..............................
            ..............................
            ..............................
            
Modelling Concurrent Mobile Transactions Execution in Broadcasting Environments
        
        Broadcast   is   an   efficient   and   scalable   method   for   resolving   the   bandwidth   limitation   in   a   wireless   environment.  
There   is   a   trade-off   between   clients’   access   time   and   throughput   for   update   mobile   transactions   in   on-demand   data  
dissemination environments.  Data scheduling at  the fixed server  can allow  more transactions  to commit  while retaining the  
access  time  for each transaction. In this paper, we present  a data scheduling scheme  for both read only and update mobile  
transactions in pull-based broadcasting environments. Rather than consider access time, which is well studied elsewhere in [1,  
2, 3], our concern is  to examine the probability that a mobile transaction is able to avoid conflict and commit. Specifically, a  
set of formulas giving an analysis of this probability is examined. Furthermore, a report of a simulation study for validating  
these formulas is also provided.    
            [1] Acharya S., Alonso R., Franklin M., and Zdonik S., Broadcast Disk: Data Management for Asymmetric Communication Environments, in Proceedings of the ACM SIGMOD Conference , pp. 199-210, 1995.
[2] Acharya S., Franklin M., and Zdonik S., Disseminating Updates on Broadcast Disks, in Proceedings of the Very Large Data Bases Conference , pp. 354-365, 1996.
[3] Chang Y. and Hsieh W., An Efficient Scheduling Method for Query-Set-Based Broadcasting in Mobile Environment, in Proceedings of the IEEE International Conference on Distributed Computing Systems Workshops , pp. 478-483, 2004.
[4] Chen M., Wu K., and Yu P., Optimizing Index Allocation for Sequential Data Broadcasting in Wireless Mobile Computing, IEEE Transactions on Knowledge and Data Engineering , vol. 15, no. 1, pp. 161-173, 2003.
[5] Chung Y. and Kim M., An Index Replication Scheme for Wireless Data Broadcasting, Journal of Systems and Software , vol. 51, no. 3, pp. 191-199, 2000.
[6] Chung Y. and Kim M., Effective Data Placement for Wireless Broadcast, Distributed and Parallel Databases , vol. 9, no. 2, pp. 133-150, 2001.
[7] Imielinski T., Viswanathan S., and Badrinath B., Energy Efficient Indexing on Air, in Special Interest Group on Management of Data (SIGMOD) ACM , pp. 25-36, 1994. Number of Classes Number of Transaction Per Class Order Repetition Probability of Commit (Mathematical) Probability of Commit (Simulation) 20 5 Yes 0.9031 0.8997 40 5 Yes 0.9171 0.9121 20 5 No 0.9331 0.9297 40 5 No 0.9471 0.9421 124 The International Arab Journal of Information Technology, Vol. 5, No. 4, October 2008
[8] Lam K., Chan E., and Yuen J., Approaches for Broadcasting Temporal Data in Mobile Computing Systems, The Journal of Systems and Software , vol. 51, no. 3, pp. 175-189, 2000.
[9] Lee G., Lo S., and Chen A., Data Allocation on Wireless Broadcast Channels for Efficient Query Processing, IEEE Transactions on Computers , vol. 51, no. 10, pp. 1237-12525, 2002.
[10] Lo S. and Chen A., Optimal Index and Data Allocation in Multiple Broadcast Channels, Data Engineering, 2000.
[11] Su C., Tassiulas L., and Tsotras V., Broadcast Scheduling for Information Distribution, Wireless Networks , vol. 5, no. 2, pp. 137-147, 1998.
[12] Tan K. and Yu J., Generating Broadcast Programs that Support Range Queries, IEEE Transactions on Knowledge and Data Engineering , vol. 10, no. 4, pp. 668-672, 1998.
[13] Vaidya N. and Hameed S., Scheduling Data Broadcasting in Asymmetric Communication Environments, Kluwer Academic Publishers , Dordrecht, vol. 5, no. 3, pp. 171-182, 1999.
[14] Yee W., Student Member, Navathe S., Omiecinski E., and Jermaine C., Efficient Data Allocation over Multiple Channels at Broadcast Servers, IEEE Transactions on Computers , vol. 51, no. 10, pp. 1231-1236, 2002. Ahmad Al -Qerem graduated in applied mathematics, obtaining a BSc in 1997 from JUST University and a Masters in computer science from Jordan University in 2002. After that he was appointed a full- time lecturer in the department of Computer Science at Zarqa Private University and also a part-time lecturer for the Arab Open University. He has also held a post in the Ministry of Labour. Currently, he is a PhD student at Loughborough University, UK. He is interested in concurrency control for mobile computing environments, and particularly transaction processing. He has published several papers in various areas of computer science. Walter Hussak graduated in mathematics, obtaining a BSc in 1979 and a PhD in 1983 from Sheffield University. Later he obtained an MSc in systems design from Manchester University, awarded in 1987. He joined Manchester University and worked for Professor Brian Warboys as a research associate on the Alvey Flagship Parallel System Project and later the ESPRIT II European Declarative (Parallel) System (EDS) project which was collaborative with industrial partners ICL, Bull and Siemens and was an industrial-scale system to run relational database systems and declarative (functional and logic) languages efficiently. The success of the EDS system was indicated by a subsequent commercial derivative, the ICL GOLDRUSH system. He was appointed to his first university full academic post as a lecturer in computer science at Loughborough University in 1991. He has published several papers at international conferences and in journals, on formal methods and database concurrency. He is currently a member of the networks, control and complex systems research group at Loughborough University and is interested in formal methods and mathematical aspects of database concurrency.
