Adaptive Utility Based Scheduling

Abstract

This work proposes a new general-purpose framework for adaptive scheduling of entities that interact in an environment. The framework developed was employed for scheduling packets in a packet switching network (PSN) and focuses on determining the order in which packets should be forwarded from a queue based on the everchanging state of the network. A scheduling system has to constantly adapt to various network states (the changing network parameters) in order to achieve maximum policy compliance. The framework presented in this paper attempts to maximize policy compliance while minimizing overhead, implementation difficulty, and computational complexity. The utility assessment of forwarding a packet in a network and the quantification of its impact, on the overall policy compliance of the network is very difficult to achieve. The problem of relevant utility assignment with minimal computational complexity is achieved using a well-known utility assignment technique in operational research, Multi Attribute Utility Theory (MAUT). Adaptability to various network states is achieved by a state aware neural network, which helps in relevant utility assignment for a given state of the network