{"title":"Reliable Hierarchical Data Storage in Sensor Networks","authors":"Song Lin, Benjamin Arai, D. Gunopulos","doi":"10.1109/SSDBM.2007.39","DOIUrl":null,"url":null,"abstract":"The ability to provide reliable in-network storage while balancing the energy consumption of individual sensors is a primary concern when deploying a sensor network. The main concern with data-centric storage in sensor networks is the ability to provide reliable and load balanced storage. Energy and wireless range constraints make centralized approaches for storage impractical, and in-network data-centric solutions can be used to reduce the number of messages sent over the network. However, these solutions quickly become expensive when combined with fault- tolerance, load balancing and routing. In this paper, we present a novel data-centric storage and query routing mechanism for sensor networks. The routing mechanism is constructed upon the neighborhood information of individual sensors and is completely independent of geographical information. Our data resilient algorithm is capable of recovering from multiple simultaneous failures in the network while adaptively adjusting the load distribution of the newly generated sensor data. Comprehensive experiments on both real-world and synthetic data sets indicate that our approach is more effective and efficient than the previously proposed solutions.","PeriodicalId":122925,"journal":{"name":"19th International Conference on Scientific and Statistical Database Management (SSDBM 2007)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"19th International Conference on Scientific and Statistical Database Management (SSDBM 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSDBM.2007.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
The ability to provide reliable in-network storage while balancing the energy consumption of individual sensors is a primary concern when deploying a sensor network. The main concern with data-centric storage in sensor networks is the ability to provide reliable and load balanced storage. Energy and wireless range constraints make centralized approaches for storage impractical, and in-network data-centric solutions can be used to reduce the number of messages sent over the network. However, these solutions quickly become expensive when combined with fault- tolerance, load balancing and routing. In this paper, we present a novel data-centric storage and query routing mechanism for sensor networks. The routing mechanism is constructed upon the neighborhood information of individual sensors and is completely independent of geographical information. Our data resilient algorithm is capable of recovering from multiple simultaneous failures in the network while adaptively adjusting the load distribution of the newly generated sensor data. Comprehensive experiments on both real-world and synthetic data sets indicate that our approach is more effective and efficient than the previously proposed solutions.