Local Search Heuristics for Media Streams Planning with Transcoding

Recent advances in processing capabilities of commodity hardware enabled deployment of high-performance collaborative environments in various application fields, where maximum image quality and interactivity are critical. In this paper, we focus on user-empowered collaborative environments that rely on information available to the users and that can be obtained from the end-nodes connected to the network. We build upon our previous work on scheduling strategies for multi-point data distribution, while utilizing media transcoding during the distribution and partial network topology knowledge that may be provided by the users. The novelty introduced by this paper focuses on improving scheduling scalability by employing local search metaheuristics, allowing us to maintain systems comprising more than twice as many applications compared to the previous approaches.