A Preference-Based Application Framework for Resource-Bounded Context-Aware Agents

Abstract

Abstract. Context-awareness is an essential component of mobile and pervasive computing. It refers to the concept that an application understands its context, reason about its current situation, and provide relevant information and/or services to the users. One of the main challenges of context-aware distributed mobile computing is the dynamic adaptation to changes in the resource-bounded operating environment with user preferences. For example, a depersonalized context-aware application may exhibit behavior that is not anticipated by its user in a given situation. In this paper, we present a personalized preference model for resource-bounded context-aware applications, which provides support for the development and execution of context-aware applications using a declarative language. We implement a simple example system that demonstrates the effectiveness of the approach in a real-world scenario.

An Efficient Rule-Based Distributed Reasoning Framework for Resource-bounded Systems

“…The output produced considering all the rules and the set of reduced rules should be the same provided the preferences are set accordingly [52,53].…”

“…Therefore, we do not consider them unless required. The enhanced preference mechanism is based on our previous works from [52,53]. The structure of rule ordering can be opt-in as an added optimization feature.…”

“…Whenever 0 is encountered it represents that the rule cannot fully match with the facts, the process is terminated and the next rule is selected for a check. A typical rule format of our framework can be found in [52], while some changes are made when preference is intended. The typical structure of a rule looks like this:…”

“…Maximal size of the preference sets In this technique, the preference sets are taken into consideration [52]. It is more complex than the previous method, and with a more space saving mechanism when preferences are supposed to be implemented.…”

Modeling and Reasoning about Preference-Based Context-Aware Agents over Heterogeneous Knowledge Sources

“…Here we limit our discussion more on the preference side, and how the preference sets are generated, while the execution of the rules remains the same as described in [10]. In our recent work [34], we have presented initial experiment on a real world scenario considering the basic preferences and not the fact-based preference. In this system modeling, we focus our discussion on fact-based preference.…”