Research of the Middleware Based Quality Management for Context-Aware Pervasive Applications
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With the rapid development of the information technology, it is inevitable that the distributed mobile computing will evolve to the pervasive computing gradually whose final goal is fusing the information space composed of computers with the physical space in which the people are working and living in. To achieve this goal, one of the problems is how to continuously monitor/capture and interpret the environment related information efficiently to assure high context awareness. Many attentions have been paid to the research of the context-aware pervasive applications. However, most of them just use the raw context directly or take just some aspects of the Quality of Context (QoC) into account. Therefore, we propose a middleware based context-aware framework that support QoC management in various layers. By this framework we can refinery raw context, discard duplicate and inconsistent context so as to protect and provide QoS-enriched context information of users to context-aware applications and services.Keywords:
Context management
Context awareness
Context model
With the rapid development of the information technology,it is inevitable that the distributed mobile computing will evolve to the pervasive computing gradually whose final goal is fusing the information space composed of computers with the physical space in which the people are working and living in.To achieve this goal,one of the problems is how to continuously monitor/capture and interpret the environment related information efficiently to assure high context awareness.Many attentions have been paid to the research of the context-aware pervasive applications.However,most of them just use the raw context directly or take just some aspects of the Quality of Context(QoC) into account.Therefore,we proposed a middleware based context-aware framework that supports QoC management in various layers.By this framework we can refine raw context,discard duplicate and inconsistent context so as to protect and provide QoS-enriched context information of users to context-aware applications and services.
Context management
Context awareness
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The ubiquitous computing environment focuses on recognizing the context and Physical entities, whereas, previous computing environments mainly focused on the conversational interactions between the computer and the user. For this reason, there has been an increase in the research of context aware computing environments. In previous researches , context services are designed using context ontology used in context aware middleware. So, context service cannot change the context ontology in execution time. We propose a hierarchical context ontology management for context aware service to change their ontology in execution time. And we also a resolution model for context conflict which is occurred in inference of context. We have designed a middleware based on this model and implemented the middleware. As the middleware is implemented on the OSGi framework, it can cause interoperability among devices such as computers, PDAs, home appliances and sensors. It can also support the development and operation of context aware services, which are required in the ubiquitous computing environment.
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Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware of and adapt to their changing contexts in highly dynamic environments. Now a days, vehicles have become an increasingly important and exciting test bed for ubiquitous computing (UbiComp), however, context-aware vehicle service to enable high adaptation of service to driver, vehicle or even road in ubiquitous environment is still little addressed in the literature. The context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. This paper focuses on building an ontology modeling approach for Context Management in Intelligent Pervasive Middleware for Context-Aware Vehicle Services. To support contextawareness, we embed capabilities of context modeling and context reasoning in an ontology-based context system, which focuses on management of the context and generates a consistent model which promises the common information representation and facilitates a development of context-aware services.
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Context-aware pervasive systems
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Location-based context awareness services can embody ubiquitous computing environments in all living environments. To achieve this, since location-based context awareness services need to be provided in various mobile devices, the configuration of open-type context awareness service is required. In this article, a spatio-temporal context manager, which serves as an important element in the ubiquitous location-based context awareness service, needs to be designed so as to be matched to an open-type platform. The suggested model includes a context manager, a spatio-temporal manager, an inference engine, a context history and a knowledge base. In particular, by introducing a spatio-temporal manager to the operation of inferring context awareness, a spatio-temporal context can be more variably inferred compared to conventional service.
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Component (thermodynamics)
Adaptability
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Context-aware pervasive systems
Ubiquitous robot
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Autonomic computing provides mechanisms for the self-management of computing systems. This paper proposes context prediction as an autonomic mechanism to improve the usability of ubiquitous computing environments; in our case, for behavioral prediction in an environment that supports independent living for ageing people. A purpose of this paper is to stimulate debate on how best to improve ubiquitous computing environments for those who inhabit them; in particular for those ageing people who wish to continue to live independently. We propose a layered and extensible context architecture that provides self-managed and self-configuration capabilities. In particular, in addition to the context provider and context service layers, we propose context prediction and context fusion layers with cross-layer context-quality capabilities. We envisage a distributed peer-to-peer architecture with some form of semantic overlay network facilitating autonomic communications within and beyond the ubiquitous home environment.
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Autonomic Computing
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End-user computing
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Pervasive computing presents an exciting realm where intelligent devices interact within the background of our environments to create a more intuitive experience for their human users. Context-awareness is a key requirement in a pervasive environment because it enables an application to adapt to the current situation. Context-awareness is best facilitated by a context management system that supports the automatic discovery, retrieval and exchange of context information by devices. Such a system must perform its functions in a pervasive computing environment that involves heterogeneous mobile devices which may experience intermittent connectivity and resource and power constraints. The objective of the chapter is to describe a robust and adaptable context management system. We achieve an adaptable context management system by adopting the autonomic computing paradigm, which supports systems that are aware of their surroundings and that can automatically react to changes in them. A robust context management system is achieved with an implementation based on widely accepted standards, specifically Web services and the Web Services Distributed Management (WSDM) standard.
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Context-aware pervasive systems
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Autonomic Computing
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본 논문에서 제안한 시스템은 유비쿼터스 컴퓨팅 환경에서 사용자에게 상황 인식 서비스와 주변 환경에 지능적인 상호 작용을 제공한다. 따라서, 유비쿼터스 컴퓨팅의 다양한 상황과 환경에서 시스템은 컨텍스트 정보를 수집과 분석을 하기 위해 상황 인식 능력을 필요 하게 된다. 그러나 현재의 상황 인식 시스템은 다양한 타입에서 컨텍스트의 체계적인 이용에 부족하고, 단지 몇몇 시스템들은 한정된 환경에서 각자 사용자의 선호도를 획득하는 학습 매커니즘을 가진다. 본 논문에서는, 유비쿼터스 컴퓨팅 환경에서 상황 인식을 위한 개괄적인 프레임워크를 제안한다. 본 프레엄워크는 다양한 센서로부터 컨텍스트의 다양한 타입을 쉽게 이용하고 생성할 수 있게 만들어졌다. 프레엄워크는 동적 환경에서 사용자에게 서비스를 제공하기 위하여 센서, 통합, 추론 그리고 학습 컨텍스트 정보를 제공한다. 그리고 사용자의 건강을 실시간으로 관리할 수 있는 u-Health 시스템에 제안한 프레임워크를 적용을 하여 구현을 하였다. The systems in the ubiquitous computing environment need to provide users with context-aware services, intelligently interacting with the surrounding environment. Therefore, the systems in the ubiquitous computing environment require context-awareness ability in order to gather and analyze context information in various situations and environments. However, existing context-aware systems lack the ability to systematically generate and handle various types of context information, and only a few systems have ability learning from environment. In this paper, a general context model is defined to describe various contexts and a context-awareness framework is implemented based in the model, which makes it straightforward to handle and generate various types of context from diverse sensor. The framework is designed to allow a system to sensed, combined, inferred, and learned context information, in order to provide users with services in dynamic environments. We have implemented the proposed framework and applied it to a u-Health management system.
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Context management
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In this article we highlight and discuss prominent aspects of context and adaptively in pervasive computing environments along with characteristics and categories of context, and context-aware systems. We also briefly refer to use, management and modeling of context in context-aware systems. This paper is not meant to provide an exhaustive review of literature but rather it aims to integrate and extend important theoretical aspects found in the literature. Our perspective reflects context from application and system development point of view, based on the expanded computing setting which is mobile, dynamic,heterogeneous and highly connected (i.e. pervasive computing) while keeping the user in the center. This paper constructs theoretical base of our future research which is enabling anytime and anywhere learning in adaptive learning environments.
Context-aware pervasive systems
Context awareness
Context model
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With the rapid development of information technology, it is inevitable that the distributed mobile computing will evolve to pervasive computing gradually whose final goal is fusing the information space composed of computers with the physical space in which the people are working and living in. However, most of WSN contexts coming from may be more and more unstructured, widespread and massive. Therefore, to realize precise location, adaptive reasoning and reliable fusion of these kinds of contexts, we should sense the changes of them efficiently and accurately in real time. One of the problems is how to assure the reliability of context fusion in the complex situations context fluctuating frequently. Many attentions have been paid to the research of the context-aware pervasive applications. However, most of them just use the raw context directly or take just some aspects of the Quality of Context (QoC) into account. Therefore, we propose an uncertain context fusion framework that supports QoC management in various layers. By this framework, we can use threshold management, quality factor management and inconsistent context management to protect and provide QoS-enriched context fusion efficiently for context-aware applications and services such as complex Internet of Vehicles.
Context management
Context awareness
Sensor Fusion
Context model
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