Proposed Priority Scheme Research Articles

Rationing scarce healthcare capacity: A study of the ventilator allocation guidelines during the COVID-19 pandemic.

In the United States, even though national guidelines for allocating scarce healthcare resources are lacking, 26 states have specific ventilator allocation guidelines to be invoked in case of a shortage. While several states developed their guidelines in response to the recent COVID-19 pandemic, New York State developed these guidelines in 2015 as "pandemic influenza is a foreseeable threat, one that we cannot ignore." The primary objective of this study is to assess the existing procedures and priority rules in place for allocating/rationing scarce ventilator capacity and propose alternative (and improved) priority schemes. We first build machine learning models using inpatient records of COVID-19 patients admitted to New York-Presbyterian/Columbia University Irving Medical Center and an affiliated community health center to predict survival probabilities as well as ventilator length-of-use. Then, we use the resulting point estimators and their uncertainties as inputs for a multiclass priority queueing model with abandonments to assess three priority schemes: (i) SOFA-P (Sequential Organ Failure Assessment based prioritization), which most closely mimics the existing practice by prioritizing patients with sufficiently low SOFA scores; (ii) ISP (incremental survival probability), which assigns priority based on patient-level survival predictions; and (iii) ISP-LU (incremental survival probability per length-of-use), which takes into account survival predictions and resource use duration. Our findings highlight that our proposed priority scheme, ISP-LU, achieves a demonstrable improvement over the other two alternatives. Specifically, the expected number of survivals increases and death risk while waiting for ventilator use decreases. We also show that ISP-LU is a robust priority scheme whose implementation yields a Pareto-improvement over both SOFA-P and ISP in terms of maximizing saved lives after mechanical ventilation while limiting racial disparity in access to the priorityqueue.

Rationing Scarce Healthcare Capacity: A Study Of The Ventilator Allocation Guidelines During The COVID-19 Pandemic In The United States

In the United States, even though national guidelines for allocating scarce healthcare resources are lacking, 26 states have specific ventilator allocation guidelines to be invoked in case of a shortage. While several states developed their guidelines in response to the recent Covid-19 pandemic, NYS developed these guidelines in 2015 as "pandemic influenza is a foreseeable threat, one that we cannot ignore." The primary objective of this study is to assess the existing procedures and priority rules in place for allocating/rationing scarce ventilator capacity and propose alternative (and improved) priority schemes. We first build machine learning models using inpatient records of COVID-19 patients admitted to New York-Presbyterian/Columbia University Irving Medical Center and an affiliated community health center to predict survival probabilities as well as ventilator length-of-use. Then, we use the resulting point estimators and their uncertainties as inputs for a multi-class priority queueing model with abandonments to assess three priority schemes: (i) SOFA-P, which most closely mimics the existing practice by prioritizing patients with sufficiently low Sequential Organ Failure Assessment (SOFA) scores, (ii) ISP, which assigns priority based on patient-level survival predictions, and (iii) ISP-LU, which takes into account survival predictions and resource use duration. Our findings highlight that our proposed priority scheme, ISP-LU, achieves a demonstrable improvement over the other two alternatives. Specifically, the expected number of survivals increases and death risk while waiting for ventilator use decreases. We also show that ISP-LU is a robust priority scheme whose implementation yields a Pareto-improvement over both ISP and SOFA-P in terms of maximizing saved lives after mechanical ventilation while limiting racial disparity in access to the priority queue.

Quality of Service Provisioning for Heterogeneous Services in Cognitive Radio-Enabled Internet of Things

The Internet of Things (IoT) is a network of interconnected objects, in which every object in the world seeks to communicate and exchange information actively. This exponential growth of interconnected objects increases the demand for wireless spectrum. However, providing wireless channel access to every communicating object while ensuring its guaranteed quality of service (QoS) requirements is challenging and has not yet been explored, especially for IoT-enabled mission-critical applications and services. Meanwhile, Cognitive Radio-enabled Internet of Things (CR-IoT) is an emerging field that is considered the future of IoT. The combination of CR technology and IoT can better handle the increasing demands of various applications such as manufacturing, logistics, retail, environment, public safety, healthcare, food, and drugs. However, due to the limited and dynamic resource availability, CR-IoT cannot accommodate all types of users. In this paper, we first examine the availability of a licensed channel on the basis of its primary users' activities (e.g., traffic patterns). Second, we propose a priority-based secondary user (SU) call admission and channel allocation scheme, which is further based on a priority-based dynamic channel reservation scheme. The objective of our study is to reduce the blocking probability of higher-priority SU calls while maintaining a sufficient level of channel utilization. The arrival rates of SU calls of all priority classes are estimated using a Markov chain model, and further channels for each priority class are reserved based on this analysis. We compare the performance of the proposed scheme with the greedy non-priority and fair proportion schemes in terms of the SU call-blocking probability, SU call-dropping probability, channel utilization, and throughput. Numerical results show that the proposed priority scheme outperforms the greedy non-priority and fair proportion schemes.

Optimal finite state predictive direct torque control without weighting factors for motor drive applications

An optimal finite state predictive direct torque control without flux and switching frequency weighting factors (WFs) is proposed to avoid the tuning of WFs and to provide high dynamic performances with reduced switching frequency and computational burden. The proposed method is a combination of the well-known direct torque control and multi-objective ranking (MOR) priority methods. The classical MOR, used to avoid the flux WF, increases the computation time compared to the standard predictive torque control (PTC) and does not consider switching frequency issues. These drawbacks impose the need for high sampling rates, which increase the implementation cost and the inverter power losses, an important issue for medium and high-power drives. In the proposed method, the direct torque control principle is used to reduce the number of voltage vectors from eight to three, which reduces the computational burden of MOR. Also, MOR is associated with a proposed priority scheme to reduce the switching frequency and avoid WFs. Simulation and experimental results confirm that similar steady-state response as in the traditional PTC based on MOR is obtained. However, fast transient response is achieved, the computational burden is reduced by about 25%, and the switching frequency is substantially reduced compared to classical PTC.

Design of an IoT Enabled Local Network Based Home Monitoring System with a Priority Scheme

Internet of things (IoT) is a concept where all devices get connected to the internet to exchange information. IoT can be utilized in order to make a home environment interactive and smart. The required connectivity can be provided by either making all the devices Wi-Fi capable, which is costly, or by setting a local wireless sensor network (WSN) which later connects to internet. In this work various devices and sensors are designed and connected in a wireless sensor network within a home environment which generates a sensor dependent data packet. These data packets are then sent to the cloud through a master node. The master sends the data using a proposed priority scheme so that the critical information can be sent early. Simulations were performed to show that under the proposed scheme the loss of critical sensors information is reduced by around 75%.

An Intercell Interference Coordination Scheme in LTE Downlink Networks based on User Priority and Fuzzy Logic System

The Intercell Interference (ICI) problem is one of the main challenges in Long Term Evolution (LTE) downlink system. In order to deal with the ICI problem, this paper proposes a joint resource block and transmit power allocation scheme in LTE downlink networks. The proposed scheme is implemented in three phases: (1) the priority of users is calculated based on interference level, Quality of Service (QoS) and Head of Line (HoL) delay;(2) users in each cell are scheduled on the specified subbands based on their priority; and (3) eNodeBs dynamically control the transmit power using a fuzzy logic system and exchanging messages to each other. Simulation results demonstrate that the proposed priority scheme outperforms the existing Reuse Factor one (RF1) and Soft Frequency Reuse (SFR) schemes in terms of cell throughput, cell edge user throughput, delay and interference level.

High-speed low-power multiplexer-based selector for priority policy

The nature of priority policy causes inefficient throughput in synchronous clock systems because of an unbalanced propagation path. To improve speed, the proposed priority scheme improves extremely unbalanced delays between the highest and lowest weight by integrating the multiplexer-based date selector with the priority encoder. Balanced propagation paths are analyzed based on the gate-level evaluation and demonstrated by post-layout simulation. In terms of scalability, this design is suitable for extending width and has a latency of only O(logm) for m requests. The proposed design also improves the critical path by using delayed-precharge technology for dynamic logic and transmission gate at transistor level. The simulation results show that, for 8–128 requests cases, this approach achieves balanced propagation paths from fastest to lowest path. The proposed design achieves a 4.5 speedup and a 57.2% decrease in power dissipation.

Differentiation, QoS guarantee, and optimization for real-time traffic over one-hop ad hoc networks

Nodes having a self-centrically broadcasting nature of communication form a wireless ad hoc network. Many issues are involved to provide quality of service (QoS) for ad hoc networks, including routing, medium access, resource reservation, mobility management, etc. Previous work mostly focuses on QoS routing with an assumption that the medium access control (MAC) layer can support QoS very well. However, contention-based MAC protocols are adopted in most ad hoc networks since there is no centralized control. QoS support in contention-based MAC layer is a very challenging issue. Carefully designed distributed medium access techniques must be used as foundations for most ad hoc networks. In this paper, we study and enhance distributed medium access techniques for real-time transmissions in the IEEE 802.11 single-hop ad hoc wireless networks. In the IEEE 802.11 MAC, error control adopts positive acknowledgement and retransmission to improve transmission reliability in the wireless medium (WM). However, for real-time multimedia traffic with sensitive delay requirements, retransmitted frames may be too late to be useful due to the fact that the delay of competing the WM is unpredictable. In this paper, we address several MAC issues and QoS issues for delay-sensitive real-time traffic. First, a priority scheme is proposed to differentiate the delay sensitive real-time traffic from the best-effort traffic. In the proposed priority scheme, retransmission is not used for the real-time traffic, and a smaller backoff window size is adopted. Second, we propose several schemes to guarantee QoS requirements. The first scheme is to guarantee frame-dropping probability for the real-time traffic. The second scheme is to guarantee throughput and delay. The last scheme is to guarantee throughput, delay, and frame-dropping probability simultaneously. Finally, we propose adaptive window backoff schemes to optimize throughput with and without QoS constraints.

Performance analysis of dynamic channel assignment algorithms in cellular mobile systems with hand‐off

AbstractIn this paper, the traffic performance of dynamic channel assignment (DCA) in cellular mobile system with hand‐off is investigated. A traffic model for cellular system incorporating hand‐off is established first. Under the framework of the model, a hand‐off priority scheme is developed to reduce the forced termination of calls in progress. This paper analyses and derives the traffic performance bound for DCA strategies with hand‐off by extending the maximum packing (MP) scheme to include the hand‐off procedure. For practical implementation, a distributed DCA algorithm (DDCA) is also proposed. A non‐priority scheme and the proposed priority scheme can be combined with either MP or DDCA. It is shown that the simulation results of DDCA scheme are comparable with the analytical bounds given by MP for both the non‐prioritized case and prioritized case. A reasonable trade‐off between the new call blocking probability and forced termination probability can be achieved by using the proposed prioritized scheme in DCA. Copyright © 2002 John Wiley & Sons, Ltd.

A queueing model for optimal control of partial buffer sharing in ATM

This system generates some decision-making problems, among which are the following. 1. (1) What are the appropriate priority control scheme? 2. (2) What would be the optimal buffer size for each class of data to meet the quality of service (QoS)? This article addresses these decision-making problems. We derive the cell loss probabilities, mean number of cells, mean waiting time and optimal buffer sizes to control the proposed priority scheme. Some numerical examples are presented. We model the optimal control of the partial buffer sharing mechanism of ATM by a queueing system M 1, M 2/ G/ 1/ K + 1. We first derive the system equations and then develop a recursive method to compute the loss probabilities at an arbitrary time epoch. We then build an approximation scheme to compute the mean waiting time of each class of cells. An algorithm is developed for finding the optimal threshold and buffer capacity for a given QoS.

Performance evaluation of triggered threshold buffer schemes for ATM networks

To achieve the quality of service for each class of traffic in ATM networks, we propose and analyze two triggered threshold buffer schemes to improve the cell loss rate in ATM networks. In the proposed schemes, there are two thresholds to control the behavior of cell discarding in the ATM switch. When the system is in the heavy traffic situation, we use one threshold to reduce the cell loss rate of the high priority class, and when the system is in the light traffic situation, we use another threshold to improve the cell loss rate of the low priority class. Performance of both the triggered threshold buffer schemes is analyzed and compared. According to the analyzed results, the performance of the proposed priority schemes can be better than that of the partial buffer sharing scheme. Besides, the buffer management complexity in the proposed priority scheme is simpler than that of the push-out scheme.