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• W2186087570 abstract "In mobile environments, mobile devices move continuously and have limited resources as computation, energy, and memory. Data management is one of the biggest challenges in this environment. Using the context in mobile environments is receiving considerable attention to meet these challenges. In the context-aware systems, the application can uses the contextual information such as user’s location, day time, nearby people and devices and user’s activity in a useful way to solve some mobile environmental issues. Context retrieval problem is one of the key issues in context awareness computing. In this paper, we describe the terms of context-aware systems and context-aware middleware. Also, we give an exemplary overview about context’s definitions and classifications. In addition to introducing new context classification approaches will introduce in this paper. Furthermore, this paper develops context retrieval approaches in mobile environments to reduce context retrieval energy consumption. Finally, the simulation results show that the proposed context retrieval approaches are much better than the traditional approach." @default.
• W2186087570 created "2016-06-24" @default.
• W2186087570 creator A5051852523 @default.
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• W2186087570 date "2014-01-01" @default.
• W2186087570 modified "2023-09-27" @default.
• W2186087570 title "Probabilistic Context Retrieval Time-Based Algorithms in Dynamic Environments" @default.
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• W2186087570 hasPublicationYear "2014" @default.
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