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EAGLE-A Scalable Query Processing Engine for linked sensor data

sensorS 2019年第20期19卷 4362-4362页

作者： Hoan Nguyen Mau Quoc Serrano, Martin Han Mau Nguyen Breslin, John G. Danh Le-Phuoc Natl Univ Ireland Galway Insight Ctr Data Analyt Galway H91 TK33 Ireland Hue Univ Informat Technol Dept Hue 530000 Vietnam Natl Univ Ireland Galway Confirm Ctr Smart Mfg Galway H91 TK33 Ireland Natl Univ Ireland Galway Insight Ctr Data Analyt Galway H91 TK33 Ireland Tech Univ Berlin Open Distributed Syst D-10587 Berlin Germany

Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio-temporal correlations. Most semantic approaches do not have spatio-temporal support. Some of them have attempted to provide full spatio-temporal support, but have poor performance for complex spatio-temporal aggregate queries. In addition, while the volume of sensor data is rapidly growing, the challenge of querying and managing the massive volumes of data generated by sensing devices still remains unsolved. In this article, we introduce EAGLE, a spatio-temporal query engine for querying sensor data based on the linked data model. The ultimate goal of EAGLE is to provide an elastic and scalable system which allows fast searching and analysis with respect to the relationships of space, time and semantics in sensor data. We also extend SPARQL with a set of new query operators in order to support spatio-temporal computing in the linked sensor data context.

关键词： internet of things graph of things linked stream data linked sensor data semantic web sensor network spatial data temporal RDF RDF stores

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An Algorithm to Generate data Linkages of linked sensor data 7

An Algorithm to Generate Data Linkages of Linked Sensor Data

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6th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Cuan, Lin-na Shi, Yi-min Li, Guan-yu Wu, Xue-hua Liu, Ning Dalian Maritime Univ Dept Informat Sci & Technol Dalian Peoples R China

ISBN: (纸本)9781467392006

To form linked sensor data, we can generate linkages among the sensor network data described by semantic information and relevant resources in a linked Open data cloud, which can make efficient use of sensor network data. Based on the analysis of existing interlinking methods of linked data and linked sensor data publishing systems, according to the property characteristics of sensor network data as well, we propose a similarity comparison algorithm of graph based on heuristic property, to generate linkages among sensor network data and related resources in linked Open data cloud effectively.

关键词： linked data linked sensor data linkages heuristic property RDF graph

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Integrating linked sensor data for On-line Analytical Processing On-The-Fly 3

Integrating Linked Sensor Data for On-line Analytical Proces...

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3rd IEEE International Colloquium on Information Science and Technology (CIST)

作者： Guilavogui, Koly Kjiri, Laila Fredj, Mounia Mohammed V Souissi Univ ENSIAS Ave Mohammed Ben Abdellah Regragui Rabat Morocco

ISBN: (纸本)9781479959792

sensor networks are gaining more and more attention in the current technology landscape. It is undeniable that their use allows a better monitoring of events that occur in the real world. Many sensors have been deployed for monitoring applications such as environmental monitoring, and traffic monitoring. A number of governments, corporates, and academic organizations or agencies hold independently sensor systems that generate a large amount of dynamic information from data sources with various formats of schemas and data. They are making this sensor data openly accessible by publishing it as linked sensor data (LSD) on the linked Open data (LOD) cloud. LSD is the concept that defines the publication of public or private organization sensor data without restrictions. This is achieved by transforming raw sensor observations to RDF format and by linking it with other datasets on the LOD cloud. The seamless integration of LSD sources from multiple providers is a great challenge. In this paper, we investigate the possibility of integrating diverse LSD sources using the hybrid ontology approach for on-line analytical processing (OLAP) on-the-fly. With such an ontology-based integration framework, organizations or individuals will have greater opportunity to make their respective analysis based on a large amount of sensor data openly accessible on the Web.

关键词： Integration Systems data warehouses OLAP linked data linked sensor data

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LSD2H: a Novel Storage Method of linked sensor data Based on HBase 10

LSD2H: a Novel Storage Method of Linked Sensor Data Based on...

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10th International Conference on Semantics, Knowledge and Grids (SKG)

作者： Gao, Hongbin Wang, Dongfeng Hebei Univ Sci & Technol Sch Informat Sci & Engn Shijiazhuang 050018 Hebei Peoples R China

ISBN: (纸本)9781479967155

With the development of sensor network, the number of sensors are increasing now. In order to manage sensor data, W3C has proposed semantic sensor web which unifies sensor network data and produces massive RDF dataset. linked sensor data is a normal dataset of semantic sensor web and links into linked Open data based on SSN ontology. HBase is a kind of distributed database and suits for the management of linked sensor data applicably. So we propose LSD2H which is a storage method of linked sensor data by use of HBase. LSD2H architecture consists of SDS, ODS, SD2H, OD2H and SCQuery. SDS is a table in HBase for storing sensor data. ODS is a table in HBase for storing observation data. SD2H maps linked sensor data to SDS, while OD2H maps linked sensor data to ODS by MapReduce. SCQuery based on tree pattern and recursion algorithm is a query method about SDS and ODS. In order to deduce storage space and improve query performance, we analyze the compression algorithms of LZO, GZIP, Snappy and no compression, which has proved that LZO selected by using storage of data is benefit for LSD2H in final.

关键词： linked sensor data Semantic sensor Web HBase Hadoop MapReduce

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IoT-Lite: a lightweight semantic model for the internet of things and its use with dynamic semantics

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PERSONAL AND UBIQUITOUS COMPUTING 2017年第3期21卷 475-487页

作者： Bermudez-Edo, Maria Elsaleh, Tarek Barnaghi, Payam Taylor, Kerry Univ Granada Software Engn Dept Granada Spain Univ Surrey Inst Commun Syst Guildford Surrey England Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia

Over the past few years, the semantics community has developed several ontologies to describe concepts and relationships for internet of things (IoT) applications. A key problem is that most of the IoT-related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time, and therefore, they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis and assess IoT-Lite against another solution in terms of round trip time performance for query-response times. We have linked IoT-Lite with stream annotation ontology, to allow queries over stream data annotations, and we have also added dynamic semantics in the form of MathML annotations to IoT-Lite. Dynamic semantics allows the annotation of spatio-temporal values, reducing storage requirements and therefore the response time for queries. Dynamic semantics stores mathematical formulas to recover estimated values when actual values are missing.

关键词： Internet of things Semantics linked sensor data Knowledge management Dynamic semantics

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IoT-Lite: A Lightweight Semantic Model for the Internet of Things 13

IoT-Lite: A Lightweight Semantic Model for the Internet of T...

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Conference on UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld

ISBN: (纸本)9781509027712

Over the past few years the semantics community has developed ontologies to describe concepts and relationships between different entities in various application domains, including Internet of Things (IoT) applications. A key problem is that most of the IoT related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time and therefore they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis, and assess IoT-Lite against another solution in terms of round time trip (RTT) performance for query-response times.

关键词： Internet of Things Semantics linked sensor data Knowledge Management

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IoT-Lite: A Lightweight Semantic Model for the Internet of Things

IoT-Lite: A Lightweight Semantic Model for the Internet of T...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Maria Bermudez-Edo Tarek Elsaleh Payam Barnaghi Kerry Taylor Software Engineering Department University of Granada Granada Spain Institute for Communication Systems University of Surrey Guildford United Kingdom The Australian National University Canberra Australia

Over the past few years the semantics community has developed ontologies to describe concepts, relationships between different entities in various application domains, including Internet of Things (IoT) applications. A key problem is that most of the IoT related semantic descriptions are not as widely adopted as expected. One of the main concerns of users, developers is that semantic techniques increase the complexity, processing time, therefore they are unsuitable for dynamic, responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability, discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good, scalable semantic model design, follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis,, assess IoT-Lite against another solution in terms of round time trip (RTT) performance for query-response times.

关键词： Knowledge Management Internet of Things Semantics linked sensor data

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A Knowledge-based Approach for Real-Time IoT data Stream Annotation and Processing

A Knowledge-based Approach for Real-Time IoT Data Stream Ann...

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IEEE International Conference on Internet of Things ( iThings) / IEEE International Conference on Green Computing and Communications (GreenCom) / IEEE International Conference on Cyber-Physical-Social Computing (CPS)

作者： Kolozali, Sefki Bermudez-Edo, Maria Puschmann, Daniel Ganz, Frieder Barnaghi, Payam Univ Surrey Ctr Commun Syst Res Guildford GU2 7XH Surrey England

ISBN: (纸本)9781479959679

Internet of Things is a generic term that refers to interconnection of real-world services which are provided by smart objects and sensors that enable interaction with the physical world. Cities are also evolving into large interconnected ecosystems in an effort to improve sustainability and operational efficiency of the city services and infrastructure. However, it is often difficult to perform real-time analysis of large amount of heterogeneous data and sensory information that are provided by various sources. This paper describes a framework for real-time semantic annotation of streaming IoT data to support dynamic integration into the Web using the Advanced Message Queuing Protocol (AMPQ). This will enable delivery of large volume of data that can influence the performance of the smart city systems that use IoT data. We present an information model to represent summarisation and reliability of stream data. The framework is evaluated with the data size and average exchanged message time using summarised and raw sensor data. Based on a statistical analysis, a detailed comparison between various sensor points is made to investigate the memory and computational cost for the stream annotation framework.

关键词： Internet of Things Smart Cities Semantic Stream Annotation linked sensor data Knowledge Management

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The SSN ontology of the W3C semantic sensor network incubator group

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JOURNAL OF WEB SEMANTICS 2012年 17卷 25-32页

作者： Compton, Michael Barnaghi, Payam Bermudez, Luis Garcia-Castro, Raul Corcho, Oscar Cox, Simon Graybeal, John Hauswirth, Manfred Henson, Cory Herzog, Arthur Huang, Vincent Janowicz, Krzysztof Kelsey, W. David Le Phuoc, Danh Lefort, Laurent Leggieri, Myriam Neuhaus, Holger Nikolov, Andriy Page, Kevin Passant, Alexandre Sheth, Amit Taylor, Kerry CSIRO ICT Ctr Wembley WA Australia Univ Surrey Guildford GU2 5XH Surrey England Univ Politecn Madrid E-28040 Madrid Spain CSIRO Earth Sci & Resource Engn Wembley WA Australia Natl Univ Ireland DERI Galway Ireland Wright State Univ Dayton OH 45435 USA Fraunhofer Gesell Germany Aachen Germany Univ Calif Santa Barbara Santa Barbara CA 93106 USA Geospatial Open Source Software N Initiat 52 Munster Germany Boeing Co Bellevue WA USA Open Univ London England Univ Southampton Southampton SO9 5NH Hants England CSIRO Tasmanian ICT Ctr Hobart Tas Australia

The W3C Semantic sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations - the SSN ontology, available at http://***/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved.

关键词： Semantic sensor web linked sensor data Ontologies Semantic interoperability sensor web enablement

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