International Journal of Computer Vision
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A performance comparison of multi-hop wireless ad hoc network routing protocols
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
Multimedia access and retrieval (panel session): the state of the art and future directions
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Using semantic caching to manage location dependent data in mobile computing
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Proactive Power-Aware Cache Management for Mobile Computing Systems
IEEE Transactions on Computers
Sequential and Parallel Algorithms for Mixed Packing and Covering
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
UCAN: a unified cellular and ad-hoc network architecture
Proceedings of the 9th annual international conference on Mobile computing and networking
Learning a Locality Preserving Subspace for Visual Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Manifold-ranking based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Parameterized neighborhood-based flooding for ad hoc wireless networks
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume II
Journal of Parallel and Distributed Computing
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Caching has been widely used in the mobile environments to improve system performance. However, traditional semantic caching methodology was proposed for structural data such as 2-D location, and cannot be directly used for image data accessing: First, traditional caching relies on exact match and therefore is unsuitable for similarity-based queries. Second, the description of cached data is defined based on query context instead of data content, which leads to inefficient use of storage. Third, the description of cached data does not reflect the popularity of the data, making it inefficient in providing QoS-related services. To facilitate content-based image retrieval in mobile environments, we propose a semantic-aware image caching scheme (SAIC) 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) multi-level partitioning of the semantic space, 2) association and Bayesian probability based content prediction, 3) constraint-based representation method showing the semantic similarity between images, 4) non-flooding query processing, and 5) adaptive QoS-aware cache consistency maintenance. The proposed model is introduced and through extensive simulation its behavior has been compared against two state-of-the-art caching schemes as advanced in the literature.