An information-theoretic model for resource-constrained systems

In this paper, we study the performance of resource-constrained systems from the perspective of information theory. Such a system consists of many components which may contribute to the performance, but resource can only be allocated to some of them. We desire to allocate the limited resources effectively so as to maximize the system performance. Usually, we have incomplete information about the system or the system has inherent randomness. Even with the optimal allocation strategy according to the available (uncertain) information, we may not achieve the best system performance. We propose a model for the generic resource-constrained system and mathematically formulate the relationship between system uncertainty, characterized by entropy, and performance. Based on this result, we can determine how the system uncertainty quantitatively influences the performance. Examples of applications of the model to data storage and peer-to-peer file sharing are also given.