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Semantic caching was originally used for structural data objects such as 2D location data and cannot be directly applied to mobile image data access. First, traditional semantic caching relies on exact match and therefore is not suitable for approximate and similarity-based queries. Second, the semantic description of cached data is defined on query context instead of data content, which leads to inefficient use of cache storage. Third, the semantic description of cached data does not reflect the popularity of the data, making it difficult to conduct popularity-driven content analysis and prediction. To facilitate content-based image retrieval in wireless ad hoc networks, we propose a semantic-aware image caching (SAIC) scheme in this paper. The proposed scheme can efficiently utilize the cache space and significantly reduce the cost of image retrieval. The proposed SAIC scheme is based on several innovative ideas: 1) multilevel representation of the semantic contents, 2) association-based and Bayesian probability-based content prediction, 3) constraint-based representation method showing the semantic similarity between images, 4) nonflooding query processing, and 5) adaptive cache consistency maintenance. The proposed model is introduced, and through extensive simulation, its behavior has been compared against two state-of-the-art ad hoc caching schemes as advanced in the literature.