B. Garbinato, R. Guerraoui, J. Hulaas, A. Kounine, Maxime Monod, J. H. Spring
{"title":"The Weight-Watcher Service and its Lightweight Implementation","authors":"B. Garbinato, R. Guerraoui, J. Hulaas, A. Kounine, Maxime Monod, J. H. Spring","doi":"10.1109/ICSAMOS.2007.4285742","DOIUrl":null,"url":null,"abstract":"This paper presents the weight-watcher service. This service aims at providing resource consumption measurements and estimations for software executing on resource-constrained devices. By using the weight-watcher, software components can continuously adapt and optimize their quality of service with respect to resource availability. The interface of the service is composed of a profiler and a predictor. We present an implementation that is lightweight in terms of CPU and memory. We also performed various experiments that convey (a) the tradeoff between the memory consumption of the service and the accuracy of the prediction, as well as (b) a maximum overhead of 10% on the execution speed of the VM for the profiler to provide accurate measurements.","PeriodicalId":106933,"journal":{"name":"2007 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAMOS.2007.4285742","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents the weight-watcher service. This service aims at providing resource consumption measurements and estimations for software executing on resource-constrained devices. By using the weight-watcher, software components can continuously adapt and optimize their quality of service with respect to resource availability. The interface of the service is composed of a profiler and a predictor. We present an implementation that is lightweight in terms of CPU and memory. We also performed various experiments that convey (a) the tradeoff between the memory consumption of the service and the accuracy of the prediction, as well as (b) a maximum overhead of 10% on the execution speed of the VM for the profiler to provide accurate measurements.