployed for smart applications. To provide good communication for the increasing number of smart applications, there is a need for low cost and long range Low Power Wide Area Network (LPWAN) technologies. LoRaWAN is an energy efficient and inexpensive LPWAN solution that is rapidly being adopted all around the world. However, LoRaWAN does not guarantee reliable communication in its basic configuration. Transmitted frames can be lost due to the channel effects and mobility of the end-devices. In this study, we perform extensive measurements on a new LoRaWAN network to characterise spatial and temporal properties of the LoRaWAN channel. The empirical outage probability for the farthest measured distance from the closest gateway of 7.5km in our deployment is as low as 0.004, but the frame loss measured at this distance was up to 70%. Furthermore, we show that burstiness in frame loss can be expected for both mobile and stationary scenarios. Frame loss results in data loss, since in the basic configuration frames are only transmitted once. To reduce data loss in LoRaWAN, we design a novel coding scheme for data recovery called DaRe, which extends frames with redundant information that is calculated from the data from previous frames. DaRe combines techniques from convolutional codes and fountain codes. We develop an implementation for DaRe and show that 99% of the data can be recovered with a code rate of 1/2 for up to 40% frame loss. Compared to repetition coding DaRe provides 21% more data recovery, and can save up to 42% energy consumption on transmission for 10 byte data units. DaRe also provides better resilience to bursty frame loss. This study provides useful results to both LoRaWAN network operators as well as developers of LoRaWAN applications. Network operators can use the characterisation results to identify possible weaknesses in the network, and application developers are offered a tool to prevent possible data loss.\",\"PeriodicalId\":179120,\"journal\":{\"name\":\"2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI)\",\"volume\":\"203 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"75\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3054977.3054978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3054977.3054978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DaRe: Data Recovery through Application Layer Coding for LoRaWAN
Internet of Things (IoT) solutions are increasingly being deployed for smart applications. To provide good communication for the increasing number of smart applications, there is a need for low cost and long range Low Power Wide Area Network (LPWAN) technologies. LoRaWAN is an energy efficient and inexpensive LPWAN solution that is rapidly being adopted all around the world. However, LoRaWAN does not guarantee reliable communication in its basic configuration. Transmitted frames can be lost due to the channel effects and mobility of the end-devices. In this study, we perform extensive measurements on a new LoRaWAN network to characterise spatial and temporal properties of the LoRaWAN channel. The empirical outage probability for the farthest measured distance from the closest gateway of 7.5km in our deployment is as low as 0.004, but the frame loss measured at this distance was up to 70%. Furthermore, we show that burstiness in frame loss can be expected for both mobile and stationary scenarios. Frame loss results in data loss, since in the basic configuration frames are only transmitted once. To reduce data loss in LoRaWAN, we design a novel coding scheme for data recovery called DaRe, which extends frames with redundant information that is calculated from the data from previous frames. DaRe combines techniques from convolutional codes and fountain codes. We develop an implementation for DaRe and show that 99% of the data can be recovered with a code rate of 1/2 for up to 40% frame loss. Compared to repetition coding DaRe provides 21% more data recovery, and can save up to 42% energy consumption on transmission for 10 byte data units. DaRe also provides better resilience to bursty frame loss. This study provides useful results to both LoRaWAN network operators as well as developers of LoRaWAN applications. Network operators can use the characterisation results to identify possible weaknesses in the network, and application developers are offered a tool to prevent possible data loss.