To analysis of a two-buffer queuing system with cross-type service and additional penalties

The concept of cloud computing was created to better preserve user privacy and data storage security. However, the resources allocated for processing this data must be optimally allocated. The problem of optimal resource management in the loud computing environment is described in many scientific publications. To solve the problems of optimality of the distribution of resources of systems, you can use the construction and analysis of QS. We conduct an analysis of two-buffer queuing system with cross-type service and additional penalties, based on the literature reviewed in the article. This allows us to assess how suitable the model presented in the article is for application to cloud computing. For a given system different options for selecting applications from queues are possible, queue numbers, therefore, the intensities of transitions between the states of the system will change. For this, the system has a choice policy that allows the system to decide how to behave depending on its state. There are four components of such selection management models, which is a stationary policy for selecting a queue number to service a ticket on a vacated virtual machine each time immediately before service ends. A simulation model was built for numerical analysis. The results obtained indicate that requests are practically not delayed in the queue of the presented QS, and therefore the policy for a given model can be considered optimal. Although Poisson flow is the simplest for simulation, it is quite acceptable for performance evaluation. In the future, it is planned to conduct several more experiments for different values of the intensity of requests and various types of incoming flows.

Optimal resource management and allocation for autonomous-vehicle-infrastructure cooperation under mobile edge computing

Purpose With the continuous technological development of automated driving and expansion of its application scope, the types of on-board equipment continue to be enriched and the computing capabilities of on-board equipment continue to increase and corresponding applications become more diverse. As the applications need to run on on-board equipment, the requirements for the computing capabilities of on-board equipment become higher. Mobile edge computing is one of the effective methods to solve practical application problems in automated driving. Design/methodology/approach In this study, in accordance with practical requirements, this paper proposed an optimal resource management allocation method of autonomous-vehicle-infrastructure cooperation in a mobile edge computing environment and conducted an experiment in practical application. Findings The design of the road-side unit module and its corresponding real-time operating system task coordination in edge computing are proposed in the study, as well as the method for edge computing load integration and heterogeneous computing. Then, the real-time scheduling of highly concurrent computation tasks, adaptive computation task migration method and edge server collaborative resource allocation method is proposed. Test results indicate that the method proposed in this study can greatly reduce the task computing delay, and the power consumption generally increases with the increase of task size and task complexity. Originality/value The results showed that the proposed method can achieve lower power consumption and lower computational overhead while ensuring the quality of service for users, indicating a great application prospect of the method.

SOLVING PROBLEM OF MULTICRITERIA CHOICE FOR RECONSTRUCTING DIESEL FUEL HYDROFINING PLANTS

The article describes a diesel fraction hydrofining plant as a rather complex object of management where an important criterion is the optimal resource management of the processes of technological units. This implies maintaining the optimal mode for regulation of the main parameters of the plants, which determine the output product quality. Under inadequate temperature and pressure values, as well as other insufficient operating parameters, the sulfur content in the raw material increases and the cost of the output product decreases. There are several types of hydrofining plants on the Russian market, each of them shows high operating efficiency under different modes. An iterative-fragmentary approach for developing a model of multifactor preferences for selecting the efficient hydrofining plants with optimal modes has been proposed. The results of hydrofining plants processing the different concentrations of sulfur in the raw material and different amounts of the raw material per year were taken as the initial data. Testing of the plants chosen for the study was carried out under different power loads for the raw materials, volumetric feed rates, tempera-ture and hydrogen-containing gas circulation. The optimal choice of the hydrofining plant model and its operating parameters guarantees the high quality of diesel fuel.

Clinical and Virological Characteristics of Hospitalized COVID-19 Patients in a German Tertiary Care Center during the First Wave of the SARS-CoV-2 Pandemic

BackgroundAdequate patient allocation is pivotal for optimal resource management in strained healthcare systems, and requires detailed knowledge of clinical and virological disease trajectories.MethodsA cohort of 168 hospitalized adult COVID-19 patients enrolled in a prospective observational study at a large European tertiary care center was analyzed.ResultsForty-four percent (71/161) of patients required invasive mechanical ventilation (IMV). Shorter duration of symptoms before admission (aOR 1.22 per day less, 95%CI 1.10-1.37, p<0.01), age 60-69 as compared to 18-59 years (aOR 4.33, 95%CI 1.07-20.10, p=0.04), and history of hypertension (aOR 5.55, 95%CI 2.00-16.82, p<0.01) were associated with need for IMV. Patients on IMV had higher maximal concentrations, slower decline rates, and longer shedding of SARS-CoV-2 than non-IMV patients (33 days, IQR 26-46.75, vs 18 days, IQR 16-46.75, respectively, p<0.01). Median duration of hospitalization was 9 days (IQR 6-15.5) for non-IMV and 49.5 days (IQR 36.8-82.5) for IMV-patients.ConclusionOur results indicate a short duration of symptoms before admission as a risk factor for severe disease and different viral load kinetics in severely affected patients.

Variables Reduction in Sequential Resource Allocation Problems

This paper presents a general framework to address diverse notoriously difficult problems arising in the area of optimal resource management, exploitation of natural reserves, pension fund valuation, environmental protection, and storage operation. Using some common abstract features of this problem class, we present a technique which provides a significant reduction of decision variables. As an application, we discuss a battery storage control to show how a decision problem, which is practically unsolvable in the original formulation, can be treated by our method.