Value-density algorithms to handle transient overloads in scheduling

Systems with timing constraints have become pervasive in several disciplines, such as real-time artificial intelligence, operating systems, operations research, and local area networks. Most of the work in real-time system scheduling deals with admission control algorithms to guarantee that accepted tasks will meet their deadlines. In this paper, we compare the different algorithms, and suggest a novel algorithm that subsumes the previous ones with respect to schedulability in the case where the system may suffer from transient overloads and where tasks have precedence constraints among them. We show how our algorithm works in allocating time to competing reasoning modules in dynamic environments