Scheduling Management for Multiple Real-Time Data over On-Demand Mobile Environments

Many time-constraint applications operate on continuous queries and need real-time data services in on-demand mobile environments. Providing deadline guarantees for queries over dynamic multiple data is a challenging problem due to continuous query rates and time-varying contents. The accurately approximated optimum distributions is used to obtain analytical expressions for performance metrics such as average real-time miss rate and outage probability. The normal probability distribution function of client request to channel hopping is approximated. In the analysis multiple channel model based on currently transmitting is considered over independent and not identically distributed wireless channels. In addition the performance of currently transmitting is compared with the QoS-based management scheme for real-time query processing. The numerical results are validated by linear programming simulations. It is shown that for broadcasting real-time data placement, this contribution is very useful and efficient for exact performance analysis and design of wireless multi-channel links.