We present our design and deployment experiences with LiveSky, a commercially deployed hybrid CDN-P2P live streaming system. CDNs and P2P systems are the common techniques used for live streaming, each having its own set of advantages and disadvantages. LiveSky inherits the best of both worlds: the quality control and reliability of a CDN and the inherent scalability of a P2P system. We address several key challenges in the system design and implementation including (a) dynamic resource scaling while guaranteeing stream quality, (b) providing low startup latency, (c) ease of integration with existing CDN infrastructure, and (d) ensuring network-friendliness and upload fairness in the P2P operation. LiveSky has been commercially deployed and used for several large-scale live streaming events serving more than ten million users in China. We evaluate the performance of LiveSky using data from these real-world deployments. Our results indicate that such a hybrid CDN-P2P system provides quality and user performance comparable to a CDN and effectively scales the system capacity when the user volume exceeds the CDN capacity.
In this paper, we propose a greedy user selection with swap (GUSS) algorithm based on zero-forcing beamforming for multiuser multiple-input-multiple-output (MIMO) downlink channels. Existing user selection algorithms such as zero forcing with selection (ZFS) have the flaws of "redundant users" and "local optimum," which compromise the achieved sum rate. GUSS improves the performance by adding the "delete" and "swap" operations to the user selection procedure of ZFS to eliminate "redundant users" and escape from "local optimum," respectively. In addition, an effective-channel-vector-based effective-channelgain-updating scheme is proposed to reduce the complexity of GUSS. With the help of this updating scheme, GUSS has the same order of complexity as ZFS with only a linear increment. Simulation results indicate that over the range of transmit signal-tonoise ratios (SNRs) considered, on average, the sum rate of GUSS reaches 99.3% of the upper bound that is achieved by exhaustive search, with only 1.51 to 2.29 times the complexity of ZFS.Index Terms-Broadcast channel, multiuser multiple-inputmultiple-output (MIMO), user selection, zero-forcing beamforming (ZFBF).
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