Efficient Multi-Resource Scheduling Algorithm for Hybrid Cloud-Based Large-Scale Media Streaming.

With the increase in the amount of dynamic and personalized content in media streaming systems, a solution that is based on only the cloud or content delivery network (CDN) cannot satisfy all application-specific requirements. Thus integrating the cloud with CDNs and private data centers can be advantageous. To efficiently deliver a huge amount of media content using a geographically distributed hybrid cloud, we propose a Multi-Resource Scheduling Algorithm for Hybrid Cloud-Based Large-Scale Media Streaming(MHLMS). The algorithm transforms resource scheduling into a Nash bargaining problem and solves it efficiently from a geometrical perspective. The simulation results show that compared to algorithms that use only the cloud or CDN, MHLMS can reduce the cost by approximately 60% and reduce the average delivery distance by up to 70%. Thus, compared with the existing video delivery methods, MHLMS can handle millions of channels effectively with much lower time complexity. (C) 2019 Elsevier Ltd. All rights reserved.