Cross-Domain Interoperability: A Case Study

Honkola, Jukka; Laine, Hannu; Brown, Ronald; Oliver, Ian

doi:10.1007/978-3-642-04190-7_3

Cited by 22 publications

(4 citation statements)

References 3 publications

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“…With this approach we can use personal and shared geo-tags, last can be implemented by introducing common user or group. Each instance of User class is connected with one or more Channels (Geo2tag terminology is used [6]). User has a relation subsribesTo so that follow different sets of geo-tags.…”

Section: Location Based Enginementioning

confidence: 99%

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Krinkin¹,

Yudenok

2013

Internet of Things, Smart Spaces, and Next Generation Networking

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Abstract. Geo-tagging and smart spaces are two promising directions in modern mobile market. Geo-tagging allows to markup any kind of data by geographical coordinates and time. This is the basis for defining geographical context which can be used in different types of applications e.g. semantic information search, machine-to-machine (M2M) interactions. Smart spaces as the basis for seamless distributed communication field for software services provides semantic level for data processing. Most desired feature of coming software is pro-activeness and context awareness, i.e. services will be able to adapt to the user's needs and situations and be able to manage decisions and behaviors on behalf of the user. The paper is dedicated discussion of integration most popular open platforms for smart spaces and geo-tagging (Smart-M3 and Geo2Tag) as possible solution for creation context aware proactive location based (LBS) services.

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Section: Location Based Enginementioning

confidence: 99%

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Krinkin¹,

Yudenok

2013

Internet of Things, Smart Spaces, and Next Generation Networking

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“…The SPARQL UPDATE [16] and QUERY [17] languages are used to update and retrieve data from the shared information store, which constitutes a knowledge base (KB) for the environment. Through these technologies, Smart-M3 becomes a candidate middleware platform for hosting a wide range of context-aware applications based on ontology-driven and multi-agent approaches [18], [19], [20], [21], [22]. The context is here intended, as from the well-known Dey definition, as any information that can be used to characterize the situation of an entity, where the latter can be a person, a place or a physical or computational object [23].…”

Section: Introductionmentioning

confidence: 99%

The M3 architecture for smart spaces: Overview of semantic information broker implementations

Viola

D’Elia

Korzun

et al. 2016

2016 19th Conference of Open Innovations Association (FRUCT)

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A smart space enhances a networked computing environment by enabling information sharing for a multitude of local digital devices and global resources from the Internet. We consider the M3 architecture (multi-device, multi-vendor, multidomain) for creating smart spaces, which integrates technologies from two innovative concepts: the Semantic Web and the Internet of Things. Our research focus is on analyses of the capabilities of Smart-M3 platform, which provides software implementations for such a central element of an M3 smart space as Semantic Information Broker (SIB). The paper presents a state-of-the-art and contributes our systematized vision on the SIB design and implementation. The analyzed open source SIB implementations include the original Smart-M3 piglet-based SIB, its optimized descendant RedSIB, OSGi SIB for Java devices, pySIB for Python devices, and CuteSIB for Qt devices. We also analyze the design of proprietary or incomplete SIB implementations: RIBS for embedded devices and ADK SIB built upon the OSGi framework with integration in the Eclipse Integrated Development Environment. The theoretical study is augmented with experimental evaluation of available SIB implementations.

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“…The focus of semantic interoperability research in the literature has been mostly on the design of smart space architectures and semantic interoperability over heterogeneous networks and devices [1][2][3][4], rather than performance analysis. The heterogeneous network in [4] is formed out of a low-capacity network of OSAS (Open Source Architecture for Sensors) [5] nodes and a highcapacity network of Smart-M3 (multi-vendor, multi-device, multi-domain) [6] nodes.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, there have been efforts [1][2][3][4] to provide technology solutions for semantic interoperability, where the information describing the smart spaces and events therein can be interpreted automatically and accurately by all devices involved. Ontology based semantic information representation formats are commonly used in this area.…”

Section: Introductionmentioning

confidence: 99%

Delay Performance in a Semantic Interoperability Architecture

Bhardwaj

Özçelebi

Verhoeven

et al. 2011

2011 IEEE/IPSJ International Symposium on Applications and the Internet

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Abstract-A semantic interoperability architecture typically consists of collaborating heterogeneous networks and devices with different availability of resources such as bandwidth, processing power, memory, storage and energy. Due to utilization of ontology based information representation and communication formats, a gateway approach for achieving semantic interoperability becomes complex and may require long processing times. Especially when the constraints on acceptable response times in services with user interaction are considered, the end-to-end delay becomes an important performance criterion. In this paper, we make an analysis of the processing delay per device and the transmission delay per hop in a heterogeneous smart network. We identify the processes and the transmission links that dominate the end-toend delay based on our experiments on a power-managed smart lighting scenario.Keywords-end-to-end delay; heterogeneous networks; knowledge processor; smart space; smart lighting; semantic information broker ; and semantic interoperability.

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Cross-Domain Interoperability: A Case Study

Cited by 22 publications

References 3 publications

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

Geo-coding in Smart Environment: Integration Principles of Smart-M3 and Geo2Tag

The M3 architecture for smart spaces: Overview of semantic information broker implementations

Delay Performance in a Semantic Interoperability Architecture

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