Reasoning about Context in Uncertain Pervasive Computing Environments

Abstract. Context-aware computing has to deal with a huge amount of context data. Taking into account the quality of these data becomes a corner stone of an efficient context management solution. Information on the quality of context helps taking appropriate decisions and allows to identify uncertain context information saving processing time for deriving a pertinent description of the observed phenomenon. This paper presents a work in progress for integrating Quality of Context in COSMOS (COntext entitieS coMpositiOn and Sharing) [4,13], a component-based framework for managing context data in ubiquitous environments, and illustrates it throughout the example of the composition of context information to implement a network connectivity vs energy adaptation situation.

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“…Depending on the amount of available knowledge, we envisage to experiment a method like FSI (Fuzzy Situation Inference) [9].…”

Section: Discussionmentioning

confidence: 99%

A Framework for Quality of Context Management

Abid

Chabridon

Conan

2009

Lecture Notes in Computer Science

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“…Hence, we utilize the cost-performance index (CPI) scheme to optimize the approach selection. The scheme combines fuzzy set (Zadeh, 1965) and the weight of context (Haghighi et al, 2008). The reason we use fuzzy set is to compare the performance and cost between approaches instead of using static values.…”

Section: Definition 5) the Time-span Of O (Denoted By ) Is Computed Bymentioning

confidence: 99%

Adaptive Mobile Cloud Workflow Management System for Service Discovery in Proximity-Based Internet of Things

Chang¹,

Srirama²,

Mass³

2015

STSC

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In the near future, Industrial Internet of Things can help people in realizing the smart cities and urban sensing scenarios by providing various useful spatial information. Based on real-time resource discovery and data retrieval technologies, mobile devices can continuously interact with surrounding things and provide real-time content mashup services. However, continuous resource discovery and content mashup processes can be resource intensive for mobile devices. In order to reduce the resource usage, certain tasks of the mobile application can be delegated to the utility Cloud. Nevertheless, task offloading isn't always cost-efficient and the decision to offload a process needs to be context-aware. This paper proposes a service-oriented workflow-based mobile Cloud middleware framework for balancing the task allocation between the mobile terminal and Cloud. The proposed cost-performance index scheme assists the decision-making of the workflow configuration by utilizing the fuzzy set and weight of context schemes. The evaluation consists of a data set generated by experts' preferences considering fuzzy logic and inference, on which linear regression was performed, for extracting the weights of the context. The prototype has been implemented in real devices and the evaluation has shown that the workflow system can automatically configure the task allocation based on resource availability.

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“…Reasoning based on formalised conceptualisations can be used to some extent for consistency checking and verification and validation of structural and behavioural properties of the software. Furthermore, various AI techniques can be applied to alleviate imperfectness (Anagnostopoulos and Hadjiefthymiades, 2009;Bardram, 2005;Binh An et al, 2005;Haghighi et al, 2008;Ranganathan et al, 2004;Zhongli and Yun, 2004); however, such techniques do not provide 100% success. Approaches based on human intervention, which will be further discussed in Section 2.4, seem to be required where fully automated mechanisms are not enough.…”

Section: Anonymousmentioning

confidence: 99%

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

Soylu

Causmaecker

Preuveneers

et al. 2011

IJMSO

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Abstract:Increasing demand for large scale and highly complex systems and applications, particularly with the emergence of pervasive computing and the impact of adaptive systems, introduces significant challenges for software development, as well as for user-machine interaction. Therefore, a perspective shift on software development and user-machine interaction is required. An amalgamation of model driven development and ontologies has been envisaged as a promising direction in recent literature. In this paper, we investigate this merged approach and conclude that a merger of both approaches, from formal modelling and knowledge representation perspective, on the one hand enables use of ontologies at run-time together with rules, prominently in terms of run-time reasoning, dynamic adaptations, software intelligibility, self-expressiveness, user involvement, and user situation awareness; and on the other hand at development time, prominently in terms of automated and incremental code generation, requirement adaptability, preservation of application knowledge, and validation and verification of structural and behavioural properties of the software. The core contribution of this paper lies in providing an elaborate and exploratory discussion of the problem and solution spaces along with a multidisciplinary meta-review and identification of complementary efforts in literature required to realise a merged approach.

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Reasoning about Context in Uncertain Pervasive Computing Environments

Cited by 45 publications

References 19 publications

A Framework for Quality of Context Management

A Framework for Quality of Context Management

Adaptive Mobile Cloud Workflow Management System for Service Discovery in Proximity-Based Internet of Things

Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review

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