Dynamic Resource Allocation for Classes of Prioritized Session and Data Requests in Preemptive Heterogeneous Networks

This research focuses on the intelligent allocation of bandwidth to requests in oversubscribed preemptive networks such that some measure of collective worth associated with the satisfied requests is optimized. A class and priority based mechanism is described for grouping requests such that all requests belonging to a higher class are processed before any request(s) of a lower class are considered. Within each class, requests are further assigned different priority levels depending on their relative worths. An on-line batch scheduling heuristic is designed to determine the bandwidth allocations to the requests depending on their class, relative worths of their priority levels, and the network capacities available for that period. This heuristic considers requests of two types: (1) data type – requesting a data item of given size with an earliest available time and fixed deadline and (2) session type – requesting a fixed amount of bandwidth for a given interval of time. Simulation experiments demonstrate that the heuristic performs well compared to a complete sharing policy and to upper bounds.