{"title":"Real-Time Traffic Management in Sensor Networks","authors":"K. Karenos, V. Kalogeraki","doi":"10.1109/RTSS.2006.40","DOIUrl":null,"url":null,"abstract":"In this work we propose a traffic management mechanism to support real-time flows in highly unpredictable sensor network environments. The mechanism is based on a joint traffic regulation and end-to-end scheduling approach; a traffic regulation component adjusts the incoming packet rate to implicitly control the channel load and intelligently rejects packets that are more likely to miss their deadline while a laxity-based scheduling component projects the packets' per-hop delay and compensates for network end-to-end delays. Thus, high success ratios without severely degrading the fidelity are achieved. Our mechanism attempts to maintain accuracy in a resource-efficient manner even under extremely unstable network conditions where delays are difficult to model and compute. Furthermore, the adoption of a component-based approach allows for substantial independence from both the MAC and routing layers. We thoroughly evaluate our mechanism and demonstrate its accuracy and performance merits","PeriodicalId":353932,"journal":{"name":"2006 27th IEEE International Real-Time Systems Symposium (RTSS'06)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 27th IEEE International Real-Time Systems Symposium (RTSS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTSS.2006.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 54
Abstract
In this work we propose a traffic management mechanism to support real-time flows in highly unpredictable sensor network environments. The mechanism is based on a joint traffic regulation and end-to-end scheduling approach; a traffic regulation component adjusts the incoming packet rate to implicitly control the channel load and intelligently rejects packets that are more likely to miss their deadline while a laxity-based scheduling component projects the packets' per-hop delay and compensates for network end-to-end delays. Thus, high success ratios without severely degrading the fidelity are achieved. Our mechanism attempts to maintain accuracy in a resource-efficient manner even under extremely unstable network conditions where delays are difficult to model and compute. Furthermore, the adoption of a component-based approach allows for substantial independence from both the MAC and routing layers. We thoroughly evaluate our mechanism and demonstrate its accuracy and performance merits