Quality of Context: models and applications for context-aware systems in pervasive environments

Abstract

Limitations of sensors and the situation of a specific measurement can affect the quality of context information that is implicitly collected in pervasive environments. The lack of information about Quality of Context (QoC) can result in degraded performance of context-aware systems in pervasive environments, without knowing the actual problem. Context-aware systems can take advantage of QoC if context producers also provide QoC metrics along with context information.In this paper, we analyze QoC and present our model for processing QoC metrics. We evaluate QoC metrics considering the capabilities of sensors, circumstances of specific measurement, requirements of context consumer, and the situation of the use of context information. We also illustrate how QoC metrics can facilitate in enhancing the effectiveness and efficiency of different tasks performed by a system to provide context information in pervasive environments. IntroductionPervasive environments are characterized by a plethora of computing and communication enabled devices that diffuse themselves in everyday living and become invisible (Weiser, 1991). These devices implicitly sense and provide context, a core task in making a system adaptable, that is far more complicated than explicit input to the system (Gray & Salber, 2001;Mostefaoui et al., 2004). Quality of context information is deteriorated during this process and contrary to general assumption context information can be incomplete, inaccurate, and ambiguous (Dey, 2001;Henricksen et al., 2002). Inadequate quality of context information severely influences the adaptiveness of context-aware applications (Dey, 2001;Chen & Kotz, 2002;Henricksen & Indulska, 2004). Context-aware applications also perform extra effort to cope with uncertainty of context information (Ranganathan et al., 2004). Quality of Context (QoC), a measurable metric that provides information about the quality of context, can help resolving uncertain and conflicting situations about context information. Therefore, context-aware applications can take advantage of QoC if they are provided with usable QoC metrics that are evaluated considering their requirements regarding the collection, processing, and provision of context information. Currently, there is not only a lack of solutions that evaluate QoC metrics and pass them along with context information to context consumers, but also existing definitions of QoC ignore its multi-facetted nature and consider it as an objective term.In this paper we consider both objective and subjective views of QoC and redefine QoC. The objective view of QoC presents quality of context information independent of the requirements of a context consumer while the subjective view of QoC considers quality of context information as https://www.cambridge.org/core/terms. https://doi

An adaptive environment based on Moodle with treating of quality of context

“…For Manzoor et al (2010), QoC indicates the degree of conformity of context collected by the sensors to the situation prevailing in the environment and the requirements of a particular context consumer.…”

“…Research conducted by different authors, such as Sheikh et al (2007), Buchholz and Schiffers (2003), Manzoor et al (2010) and Nazario et al (2012), showed no standardisation for nomenclature and definitions to those parameters; many authors defined a set of parameters, often with different names and the same or similar meanings. One example is the definition of the of Up-to-Dateness and Timeliness parameters, which are used in different works by the same author, but whose meanings are the same.…”

“…Access Right: shows the extent to which the information owner allows the context consumer to access the information (Manzoor et al, 2010). Access to certain pages can be restricted to ensure that the user' context will not be affected.…”

“…Representation consistency: the measure in which the context representation format is consistent with the requirements of consumers (Manzoor et al, 2010). Combined to the accuracy stipulated in Zheng et al (2011), which are used in two decimals after the comma, the Representation of Consistency checks if the data format conforms to the require one in order to form the users context.…”

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“…The Quality of Context (QoC) is defined in [24], and is oriented to characterize the state of the end-point device [106].…”