Models for video-on-demand scheduling with costs

Video-on-demand, which provides digital content as needed, supplies flexibility for the users but presents reactive challenges for the provider, as the peaks and troughs in demand lead to an inconsistent requirement of resources. The cost of keeping servers primed for demand that may not appear must be balanced against the cost of frustrating users who must wait for service. This VoD problem is a bi-objective optimization problem, minimizing cost to the provider and delay for the user. Mindful of real-world applications, we introduce a model that handles tasks of differing size ( bandwidth) or value by assigning weights to these tasks, and combining the weight with the duration. In this way, we can account for differentiated tasks, in particular, premium users and variable sized tasks. We also extend our approach to account for multiple tasks on each machine.