Double-granularity connection admission control scheme based on compression sensing
基于压缩感知的双粒度连接准入控制策略

Data compressing techniques are often adopted in practical network systems to improve the efficiency of traffic transmission. However, compression status is ignored in most admission control schemes that usually measure the performance in term of blocking (dropping) probability. In this paper, a Double Granularity Multiple Threshold (DGMT) CAC scheme based on compression sensing was proposed. By sensing compressing levels of arrival connections, DGMT scheme controlled connection admission in granularities of both connection and original information. Multiple thresholds strategy was used in DGMT. Alternatively, Original Information Loss Ratio (OILR) and Transmission Efficiency of Original Information (TEoOI) were presented to measure CAC performances. Theoretical analysis and simulation results show that OILR and TEoOI can well indicate CAC performances, and the performance obtained by compression sensing CAC algorithm improves significantly.