Capacity Planning and Production Scheduling for Aircraft Painting Operations

Long-term capacity planning and production scheduling present significant challenges for the aviation industry. Our research has integrated three different modeling methodologies to effectively forecast future demand for aircraft painting and then assess and manage the capacity that is needed to meet these requirements. First, an innovative forecasting approach was developed in which stochastic processes were used to model aircraft demand over a selected time interval. These demand forecasts were used as inputs to an integer programming model, which was used to find optimal monthly aircraft painting schedules. This approach supports for resource allocation that is based on optimal scheduling, rather than the existing heuristic-based methods. The optimal monthly schedules can then serve as inputs to a discrete event simulation model of the painting operation, which can be used to test the robustness of the optimal schedules under conditions of uncertain demand and processing times

Планирование загрузки ресурсов центра обработки данных на основе статистических данных

Якість обслуговування клієнтів залежить від процедури підтримки прикладних програм в центрі обробки даних постачальника зв'язку. У статті розглядається підхід контролю динамічного використання ресурсів для забезпечення обслуговування вхідного потоку, який враховує випадковий характер надходження заявок і використовує короткострокові і довгострокові статистичні навантаження. Запропонований підхід складається з двох методів, які керують кількістю обслуговуючих вузлів. Результати моделювання управління технічними ресурсами були представлені для інфраструктури ЦОД провайдера зв'язку, що доводить ефективність запропонованих методів.The customer service quality depends on the procedure of the application maintenance in data center of the communication provider. In the article the control approach of dynamic resource involvement has been suggested in order to ensure the input flow maintenance that takes into account the random nature of applications’ inflow and utilizes both short-term and long-term load statistics. The proposed approach consists of two methods that manage the number of the implicated serving nodes. The first one verifies the resource amount adequacy, provides the evaluation of input load’s dynamics based on the short-term statistics as well as the current state of the technical facilities. The second one accounts for the long-term statistics according to which the implication of additional resources can be scheduled during the load peaks. The simulation results of technical resources management have been presented for the data center infrastructure of the communication provider, that prove the effectiveness of the proposed methods.Качество обслуживания клиентов зависит от процедуры поддержки приложений в центре обработки данных поставщика связи. В статье рассматривается подход контроля динамического использования ресурсов для обеспечения обслуживания входящего потока, который принимает во внимание случайный характер поступления заявок и использует краткосрочные и долгосрочные статистические нагрузки. Предложенный подход состоит из двух методов, которые управляют количеством обслуживающих узлов. Результаты моделирования управления техническими ресурсами были представлены для инфраструктуры ЦОД провайдера связи, что доказывает эффективность предложенных методов

A cost-effective methodology applied to videoconference services over hybrid clouds

This paper tackles the optimization of applications in multi-provider hybrid cloud scenarios from an economic point of view. In these scenarios the great majority of solutions offer the automatic allocation of resources on different cloud providers based on their current prices. However our approach is intended to introduce a novel solution by making maximum use of divide and rule. This paper describes a methodology to create cost aware cloud applications that can be broken down into the three most important components in cloud infrastructures: computation, network and storage. A real videoconference system has been modified in order to evaluate this idea with both theoretical and empirical experiments. This system has become a widely used tool in several national and European projects for e-learning and collaboration purposes

Планування завантаження ресурсів центру обробки даних на основі статистичних даних

The customer service quality depends on the procedure of the application maintenance in data center of the communication provider. In the article the control approach of dynamic resource involvement has been suggested in order to ensure the input flow maintenance that takes into account the random nature of applications’ inflow and utilizes both short-term and long-term load statistics. The proposed approach consists of two methods that manage the number of the implicated serving nodes. The first one verifies the resource amount adequacy, provides the evaluation of input load’s dynamics based on the short-term statistics as well as the current state of the technical facilities. The second one accounts for the long-term statistics according to which the implication of additional resources can be scheduled during the load peaks. The simulation results of technical resources management have been presented for the data center infrastructure of the communication provider, that prove the effectiveness of the proposed methods.Качество обслуживания клиентов зависит от процедуры поддержки приложений в центре обработки данных поставщика связи. В статье рассматривается подход контроля динамического использования ресурсов для обеспечения обслуживания входящего потока, который принимает во внимание случайный характер поступления заявок и использует краткосрочные и долгосрочные статистические нагрузки. Предложенный подход состоит из двух методов, которые управляют количеством обслуживающих узлов. Результаты моделирования управления техническими ресурсами были представлены для инфраструктуры ЦОД провайдера связи, что доказывает эффективность предложенных методов.Якість обслуговування клієнтів залежить від процедури підтримки прикладних програм в центрі обробки даних постачальника зв'язку. У статті розглядається підхід контролю динамічного використання ресурсів для забезпечення обслуговування вхідного потоку, який враховує випадковий характер надходження заявок і використовує короткострокові і довгострокові статистичні навантаження. Запропонований підхід складається з двох методів, які керують кількістю обслуговуючих вузлів. Результати моделювання управління технічними ресурсами були представлені для інфраструктури ЦОД провайдера зв'язку, що доводить ефективність запропонованих методів

Cost-aware scheduling of deadline-constrained task workflows in public cloud environments

Public cloud computing infrastructure offers resources on-demand, and makes it possible to develop applications that elastically scale when demand changes. This capacity can be used to schedule highly parallellizable task workflows, where individual tasks consist of many small steps. By dynamically scaling the number of virtual machines used, based on varying resource requirements of different steps, lower costs can be achieved, and workflows that would previously have been infeasible can be executed. In this paper, we describe how task workflows consisting of large numbers of distributable steps can be provisioned on public cloud infrastructure in a cost-efficient way, taking into account workflow deadlines. We formally define the problem, and describe an ILP-based algorithm and two heuristic algorithms to solve it. We simulate how the three algorithms perform when scheduling these task workflows on public cloud infrastructure, using the various instance types of the Amazon EC2 cloud, and we evaluate the achieved cost and execution speed of the three algorithms using two different task workflows based on a document processing application

Modeling the virtual machine allocation problem

Finding the right allocation of virtual machines (VM) in cloud data centers is one of the key optimization problems in cloud computing. Accordingly, many algorithms have been proposed for the problem. However, lacking a single, generally accepted formulation of the VM allocation problem, there are many subtle differences in the problem formulations that these algorithms address; moreover, in several cases, the exact problem formu- lation is not even defined explicitly. Hence in this paper, we present a comprehensive generic model of the VM allocation problem. We also show how the often-investigated problem variants fit into this general model

Data centre optimisation enhanced by software defined networking

Contemporary Cloud Computing infrastructures are being challenged by an increasing demand for evolved cloud services characterised by heterogeneous performance requirements including real-time, data-intensive and highly dynamic workloads. The classical way to deal with dynamicity is to scale computing and network resources horizontally. However, these techniques must be coupled effectively with advanced routing and switching in a multi-path environment, mixed with a high degree of flexibility to support dynamic adaptation and live-migration of virtual machines (VMs). We propose a management strategy to jointly optimise computing and networking resources in cloud infrastructures, where Software Defined Networking (SDN) plays a key enabling role