On-demand data broadcast with deadlines for avoiding conflicts in wireless networks

The paper presents UPF algorithm to solve data schedule problem in on-demand data broadcast for a set of requests.Two well-known conflicts are considered in this algorithm.The UFP algorithm tries best to allocate all data items of a request in its deadlines.Increasing the number of broadcast channels will reduce deadline miss ratio and access latency in different sizes of databases.Increasing the request size will increase deadline miss ratio and access latency in different sizes of databases. On-demand data broadcast (ODDB) has attracted increasing interest due to its efficiency of disseminating information in many real-world applications such as mobile social services, mobile payment and mobile e-commerce. In an ODDB system, the server places client requested data items received from the uplink to a set of downlink channels for downloading by the clients. Most existing work focused on how to allocate client requested data items to multiple channels for efficient downloading, but did not consider the time constraint of downloading which is critical for many real-world applications. For a set of requests with deadlines for downloading, this paper proposes an effective algorithm to broadcast data items of each request within its specified deadline using multiple channels under the well-known 2-conflict constraint: two data items conflict if they are broadcast in the same time slot or two adjacent time slots in different channels. Our algorithm adopts an approach of allocating most urgent and popular data item first (UPF) for minimizing the overall deadline miss ratio. The performance of the UPF method has been validated by extensive experiments on real-world data sets against three popular on-demand data broadcast schemes.

[1]  Rafael Alonso,et al.  Broadcast disks: data management for asymmetric communication environments , 1995, SIGMOD '95.

[2]  Victor C. S. Lee,et al.  Data scheduling for multi-item requests in multi-channel on-demand broadcast environments , 2008, MobiDE '08.

[3]  Yan Shi,et al.  Efficient data retrieval scheduling for multi-channel wireless data broadcast , 2012, 2012 Proceedings IEEE INFOCOM.

[4]  Ta-Chih Su,et al.  On-Demand Data Broadcasting for Data Items with Time Constraints on Multiple Broadcast Channels , 2010, DASFAA Workshops.

[5]  Joseph Kee-Yin Ng,et al.  Scheduling Real-Time Multi-item Requests in On-Demand Broadcast , 2008, 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications.

[6]  Herb Schwetman,et al.  CSIM19: a powerful tool for building system models , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[7]  Heonshik Shin,et al.  A hybrid scheduling scheme for data broadcast over a single channel in mobile environments , 2012, J. Intell. Manuf..

[8]  Kai Liu,et al.  Performance analysis of data scheduling algorithms for multi-item requests in multi-channel broadcast environments , 2010 .

[9]  Nicolas Schabanel.  The Data Broadcast Problem with Preemption , 2000, STACS.

[10]  Michael J. Franklin,et al.  Scheduling for large-scale on-demand data broadcasting , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

[11]  Jianliang Xu,et al.  Time-critical on-demand data broadcast: algorithms, analysis, and performance evaluation , 2006, IEEE Transactions on Parallel and Distributed Systems.

[12]  J. Wong,et al.  Broadcast Delivery , 1988, Proc. IEEE.

[13]  Ming-Syan Chen,et al.  Scheduling dependent items in data broadcasting environments , 2006, SAC '06.

[14]  Mostafa H. Ammar,et al.  Analysis of Broadcast Delivery in a Videotex System , 1985, IEEE Transactions on Computers.

[15]  Indrajit Ray,et al.  Utility driven optimization of real time data broadcast schedules , 2012, Appl. Soft Comput..

[16]  Michael J. Franklin,et al.  R × W: a scheduling approach for large-scale on-demand data broadcast , 1999, TNET.

[17]  Victor C. S. Lee,et al.  On-demand broadcast for multiple-item requests in a multiple-channel environment , 2010, Inf. Sci..

[18]  Enhong Chen,et al.  Profit-based scheduling and channel allocation for multi-item requests in real-time on-demand data broadcast systems , 2012, Data Knowl. Eng..

[19]  Chuan-Ming Liu,et al.  Efficient scheduling algorithms for disseminating dependent data in wireless mobile environments , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[20]  Nitin H. Vaidya,et al.  Scheduling data broadcast in asymmetric communication environments , 1999, Wirel. Networks.

[21]  Krithi Ramamritham,et al.  Broadcast on demand: efficient and timely dissemination of data in mobile environments , 1997, Proceedings Third IEEE Real-Time Technology and Applications Symposium.

[22]  Shamkant B. Navathe,et al.  Efficient Data Allocation over Multiple Channels at Broadcast Servers , 2002, IEEE Trans. Computers.

[23]  Victor C. S. Lee,et al.  On the performance of real-time multi-item request scheduling in data broadcast environments , 2010, J. Syst. Softw..