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Issue No.03 - March (2010 vol.9)
pp: 390-404
Shiow-yang Wu , National Dong Hwa University, Hualien
Hsiu-Hao Fan , EDIMAX Technology Co., Ltd., Taipei Hsien
Most users in a mobile environment are moving and accessing wireless services for the activities they are currently engaged in. We propose the idea of complex activity for characterizing the continuously changing complex behavior patterns of mobile users. For the purpose of data management, a complex activity is modeled as a sequence of location movement, service requests, the cooccurrence of location and service, or the interleaving of all above. An activity may be composed of subactivities. Different activities may exhibit dependencies that affect user behaviors. We argue that the complex activity concept provides a more precise, rich, and detail description of user behavioral patterns which are invaluable for data management in mobile environments. Proper exploration of user activities has the potential of providing much higher quality and personalized services to individual user at the right place on the right time. We, therefore, propose new methods for complex activity mining, incremental maintenance, online detection and proactive data management based on user activities. In particular, we devise prefetching and pushing techniques with cost-sensitive control to facilitate predictive data allocation. Preliminary implementation and simulation results demonstrate that the proposed framework and techniques can significantly increase local availability, conserve execution cost, reduce response time, and improve cache utilization.
Activity mining, proactive data management, prefetching, pushing, mobile environments.
Shiow-yang Wu, Hsiu-Hao Fan, "Activity-Based Proactive Data Management in Mobile Environments", IEEE Transactions on Mobile Computing, vol.9, no. 3, pp. 390-404, March 2010, doi:10.1109/TMC.2009.139
[1] I.F. Akyildiz and W. Wang, “The Predictive User Mobility Profile Framework for Wireless Multimedia Networks,” IEEE/ACM Trans. Networking, vol. 12, no. 6, pp. 1021-1035, Dec. 2004.
[2] W.-S. Soh and H. Kim, “QoS Provisioning in Cellular Networks Based on Mobility Prediction Techniques,” IEEE Comm. Magazine, vol. 41, no. 1, pp. 86-92, Jan. 2003.
[3] W. Su, S.-J. Lee, and M. Gerla, “Mobility Prediction and Routing in Ad Hoc Wireless Networks,” Int'l J. Network Management, vol. 11, no. 1, pp. 3-30, Jan. 2001.
[4] I.F. Akyildiz, J. Mcnair, J.S.M. Ho, H. Uzunalioglu, and W. Wang, “Mobility Management in Next-Generation Wireless System,” Proc. IEEE, vol. 87, no. 8, pp. 1347-1384, Aug. 1999.
[5] W.-C. Peng and M.-S. Chen, “Mining User Moving Patterns for Personal Data Allocation in a Mobile Computing System,” Proc. 29th Int'l Conf. Parallel Processing, pp. 573-580, Aug. 2000.
[6] C.-H. Yun and M.-S. Chen, “Mining Mobile Sequential Patterns in a Mobile Commerce Environment,” IEEE Trans. Systems, Man, and Cybernetics, Part C, vol. 37, no. 2, pp. 278-295, Mar. 2007.
[7] X. Li and Q. Li, “User Pattern Analysis in Cellular Systems,” Proc. Seventh IEEE Int'l Conf. Mobile Data Management, 2006.
[8] G. Resta and P. Santi, “WiQoSM: An Integrated Qos-Aware Mobility and User Behavior Model for Wireless Data Networks,” IEEE Trans. Mobile Computing, vol. 7, no. 2, pp. 187-198, Feb. 2008.
[9] S.-y. Wu and Y.-t. Chang, “A User-Centered Approach to Active Replica Management in Mobile Environments,” IEEE Trans. Mobile Computing, vol. 5, no. 11, pp. 1606-1619, Nov. 2006.
[10] A. Yamasaki, H. Yamaguchi, S. Kusumoto, and T. Higashino, “Mobility-Aware Data Management on Mobile Wireless Networks,” Proc. IEEE 65th Vehicular Technology Conf., pp. 679-683, 2007.
[11] R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules in Large Databases,” Proc. Int'l Conf. Very Large Databases (VLDB), pp. 487-499, 1994.
[12] W.-C.P. Jiun-Long Huang and M.-S. Chen, “Exploring Group Mobility for Replica Data Allocation in a Mobile Environment,” Proc. 12th Int'l Conf. Information and Knowledge Management, pp.161-168, 2003.
[13] J.-L. Huang and M.-S. Chen, “On the Effect of Group Mobility to Data Replication in Ad-Hoc Networks,” IEEE Trans. Mobile Computing, vol. 5, no. 5, pp. 492-507, May 2006.
[14] W. Ma, Y. Fang, and P. Lin, “Mobility Management Strategy Based on User Mobility Patterns in Wireless Networks,” IEEE Trans. Vehicular Technology, vol. 56, no. 1, pp. 322-330, Jan. 2007.
[15] W.-C. Peng and M.S. Chen, “Allocation of Shared Data Based on Mobile User Movement,” Proc. Third Int'l Conf. Mobile Data Management, pp. 105-112, 2002.
[16] M. Sricharan, V. Vaidehi, and P. Arun, “An Activity Based Mobility Prediction Strategy for Next Generation Wireless Networks,” Proc. IFIP Int'l Conf. Wireless and Optical Comm. Networks, 2006.
[17] R. Agrawal and R. Srikant, “Mining Sequential Patterns,” Proc. 11th Int'l Conf. Data Eng., pp. 3-14, 1995.
[18] K. Gouda, M. Hassaan, and M.J. Zaki, “Prism: A Primal-Encoding Approach for Frequent Sequence Mining,” Proc. Seventh IEEE Int'l Conf. Data Mining, pp. 487-492, 2007.
[19] J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu, “Mining Sequential Patterns by Pattern-Growth: The Prefixspan Approach,” IEEE Trans. Knowledge and Data Eng., vol. 16, no. 11, pp. 1424-1440, Nov. 2004.
[20] C.-C. Yu and Y.-L. Chen, “Mining Sequential Patterns from Multidimensional Sequence Data,” IEEE Trans. Knowledge and Data Eng., vol. 17, no. 1, pp. 136-140, Jan. 2005.
[21] S.-Y. Wu and Y.-L. Chen, “Mining Nonambiguous Temporal Patterns for Interval-Based Events,” IEEE Trans. Knowledge and Data Eng., vol. 19, no. 6, pp. 742-758, June 2007.
[22] V.S. Tseng and K.W. Lin, “Mining Sequential Mobile Access Patterns Efficiently in Mobile Web Systems,” Proc. 19th Int'l Conf. Advanced Information Networking and Applications, vol. 2, pp. 762-767, Mar. 2005.
[23] H. Cao, N. Mamoulis, and D. Cheung, “Mining Frequent Spatio-Temporal Sequential Patterns,” Proc. Fifth IEEE Int'l Conf. Data Mining, 2005.
[24] V.S. Tseng, H.-C. Lu, and C.-H. Huang, “Mining Temporal Mobile Sequential Patterns in Location-Based Service Environments,” Proc. Int'l Conf. Parallel and Distributed Systems, vol. 1, pp. 1-8, 2007.
[25] W.-C. Peng and M.-S. Chen, “Shared Data Allocation in a Mobile Computing System-Exploring Local and Global Optimization,” IEEE Trans. Parallel and Distributed Systems, vol. 16, no. 4, pp. 374-384, Apr. 2005.
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