IEEE Project Abstract

The introduction of cache can reduce unnecessary traffic load and improve latency in the wireless access networks,especially for wireless video broadcasting. But how cache impacts video broadcasting with scalable video coding (SVC) is still an openproblem. In this paper, we analyze the optimization of random caching in a large-scale cache-enabled IoT networks. Specifically wepropose to optimize the random caching strategy which aims to maximize the successful transmission probability (STP) of the videocontents at edge base stations (BSs). To this end, by using the stochastic geometry theory, we derive analytical expression of STP byconsidering scalable video coding (SVC) to satisfy different levels of quality of service (QoS) requirements. We develop a gradientbased iterative algorithm to search the local optimal solution for the general random caching strategy optimization problem. Theasymptotical optimal caching strategy is obtained with a lower complexity. The closed-form STP is also obtained in high signal-to-noiseratio (SNR) and particular cache size. Based on the closed-form STP expressions, the random caching strategy, i.e., caching probabilityof different video contents, is further optimized to enhance STP performance. Compare to different reference schemes, the proposedcaching strategy improves the STP up to 18% and 21:6% with the low density of BSs and the high density of BSs, respectively