Algorithms for advance bandwidth reservation in media production networks

Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results

Internet scheduling environment with market-driven agents

This paper describes a new generation scheduling paradigm, the Internet scheduling environment. It is formed by a group of Internet scheduling agents which share computational resources to solve scheduling problems in a distributed and collaborative manner. We propose a migration scheme to transform existing standalone scheduling systems to Internet scheduling agents that can communicate with each other and solve problems beyond individual capabilities. To coordinate computational resource collaboration among agents, we introduce the market-based control mechanism is which self-interested agents initiate or participate in auctions to sell or buy scheduling problems. Efficient allocation of computational resources is achieved through the auctions. This paper also describes a prototype Internet scheduling environment named LekiNET, which is migrated from LEKIN®, a flexible job shop scheduling system. The experiments on the LekiNET testbed demonstrate that the agent-based market-driven Internet scheduling environment is feasible and advantageous to future scheduling research and development.published_or_final_versio