In a M/M/N +M queue, when there are many customers waiting, it may be preferable to reject a new arrival rather than risk that arrival later abandoning without receiving service. On the other hand, rejecting new arrivals increases the percentage of time servers are idle, which also may not be desirable. We address these trade-offs by considering an admission control problem for a M/M/N +M queue...

We propose the use of Bayesian networks, which provide both a mean value and an uncertainty estimate as output, to enhance the safety of learned control policies under circumstances in which a test-time input differs significantly from the training set. Our algorithm combines reinforcement learning and end-to-end imitation learning to simultaneously learn a control policy as well as a threshold...

11 In a traditional key assignment scheme, an access control policy is used to solve the access control problem in a hierarchy. A higher security class can access lower security classes, but the opposite is not allowed. However, in some cases, this can be troublesome because of the lack of flexibility. In this paper, we shall propose a secure key assignment scheme which can be performed not onl...

In this paper, we present an adaptive multi-agent reinforcement learning method for solving congestion control problems on high-speed networks. Traditional reactive congestion control regulates source rate in terms of queue length restricted to a predefined threshold. However, the determination of the congested threshold and sending rate is difficult and inaccurate due to the dynamic nature of ...

Languages for the specification of access-control policies should support language features that allow for policies to be written in a clear manner. This work presents a set of language features found in current access-control languages and formalizes a set of intuitive properties the author believes to be relevant to policy clarity. The author analyzes access-control languages with respect to ...

This paper describes the design and implementation of a dynamic threshold policy (to be used to classify local node availability, for load-balancing purpose). The experiments were built upon the Extended Gradient algorithm, running over Linux/X86 computing nodes. Results validating the usefulness of the dynamic threshold policy are presented.

The paper describes a Markov Decision Process (MDP) framework for coordinated sensing and adaptive communication in embedded sensor networks. The technique enables distributed sensor nodes to adapt their sampling rates in response to changing event criticality and the availability of resources (energy) at each node. The relationship between energy consumption, sampling rates, and utility of coo...

BACKGROUND Recent studies show that transfusing older blood may lead to increased mortality. This raises the issue of whether transfusing fresher blood can be achieved without jeopardizing blood availability. STUDY DESIGN AND METHODS We propose a simple family of policies that is defined by a single threshold: rather than transfusing the oldest available blood that is younger than 42 days, we...