{"title":"Real-Time Encoding/Decoding for Pairwise Communication Over an Unreliable Sensor Network","authors":"Daniel Graham, Arnold Yim, Gang Zhou, W. Mao","doi":"10.5220/0007247000690076","DOIUrl":null,"url":null,"abstract":"The length of time that a wireless sensor can be deployed is limited by its internal power supply. To increase the deployment lifetime of these sensors we must find ways to conserve power. In this paper, we propose an algorithm that reduces the amount of energy the transceiver consumes by compressing the bytes that are sent and received over the network. The algorithm compresses a data stream by exploiting its temporal locality and is designed to function efficiently on an unreliable network in real-time. A stream is compressed by using fewer bits to represent elements that frequently recur. We evaluate the proposed compression algorithm using a collection of independently collected traces from the crawdad database. We calculated the compression ratio for each trace and found that we were able to reduce the number of bytes transmitted by an average of 60%, resulting in a 30% increase in energy savings.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0007247000690076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The length of time that a wireless sensor can be deployed is limited by its internal power supply. To increase the deployment lifetime of these sensors we must find ways to conserve power. In this paper, we propose an algorithm that reduces the amount of energy the transceiver consumes by compressing the bytes that are sent and received over the network. The algorithm compresses a data stream by exploiting its temporal locality and is designed to function efficiently on an unreliable network in real-time. A stream is compressed by using fewer bits to represent elements that frequently recur. We evaluate the proposed compression algorithm using a collection of independently collected traces from the crawdad database. We calculated the compression ratio for each trace and found that we were able to reduce the number of bytes transmitted by an average of 60%, resulting in a 30% increase in energy savings.