On-demand data broadcast scheduling based on AHP and GRA methods in wireless broadcast/UMTS integrated systems

Abstract

The increasing demand for interactive mobile multimedia service is causing the integration of 3rd generation (3G) cellular systems and wireless broadcast systems. The key challenge is to support data dissemination with low response time, request drop rate, and the unfairness of request drop. This article proposes a novel scheduling algorithm called DAG (on-demand scheduling utilizing analytic hierarchy process (AHP) and grey relational analysis (GRA)), which takes multiple factors—waiting time, number of active requests, deadline—into consideration, and models the data scheduling process as a multiple factors' decision-making and best option-selecting process. The proposed approach comprises two parts. The first part applies AHP to decide the relative weights of multiple decision factors according to user requests, while the second adopts GRA to rank the data item alternatives through the similarity between each option and the ideal option. Simulation results are presented to demonstrate that DAG performs well in the multiple criterions mentioned above.