{"title":"PINCO: a pipelined in-network compression scheme for data collection in wireless sensor networks","authors":"Tarik Arici, B. Gedik, Y. Altunbasak, Ling Liu","doi":"10.1109/ICCCN.2003.1284221","DOIUrl":null,"url":null,"abstract":"In this paper, we present PINCO, an in-network compression scheme for energy constrained, distributed, wireless sensor networks. PINCO reduces redundancy in the data collected from sensors, thereby decreasing the wireless communication among the sensor nodes and saving energy. Sensor data is buffered in the network and combined through a pipelined compression scheme into groups of data, while satisfying a user-specified end-to-end latency bound. We introduce a PINCO scheme for single-valued sensor readings. In this scheme, each group of data is a highly flexible structure so that compressed data can be recompressed without decompressing, in order to reduce newly available redundancy at a different stage of the network. We discuss how PINCO parameters affect its performance, and how to tweak them for different performance requirements. We also include a performance study demonstrating the advantages of our approach over other data collection schemes based on simulation and prototype deployment results.","PeriodicalId":168378,"journal":{"name":"Proceedings. 12th International Conference on Computer Communications and Networks (IEEE Cat. No.03EX712)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"120","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 12th International Conference on Computer Communications and Networks (IEEE Cat. No.03EX712)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2003.1284221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 120
Abstract
In this paper, we present PINCO, an in-network compression scheme for energy constrained, distributed, wireless sensor networks. PINCO reduces redundancy in the data collected from sensors, thereby decreasing the wireless communication among the sensor nodes and saving energy. Sensor data is buffered in the network and combined through a pipelined compression scheme into groups of data, while satisfying a user-specified end-to-end latency bound. We introduce a PINCO scheme for single-valued sensor readings. In this scheme, each group of data is a highly flexible structure so that compressed data can be recompressed without decompressing, in order to reduce newly available redundancy at a different stage of the network. We discuss how PINCO parameters affect its performance, and how to tweak them for different performance requirements. We also include a performance study demonstrating the advantages of our approach over other data collection schemes based on simulation and prototype deployment results.