{"title":"Multi-Attribute Query Processing Through In-Network Aggregation in Edge Computing","authors":"Xiaocui Li, Zhangbing Zhou","doi":"10.1109/SKG.2018.00027","DOIUrl":null,"url":null,"abstract":"This paper proposes a multi-attribute aggregation query mechanism in the context of edge computing, where an energy-aware IR-tree is constructed to process query processing in single edge networks, while an edge node routing graph is es-tablished to facilitate query processing for marginal smart things contained in contiguous edge networks. This in-network and localized strategy has shown its e □ ciency and applicability of query processing in IoT sensing networks, and experimental evaluation demonstrates that this technique performs better than the rivals in reducing the network tra □ c and energy consumption.","PeriodicalId":265760,"journal":{"name":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SKG.2018.00027","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
This paper proposes a multi-attribute aggregation query mechanism in the context of edge computing, where an energy-aware IR-tree is constructed to process query processing in single edge networks, while an edge node routing graph is es-tablished to facilitate query processing for marginal smart things contained in contiguous edge networks. This in-network and localized strategy has shown its e □ ciency and applicability of query processing in IoT sensing networks, and experimental evaluation demonstrates that this technique performs better than the rivals in reducing the network tra □ c and energy consumption.