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Scalable architecture for context-aware activity-detecting mobile recommendation systems
One of the main challenges in building multi-user mobile information systems for real-world deployment lies in the development of scalable systems. Recent work on scaling infrastructure for conventional web services using distributed approaches can be applied to the mobile space, but limitations inherent to mobile devices (computational power, battery life) and their communication infrastructure (availability and quality of network connectivity) challenge system designers to carefully design and optimize their software architectures. Additionally, notions of mobility and position in space, unique to mobile systems, provide interesting directions for the segmentation and scalability of mobile information systems. In this paper we describe the implementation of a mobile recommender system for leisure activities, codenamed Magitti, which was built for commercial deployment under stringent scalability requirements. We present concrete solutions addressing these scalability challenges, with the goal of informing the design of future mobile multi-user systems.
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citation
Roberts, M. ; Ducheneaut, N. ; Begole, J. ; Partridge, K .; Price, R. , Bellotti, V. , Walendowski, A. , Rasmussen, P. Scalable architecture for context-aware activity-detecting mobile recommendation systems. Proceedings ADAMUS Workshop at 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2008); 2008 June 23-26; Newport Beach, CA. NY: IEEE; 2008; 1-6.
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Copyright © IEEE, 2008. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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