Collaborative joins in a pervasive computing environment

Perich, Filip; Joshi, Anupam; Yesha, Yelena; Finin, Tim

doi:10.1007/s00778-004-0127-3

Cited by 9 publications

(4 citation statements)

References 28 publications

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“…While existing context query languages support only a subset of the features mentioned above, CQL stands out by supporting all of them. This is also supported by the evaluation presented in Haghighi et al, which identified the CML and the RDF‐based MoGATU as the two most sophisticated systems. However, both of them lack either support for heterogeneous representations and incorporation of ontologies or the provisioning of elaborate aggregation and filtering mechanisms.…”

Section: Reference Architecturementioning

confidence: 84%

An MDD‐based method for building context‐aware applications with high reusability

Paspallis

2019

J Software Evolu Process

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Adding context -awareness capabilities to modern mobile and pervasive computing applications (apps) is becoming a mainstream activity in the software engineering community. In this respect, many context models and middleware architectures have been proposed with the aim to provide the developers with tools and abstractions that make it easier to produce context-aware applications. However, current solutions suffer from relatively low reusability and lack ease-of-use. In this paper, we propose a two-layer approach based on model-driven development: At the higher layer, we introduce the design of reusable context plug-ins, which can be used to monitor low-level context data and to infer higher-level information about the users, their computing infrastructure, and their interaction. At the lower layer, the plug-ins themselves are synthesized using more elementary, reusable components. We argue that this development approach provides significant advantages to the developers, as it enables them to design, implement, reuse, and maintain the codebase of context-aware apps more efficiently.To evaluate this approach, we demonstrate it in the context of a two-part example application and assess it both qualitatively and quantitatively. KEYWORDScode generation, context awareness, MDD, middleware, plug-in, reusability INTRODUCTIONContext awareness is one of the most sought-after features for modern mobile and pervasive computing applications. Understanding and using context allows applications to identify and predict intention, thus allowing for better and richer human-computer interaction.Researchers have proposed various approaches to ease the task of designing and implementing applications that are context-aware and self-adaptive. At their core, many of these build on reusable code, ranging from the early works of Dey 1 to more recent, plug-in-based architectures such as those described in the previous studies. 2-5 These approaches are designed to allow the applications, which are using them to inquire and access arbitrary context data types. In this respect, the context-awareness and context-inferring parts are separated from the functional logic of the applications by means of reusable context plug-ins (ie, individually deployable units, which provide mechanisms for collecting and processing context data, and inferring higher-level context information). At the same time, many context models and middleware architectures were proposed and documented in the literature. 6,7 Software reuse is at the core of many of those approaches. At a higher level, reuse covers all software engineering phases and ''can be supported by different types of methods, including ad hoc, opportunistic, adaptive, systematic, black-box, whitebox, etc.'' 8 A common drawback in these approaches is that the developers are required to invest a significant amount of time to develop customized components, which are used for collecting, processing, inferring, storing, querying, and accessing context data. Moreover, the developed components are then harder...

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Section: Reference Architecturementioning

confidence: 84%

An MDD‐based method for building context‐aware applications with high reusability

Paspallis

2019

J Software Evolu Process

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“…The SOCAM (Service-oriented Context-Aware Middleware) architecture [15,16] describes context queries in OWL that is a RDF-based language and supports complex context queries by combining predicates and Boolean algebra. Although the structure of RDFbased languages is more suitable for context queries, it is not as flexible as SQL and it can result in large amounts of overheads as it requires creation of many classes, subclasses and relationships [17].…”

Section: Rdf-based Query Languagesmentioning

confidence: 99%

“…One of the innovative works in the area of querying context is CQP (Collaborative Query Processing) protocol that has been implemented on top of MoGATU framework [17]. MoGATU is a profile-driven and proactive peer-to-peer semantic data management system for pervasive environments that defines queries in DAML-OIL [18].…”

Section: Rdf-based Query Languagesmentioning

confidence: 99%

“…MoGATU is a profile-driven and proactive peer-to-peer semantic data management system for pervasive environments that defines queries in DAML-OIL [18]. The CQP model is based on the concept of nested-loop joins and the principles of Contract Nets [17]. Using the CQP protocol, mobile devices can query their neighboring devices by decomposing queries and assigning them to different peer devices.…”

Section: Rdf-based Query Languagesmentioning

confidence: 99%

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An Evaluation of Query Languages for Context-Aware Computing

Haghighi

Zaslavsky

Krishnaswamy

17th International Conference on Database and Expert Systems Applications (DEXA'06)

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Context-awareness highly depends on easy and prompt access to the right information and this needs overcoming challenges of query expression and processing of context information. One of the main considerations in querying context is selecting and applying an appropriate and expressive query language for defining user's context needs. This paper presents an overview of current languages used for querying context and investigates their strengths and limitations in expressing different aspects of context.

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