Proceedings of the 6th ACM conference on Embedded network sensor systems - SenSys '08最新文献

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Dustminer

Proceedings of the 6th ACM conference on Embedded network sensor systems - SenSys '08 Pub Date : 1900-01-01 DOI: 10.1145/1460412.1460423

Mohammad Maifi Hasan Khan, H. Le, Hossein Ahmadi, T. Abdelzaher, Jiawei Han

{"title":"Dustminer","authors":"Mohammad Maifi Hasan Khan, H. Le, Hossein Ahmadi, T. Abdelzaher, Jiawei Han","doi":"10.1145/1460412.1460423","DOIUrl":"https://doi.org/10.1145/1460412.1460423","url":null,"abstract":"This paper presents a tool for uncovering bugs due to interactive complexity in networked sensing applications. Such bugs are not localized to one component that is faulty, but rather result from complex and unexpected interactions between multiple often individually non-faulty components. Moreover, the manifestations of these bugs are often not repeatable, making them particularly hard to find, as the particular sequence of events that invokes the bug may not be easy to reconstruct. Because of the distributed nature of failure scenarios, our tool looks for sequences of events that may be responsible for faulty behavior, as opposed to localized bugs such as a bad pointer in a module. An extensible framework is developed where a front-end collects runtime data logs of the system being debugged and an offline back-end uses frequent discriminative pattern mining to uncover likely causes of failure. We provide a case study of debugging a recent multichannel MAC protocol that was found to exhibit corner cases of poor performance (worse than single channel MAC). The tool helped uncover event sequences that lead to a highly degraded mode of operation. Fixing the problem significantly improved the performance of the protocol.We also provide a detailed analysis of tool overhead in terms of memory requirements and impact on the running application.","PeriodicalId":305361,"journal":{"name":"Proceedings of the 6th ACM conference on Embedded network sensor systems - SenSys '08","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127113030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 122

MODEL 模型

Proceedings of the 6th ACM conference on Embedded network sensor systems - SenSys '08 Pub Date : 1900-01-01 DOI: 10.1145/1460412.1460498

Qingming Yao, Hui Gao, B. Liu, Fei-Yue Wang

{"title":"MODEL","authors":"Qingming Yao, Hui Gao, B. Liu, Fei-Yue Wang","doi":"10.1145/1460412.1460498","DOIUrl":"https://doi.org/10.1145/1460412.1460498","url":null,"abstract":"Procurement decisions play a vital part in the sustainable transformation of the supply chain. Till now, a variety of supplier selection and lot-sizing models have been suggested, in particular, focusing on carbon emissions in a deterministic environment. It is noted that stressing only on carbon emissions cannot fully transform a sustainable supply chain. The present study argues that with carbon footprint, other dimensions, such as social sustainability, water footprint, recycled material use, solid and liquid waste, need to be considered in sustainable procurement decisions. To fill the gaps, this study proposed a three-stage multi-objective multi-supplier, multi-period joint supplier selection, and a lot-sizing model, taking into account carbon footprint, water footprint, solid and liquid waste, and use of recycled materials in a stochastic environment. The model optimizes three objectives (cost, carbon emission, and social sustainability). The model considers different model parameters as uncertain, such as costs, emission, solid waste, liquid waste, recycled material, quality rejection, and capacity. The present study suggests how to quantify social sustainability and further use it in the lot-sizing model. The proposed study has been carried out in three stages. In the first stage, BWM (Best-Worst method) and TOPSIS are applied to evaluate suppliers' social scores. In the second stage, the suppliers' social scores are used in the proposed possibilistic lot-sizing model. In the third stage, various trade-off curves are generated by applying the ε-constraint method. The model produces distinct optimal solutions for different uncertainty levels, which are used to create trade-off curves among the cost, emission, and social dimensions. The results facilitate decision-makers to decide the lot-size in an ambiguous environment.","PeriodicalId":305361,"journal":{"name":"Proceedings of the 6th ACM conference on Embedded network sensor systems - SenSys '08","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125407231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8