Open J. Internet Things最新文献

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Online Replication Strategies for Distributed Data Stores 分布式数据存储的在线复制策略

Open J. Internet Things Pub Date : 2019-08-01 DOI: 10.14279/DEPOSITONCE-9383

Niklas Semmler, Georgios Smaragdakis, A. Feldmann

{"title":"Online Replication Strategies for Distributed Data Stores","authors":"Niklas Semmler, Georgios Smaragdakis, A. Feldmann","doi":"10.14279/DEPOSITONCE-9383","DOIUrl":"https://doi.org/10.14279/DEPOSITONCE-9383","url":null,"abstract":"The rate at which data is produced at the network edge, e.g., collected from sensors and Internet of Things (IoT) devices, will soon exceed the storage and processing capabilities of a single system and the capacity of the network. Thus, data will need to be collected and preprocessed in distributed data stores - as part of a distributed database - at the network edge. Yet, even in this setup, the transfer of query results will incur prohibitive costs. To further reduce the data transfers, patterns in the workloads must be exploited. Particularly in IoT scenarios, we expect data access to be highly skewed. Most data will be store-only, while a fraction will be popular. Here, the replication of popular, raw data, as opposed to the shipment of partially redundant query results, can reduce the volume of data transfers over the network. In this paper, we design online strategies to decide between replicating data from data stores or forwarding the queries and retrieving their results. Our insight is that by profiling access patterns of the data we can lower the data transfer cost and the corresponding response times. We evaluate the benefit of our strategies using two real-world datasets.","PeriodicalId":299874,"journal":{"name":"Open J. Internet Things","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127382391","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: 2

Controlled Components for Internet of Things As-A-Service 物联网即服务的受控组件

Open J. Internet Things Pub Date : 2016-05-01 DOI: 10.19210/1005.2.1.16

T. Aubonnet, Amina Boubendir, F. Lemoine, N. Simoni

引用次数: 6

Evidential Sensor Data Fusion in a Smart City Environment 智慧城市环境中的证据传感器数据融合

Open J. Internet Things Pub Date : 1900-01-01 DOI: 10.19210/OJIOT_2015V1I2N02_GAUR

Aditya Gaur, B. Scotney, G. Parr, S. McClean

{"title":"Evidential Sensor Data Fusion in a Smart City Environment","authors":"Aditya Gaur, B. Scotney, G. Parr, S. McClean","doi":"10.19210/OJIOT_2015V1I2N02_GAUR","DOIUrl":"https://doi.org/10.19210/OJIOT_2015V1I2N02_GAUR","url":null,"abstract":"Wireless sensor networks have increasingly become contributors of very large amounts of data. The recent deployment of wireless sensor networks in Smart City infrastructures have led to very large amounts of data being generated each day across a variety of domains, with applications including environmental monitoring, healthcare monitoring and transport monitoring. The information generated through the wireless sensor nodes has made possible the visualization of a Smart City environment for better living. The Smart City offers intelligent infrastructure and cogitative environment for the elderly and other people living in the Smart society. Different types of sensors are present that help in monitoring inhabitants’ behaviour and their interaction with real world objects. To take advantage of the increasing amounts of data, there is a need for new methods and techniques for effective data management and analysis, to generate information that can assist in managing the resources intelligently and dynamically. Through this research a Smart City ontology model is proposed, which addresses the fusion process related to uncertain sensor data using semantic web technologies and Dempster-Shafer uncertainty theory. Based on the information handling methods, such as Dempster-Shafer theory (DST), an equally weighted sum operator and maximization operation, a higher level of contextual information is inferred from the low-level sensor data fusion process. In addition, the proposed ontology model helps in learning new rules that can be used in defining new knowledge in the Smart City system.","PeriodicalId":299874,"journal":{"name":"Open J. Internet Things","volume":"20 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":"123885911","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: 3