Extending the effective bandwidth concept to networks with priority classes

In March of 2020, elective surgical procedures in New York State were suspended in response to the COVID-19 pandemic. At Northwell Health, this lasted a total of 8 weeks, leaving plastic surgeons responsible for recording and rescheduling delayed procedures. Many plastic and reconstructive procedures are considered elective, but these procedures can be time sensitive, and delays can have a negative impact on patient care.1 Our goal was to compare the rates of completion and time to completion between different priority groups and procedure types in order to predict potential consequences for one's practice if future suspensions in elective surgery were to occur. We hypothesized that procedures grouped in the reconstructive categories with higher priority levels would have a higher completion rate and lower time to completion compared to less urgent, aesthetic based procedures. Plastic surgeons working for our department were responsible for keeping track of their suspended cases between March 23, 2020, and May 19, 2020.2,3 Under the discretion of the attending plastic surgeon, cases were categorized into procedure type, priority level, and surgery setting. The procedure types included aesthetic, pediatrics/craniofacial, hand, general, and reconstructive. The priority classes were elective, nonurgent, semiurgent, urgent, and emergent. The surgery setting was classified into inpatient and outpatient. In total, we examined 135 surgical cases that were suspended (Table 1). The average patient age was 45.8 years, and 45.9 percent of the surgical procedures were completed by the end of August of 2020, more than 3 months after the suspension was lifted. Of those that were completed, the average time to completion from the original surgical date was 79.2 days. Surgery classifications are summarized in Table 1. We ran binary logistic regressions that showed no significant correlation between the surgery type, urgency, or priority class and whether or not the surgery was completed. In addition, linear regression analyses did not show a significant correlation between the surgery type, urgency, or priority class and the time it took to complete the surgery. All the models controlled for patient age and whether or not there was malignancy. Table 1. - Summary of Sample by Procedure Priority Procedure Classification No. of Patients Percent of Sample Priority Elective 8 5.93% Nonurgent 80 52.29% Semiurgent 22 16.30% Urgent 24 17.78% Emergent 1 0.01% Type Aesthetic 12 8.89% Pediatrics/craniofacial 10 7.41% Hand 9 6.67% General 35 25.93% Reconstructive 68 50.37% No type specified 1 0.74% Location Inpatient 34 25.19% Outpatient 66 48.89% No location specified 35 25.93% Our surprising results may be due to several factors, including differences in patients' concerns with undergoing surgery during a pandemic, patients' continuous desire to undergo aesthetic surgery, or a lack of prioritization of urgent cases when rescheduling surgery. With new variants of SARS-CoV-2 emerging and the number of COVID-19 cases climbing rapidly in the United States,5 plastic surgeons must be prepared for another potential suspension of surgery.6 Plastic surgery departments and private practices can use our experience to guide their recovery from future surgical suspension. Prior studies have already shown the tremendous economic impact of surgery delays on plastic surgeons.4Additional research is needed, however, to evaluate the impact of delays on patient care and quality of life. A more systematic approach to rescheduling surgery, which prioritizes the most vulnerable patients, is needed. DISCLOSURE The authors have no relevant financial disclosures to report.

In computer networks, the Strict Priority (SP) discipline is perhaps the most common and simplest method to schedule packets from different classes of applications, each with diverse performance requirements. With this discipline, however, packets at higher priority levels can starve packets at lower priority levels. To resolve this starvation problem, we propose to assign a parameter to each priority queue in the SP discipline. The assigned parameter determines the probability or extent by which its corresponding queue is served when the queue is polled by the server. We thus form a new packet service discipline, referred to as the Probabilistic Priority (PP) discipline. By properly adjusting the assigned parameters, not only is the performance of higher priority classes satisfied, but also the performance of lower priority classes can be improved. This paper analyzes the delay performance of the PP discipline. A decomposition approach is proposed for calculating the average waiting times and their bounds are studied. Two approximation approaches are proposed to estimate the waiting times. Simulation results that validate the numerical analysis are presented and examined. A numerical example which demonstrates the use of the PP discipline to achieve service differentiation is presented. This example also shows how the assigned parameters can be determined from the results of analysis mentioned above.

A simulation study of the performances of MiniMAP networks is presented. The two network models used in the simulation take into account the effect of the maximum number of outstanding requests set for each manufacturing message specification (MMS) application association. Three different situations are considered. In the first, all the messages are generated at the same priority level, whereas in the other two, four priority classes that are directly mapped onto channel priorities are introduced. However, the second situation considers the use of priorities only on the client side of MMS, whereas the third uses priorities on both sides.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

There seems to be evidence of gender and ethnic bias in the early management of acute coronary syndrome. However, whether these differences are related to less severe severity assessment or to less intensive management despite the same severity assessment has not yet been established. To show whether viewing an image with characters of different gender appearance or ethnic background changes the prioritization decision in the emergency triage area. The responders were offered a standardized clinical case in an emergency triage area. The associated image was randomized among eight standardized images of people presenting with chest pain and differing in gender and ethnic appearance (White, Black, North African and southeast Asian appearance). Each person was asked to respond to a single clinical case, in which the priority level [from 1 (requiring immediate treatment) to 5 (able to wait up to 2 h)] was assessed visually. Priority classes 1 and 2 for vital emergencies and classes 3-5 for nonvital emergencies were grouped together for analysis. Among the 1563 respondents [mean age, 36 ± 10 years; 867 (55%) women], 777 (50%) were emergency physicians, 180 (11%) emergency medicine residents and 606 (39%) nurses. The priority levels for all responses were 1-5 : 180 (11%), 686 (44%), 539 (34%), 131 (9%) and 27 (2%). There was a higher reported priority in male compared to female [62% vs. 49%, difference 13% (95% confidence interval; CI 8-18%)]. Compared to White people, there was a lower reported priority for Black simulated patients [47% vs. 58%, difference -11% (95% CI -18% to -4%)] but not people of southeast Asian [55% vs. 58%, difference -3% (95% CI -10-5%)] and North African [61% vs. 58%, difference 3% (95% CI -4-10%)] appearance. In this study, the visualization of simulated patients with different characteristics modified the prioritization decision. Compared to White patients, Black patients were less likely to receive emergency treatment. The same was true for women compared with men.

Patient Demand Management through Prioritized Access with Time Windows Access Protocol

Watershed prioritization is a strategic procedure used to delineate the most erosion-prone sub-watersheds. Identifying these critical areas is paramount for the effective allocation of resources and the successful implementation of soil and water conservation measures at the watershed level. However, studies concerning the mountainous watershed of Kiile are limited. In this study, the prioritization of 10 sub-watersheds of the Kiile River was done to identify erosion-prone areas using quantitative morphometric analysis. The watershed and its drainage networks were delineated using ALOS PALSAR 12.5 m resolution DEM in ArcGIS 10.4. For prioritisation, morphometric parameters such as linear, areal, and relief aspects were considered and calculated using standard formulae provided by various hydrologists and geomorphologists. Each morphometric parameter was preliminarily ranked based on its relation with soil erodibility. The final prioritization was done based on the compound value (Cp). The analysis result revealed that SW-8 and SW-5 are the most erosion-prone sub-watersheds with the lowest compound value, indicating greater susceptibility to erosion. Based on the results, the sub-watersheds of the Kiile River were categorised into four priority classes: very high, high, medium, and low. The SW-8 and SW-5 fall under the very high priority class, SW-3, SW-4, SW-6, and SW-9 fall under the high priority class, SW-1, SW-7, and SW-2 fall under the medium priority class, and SW-10 falls under the low priority class. This study significantly contributes to the management of mountainous watersheds and may be useful for decision-makers in sustainably managing and conserving the watershed resources.

We investigated the photonic packet switch architecture that enables a high node throughput and provides priority services. Previously, we proposed PBSO (partial buffer sharing with overwriting) method that enables prioritized buffer management to control an optical buffer. The PBSO method is based on a single queue and its complexity is O(p), where p is the number of priority classes. PBSO can be used to provide different levels of drop precedence in DiffServ (Differentiated Services) Assured Forwarding. In this paper, we propose an analytical method of PBSO where p=2. We assess the accuracy of the analytic method. We show that PBSO improves the packet loss probability in each priority class more than the existing PBS (partial buffer sharing) does, and that it can be used for prioritized buffer management of an optical buffer. PBSO is especially effective when the arrival rate of higher priority class packets is much lower than that of lower priority class packets. In this case, PBSO dramatically improves the performance of higher priority class packets while the degradation in the performance of lower priority class packets is small. In PBSO, a larger number of higher priority class packets can be accepted at a given packet loss probability than in PBS or non-priority method.

This paper presents a greedy randomized adaptive search procedure (GRASP) for scheduling n jobs on m nonhomogeneous parallel machines with time windows. An additional feature of the problem is that each job falls into one of ρ priority classes. The objective is to maximize the number of jobs scheduled, where a job in a higher priority class has infinitely more value than a job in a lower priority class. The GRASP consists of two phases. The first phase produces feasible solutions by ranking each job with a greedy function and then selecting one at random from a restricted candidate list. The process is repeated until no more jobs can be scheduled. The second phase seeks a local optimum by searching over a series of neighborhoods defined by job insertions and exchanges. The algorithm is compared to a dynamic-programming heuristic that sequentially schedules the jobs in each priority class. Extensive computational results are presented based on data drawn from an application involving the use of communications relay satellites.

Cell loss probability is a critical performance criterion that will be encountered in satisfying the needs of ATM services. To enforce dynamic control on the finite buffer in an ATM switch, it is desirable that multiple loss priority classes can be supported to accommodate diverse connection-levels as well as cell-level loss requirements of users. However, very little work has appeared in literature in the study of controlling cell loss probabilities with multiple priority classes. In this paper we conduct a thorough analysis of a generalized space priority control scheme, the Partial Buffer Sharing scheme, to manage optimally the finite shared buffer system. We develop an analytical queuing model to characterize accurately the system, and present efficient optimization procedures that are capable of finding the optimal loss thresholds to maximize the system admissible load. We verify the optimization procedures, demonstrate the resource efficiency improvement and evaluate the impact of given traffic conditions and cell loss criteria by numerous numerical examples. The study produces a feasible and attractive means to support different grades of loss probabilities with a minimum hardware cost and also to provide a better control on the delay introduced during cell buffering.

This paper presents a new bandwidth management framework supporting Differentiated Services aware Traffic Engineering (DSTE) in the Multi-Protocol Label Switching (MPLS). Our bandwidth management framework contains route computation, bandwidth allocation and preemption for Label Switched Paths (LSPs). We put forward two algorithms. The first one, named bandwidth preemption algorithm, dedicated for the Maximum Allocation Model and in which preemption is conducted in two dimensions: Class Type and priority levels within a same CT. Furthermore, we design a second algorithm named LSP preemption algorithm to select the most appropriate LSPs to be cast out. Selection decision is made on the basis of several citeria: the precedence level, the number of LSPs to preempt and the excess of bandwidth to gain. Extensive simulation study is carried out to evaluate the performance of our approach. Compared with existing ones, our algorithm improves not only bandwidth efficiency but also robustness and fairness. It achieves significant performance improvement for the well-behaving traffic classes in term of bandwidth link utilization, bandwidth blocking,and LSPs preemption.

This study examines the refugee reallocation problem by modeling it as a two-sided matching problem between countries and refugees. Based on forced hierarchical priority classes, I study two interesting refugee matching algorithms to match refugees with countries. Axioms for fairness measures in resource allocation are presented by considering the stability and fairness properties of the matching algorithms. Two profiles are explicitly modeled---country preferences and forced prioritization of refugee families by host countries. This approach shows that the difference between the profiles creates blocking pairs of countries and refugee families owing to the forced hierarchical priority classes. Since the forced priorities for countries can cause certain refugees to linger in a lower priority class in every country, this study highlights the importance of considering refugees' preferences. It also suggests that a hierarchical priority class-based approach without category-specific quotas can increase countries' willingness to solve the refugee reallocation problem.

This paper presents an approximate analysis of delay performance of a WD/SD optical packet/burst switch equipped with infinite optical buffers. By using M/G/1 model, we give the theoretical expression of delay performance of the switch fabric with/without assignment of priority class to service under fixed/variable packet length. Meanwhile, the results of numerical analysis are presented, too. According to these analyses, we give the following main conclusions: in the switch fabric with variable packet/burst length and no assignment of priority class to service, the mean packet/burst delay appears much smaller than that with fixed packet length; and in the switch fabric with assignment of three priority classes to service, the delay of two kinds of services with lower priority classes appears to bigger than that of service with no assignment of priority class.

Software rejuvenation is modeled in a client–server system, which provides resources to priority classes of users. To assure availability, resource reservation policies are adopted for the higher priority classes. In addition software rejuvenation is proposed to optimize resource availability. The system is modeled by a cyclic nonhomogeneous Markov chain to capture the variation of the arrival and service rates during a day period. An optimization problem is solved based on a similar previous work and given the optimal resource reservation policy obtained by its solution, rejuvenation is performed and the optimal rejuvenation policy is determined. As a measure of resource availability the blocking probability of each priority class is used. Performability indicators expressing the total cost are also derived, with respect to the optimal resource reservation and optimal rejuvenation policies, to examine whether rejuvenation benefits the system in terms of cost. To derive the blocking probabilities, the limiting probability distribution is computed using explicit generalized approximate inverse preconditioning for solving efficiently sparse linear systems of algebraic equations. Copyright © 2012 John Wiley &amp; Sons, Ltd.

CV Baja Mandiri Teknik is a Commanditaire Vennootschap (CV) engaged in the manufacturing sector, specializing in the production of cutting machine hinge shafts. The company faces a problem where the production output of cutting machine hinge shafts in several predetermined periods does not meet the production target.To address this issue, a production capacity planning approach using the Rough Cut Capacity Planning (RCCP) method has been implemented. Based on the aggregate planning, the Master Production Schedule (MPS) for cutting machine hinge shafts in 2024 has been generated. The production output per period is as followsPeriod 1: 26 pcs, Period 2: 23 pcs, Period 3: 24 pcs, Period 4: 19 pcs, Period 5: 24 pcs, Period 6: 23 pcs, Period 7: 26 pcs, Period 8: 26 pcs, Period 9: 25 pcs, Period 10: 27 pcs, Period 11: 26 pcs, and Period 12: 25 pcs. According to the Rough Cut Capacity Planning (RCCP) results, the required capacity does not exceed the available capacity, eliminating the need for overtime. However, to achieve the Master Production Schedule (MPS), an additional worker is required, increasing the workforce from 4 to 5 employees.

We consider an inventory system under continuous review with two demand classes that are different in terms of service level required (or penalty cost incurred for backordering of demand). Prior literature has proposed the critical level rationing (CLR) policy under which the demand from the lower priority class is backordered once inventory falls below the critical level. While this reduces the penalty cost for the higher demand class, the fill rate achieved for the lower priority demand class gets compromised. In this study, we propose a new class of two‐bin (2B) policy for the problem. The proposed 2B policy assigns separate bins of inventory for the two demand classes. The demand for each class is fulfilled from its assigned bin. However, when the bin intended for the higher demand class is empty, the demand from the higher class can still be fulfilled with the inventory from the other bin. The advantage of the 2B policy is that better fill rates are achieved, especially for the lower demand class. Computational results show that the proposed policy is able to provide a much higher service level for the lower priority class demand without increasing the total cost too much and without affecting the service level for the higher priority class. When a service level constrained optimization problem is considered, the 2B policy dominates the CLR policy when the service level difference for the two classes is not too high or the service levels required for both the classes are relatively lower.