A data partition based near optimal scheduling algorithm for wireless multi-channel data broadcast

Data broadcast is an efficient way to disseminate information to large numbers of users in wireless environments. The Square Root Rule (SRR) is the theoretical basis for the single channel broadcast Scheduling. In this paper, we extend the SRR and propose the Multi-channel Square Root Rule (MSRR) for scheduling variable-length data with skewed access probabilities on variable-bandwidth channels. The theoretical optimal average access latency is also provided. However, this optimal value can not be achieved in reality. Based on MSRR, we provide a two-phase scheduling algorithm which achieves near optimal access latency. First data are partitioned and allocated to different channels according to MSRR. Second, different scheduling strategies are adopted on each channel according to the skewness of data subset allocated on that channel. Experiments show that the difference of average access latency between our results and the optimal value is below five percent in most situations.