A Novel Multi-Channel Data Broadcast Scheme for Multimedia Database Systems

MultiMedia DataBase Management System (MMDBMS) becomes more popular in recent years, which supports complex and large multimedia data like images, audios, and videos etc. Data Broadcasting is an attractive approach for data dissemination to improve the limitations in mobile environment, such as narrow bandwidth, unreliable connections, and battery limitation. However, existing data broadcast schemes are inefficient for MMDBMS. In this paper, we present four novel multimedia data broadcast schemes (namely, SDAA, MDAA, AEA, and COA) specifically for wireless multichannel communications. The major strategies are scalable coding to generate data segments to different qualities, indexing and channel assignment to minimize the expected waiting time for clients. We prove theoretically that SDAA is a 2-approximation. COA performs best when we release the constraints and it can be judged as an theoretical lower bound, while AEA outputs local optimal solution with quality allocation constraints. Finally, SDAA+AEA form a best scheduling for practical applications. We also provide numerical experiments to evaluate the system performance, proving the efficiency of our schemes.

[1]  Ge-Ming Chiu,et al.  Efficient Dissemination of Transaction-Consistent Data in Broadcast Environments , 2007, IEEE Transactions on Knowledge and Data Engineering.

[2]  Ming-Syan Chen,et al.  Dependent data broadcasting for unordered queries in a multiple channel mobile environment , 2004, IEEE Transactions on Knowledge and Data Engineering.

[3]  Elvis Gaona,et al.  Comparative Analysis and Tests of Intelligent Streaming Video on Demand for Next Generation Networks: Two Colombian Study Cases , 2011, ICNS 2011.

[4]  Shojiro Nishio,et al.  Scheduling methods for broadcasting multiple continuous media data , 2003, MMDB '03.

[5]  A. Osseiran,et al.  A MIMO framework for 4G systems: WINNER concept and results , 2007, 2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications.

[6]  Andrea J. Goldsmith,et al.  Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks , 2004, IEEE Journal on Selected Areas in Communications.

[7]  Yungho Leu,et al.  Efficient data broadcast schemes for mobile computing environments with data missing , 2005, Inf. Sci..

[8]  Dik Lun Lee,et al.  Adaptive data delivery in wireless communication environments , 2000, Proceedings 20th IEEE International Conference on Distributed Computing Systems.

[9]  Ying Cai,et al.  An Overlay Subscription Network for Live Internet TV Broadcast , 2006, IEEE Transactions on Knowledge and Data Engineering.

[10]  Ming-Syan Chen,et al.  Dependent Data Broadcasting for Unordered Queries in a Multiple Channel Mobile Environment , 2004, IEEE Trans. Knowl. Data Eng..

[11]  Ming-Syan Chen,et al.  On Bandwidth-Efficient Data Broadcast , 2008, IEEE Transactions on Knowledge and Data Engineering.

[12]  Zongpeng Li,et al.  Auction-based P2P VoD streaming: Incentives and optimal scheduling , 2012, TOMCCAP.

[13]  Alan A. Bertossi,et al.  Efficient heuristics for data broadcasting on multiple channels , 2008, Wirel. Networks.

[14]  Guohong Cao,et al.  Stretch-optimal scheduling for on-demand data broadcasts , 2001, Proceedings Tenth International Conference on Computer Communications and Networks (Cat. No.01EX495).

[15]  Stanley B. Zdonik,et al.  Research in Data Broadcast and Dissemination , 1998, AMCP.

[16]  SangKeun Lee,et al.  Efficient, Energy Conserving Transaction Processing in Wireless Data Broadcast , 2006, IEEE Transactions on Knowledge and Data Engineering.

[17]  Tomasz Imielinski,et al.  Data on Air: Organization and Access , 1997, IEEE Trans. Knowl. Data Eng..

[18]  Sungwon Jung,et al.  Effective Generation of Data Broadcast Schedules with Different Allocation Numbers for Multiple Wireless Channels , 2008, IEEE Transactions on Knowledge and Data Engineering.

[19]  S. Pekowsky,et al.  Multimedia data broadcasting strategies , 2001 .