Dynamic Airport Configuration and Resource Scheduling

Aiming at the problem of limited resources and operational time combat air defense combat, naval combat formation analysis dynamic resources scheduling needs, on the basis of the establishment of ship dynamic scheduling model of warship formation combat resources dynamic combat formation resource scheduling, the operational resources and operational objectives, relationship between reasonable allocation of resources to play the warship formation combat operations the maximum efficiency. The design of three kinds of air defense command models: centralized platform free attack mode, command mode, request attack mode of air defense strategy, put forward the dynamic scheduling hybrid algorithm for solving the model, according to the naval fleet air defense combat scenario example for simulation. The simulation results show that the air defense strategy with the request attack mode can have effects on multi-target attacks under the shared combat situation, and the hybrid algorithm based on combat resource dynamic scheduling can meet the real-time operational requirements.

A number of Federal Aviation Administration (FAA) automation systems and developmental programs interoperate to support the day-to-day operations of the National Airspace System (NAS). The integration of New Entrants (NEs), such as Remotely Piloted Aircraft (RPA) 1 and Space Vehicle (SV) operations, into the NAS will require modification to the current state of automation. Examining the relevant operational, technical, and procedural implications of integrated NE operations, in addition to exploring the potential impacts of accelerated RPA usage on NAS dynamics, are critically important efforts necessary to understanding operational impacts to NAS systems and users. Our paper presents the potential impacts of RPA integration on two of these systems: En Route Automation Modernization (ERAM) and Traffic Flow Management System (TFMS). A significant component of the impact on NAS systems comes from flight plan and related data processing since all SVs and many RPAs will fly non-standard flight patterns (e.g., RPA loitering and grid search). The processes and details of the non-traditional flight routes, as well different RPA performance specifications, need to be considered as missions are overlaid on the national jet route structure. Of particular concern and interest are the changes in air traffic control (ATC) and air traffic management (ATM) systems and sub-systems needed to address air traffic controller workload and workload complexity concerns associated with NE activities. One potential accommodation approach, presented in this paper, is the use of Dynamic Airspace Configuration both for RPA routine operations and contingency events. Additionally, we present an RPA 1 In this paper, UAS and RPA are used interchangeably without intending any difference per se. It is noted that the U.S. DoD and ICAO use RPA while NASA and the FAA use UAS. demand forecast tool developed under a National Aeronautics and Space Administration (NASA) project. This tool will assist the FAA in meeting its objectives for accommodation of RPA by providing accurate demand forecast information.

Mobile cloud computing (MCC) as an emerging and prospective computing paradigm, can significantly enhance computation capability and save energy of smart mobile devices (SMDs) by offloading computation-intensive tasks from resource-constrained SMDs onto the resource-rich cloud. However, how to achieve energy-efficient computation offloading under the hard constraint for application completion time remains a challenge issue. To address such a challenge, in this paper, we provide an energy-efficient dynamic offloading and resource scheduling (eDors) policy to reduce energy consumption and shorten application completion time. We first formulate the eDors problem into the energy-efficiency cost (EEC) minimization problem while satisfying the task-dependency requirements and the completion time deadline constraint. To solve the optimization problem, we then propose a distributed eDors algorithm consisting of three subalgorithms of computation offloading selection, clock frequency control and transmission power allocation. More importantly, we find that the computation offloading selection depends on not only the computing workload of a task, but also the maximum completion time of its immediate predecessors and the clock frequency and transmission power of the mobile device. Finally, our experimental results in a real testbed demonstrate that the eDors algorithm can effectively reduce the EEC by optimally adjusting the CPU clock frequency of SMDs based on the dynamic voltage and frequency scaling (DVFS) technique in local computing, and adapting the transmission power for the wireless channel conditions in cloud computing.

WiMAX network provides effective internet communication between users with low expense and ease of deployment. It is used efficiently in small to medium enterprises. However, proficient resource allocation and scheduling is still a critical requirement in WiMAX networks due to the varying factors related to the network communication. If the network resources are not appropriately allocated, then there are possibilities for missing out critical data, or wasting more resources on transmitting less important data which in turn will have adverse affect on data transmission in the future stages. Hence, in this paper, we propose to develop a Priority Based Dynamic Resource Allocation and Scheduling for WiMAX Networks. In this technique, the incoming data are dynamically allocated, and then users are prioritized to identify the critical users. The allocation and scheduling is performed by considering user priority, robustness and also power consumption rate to ensure effective network performance.

PurposeIn recent years, it is imperative to establish the structure of manufacturing industry in the context of smart factory. Due to rising demand for exchange of information with various devices, and huge number of sensor nodes, the industrial wireless networks (IWNs) face network congestion and inefficient task scheduling. For this purpose, software-defined network (SDN) is the emerging technology for IWNs, which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.Design/methodology/approachIn this paper, the authors present SDN based dynamic resource management and scheduling (DRMS) for effective devising of the resource utilization, scheduling, and hence successful transmission in a congested medium. Moreover, the earliest deadline first (EDF) algorithm is introduced in authors’ proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.FindingsThe result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio. At last, the proposed method outperforms the existing myopic algorithms in terms of query response time, energy consumption and success ratio (packet delivery) versus number of increasing nodes, respectively.Originality/valueThe authors proposed a priority based scheduling between the devices and it is done by the EDF approach. Therefore, the proposed work reduces the network delay time and minimizes the overall energy efficiency.

<div class="htmlview paragraph">“As we handle more operations and passengers in the air, we must make certain we have the capacity to handle increased traffic on the ground.”</div> <div class="htmlview paragraph">- Jane Garvey, FAA Administrator (4/20/98)</div> <div class="htmlview paragraph">The FAA Technical Center (Aviation System Analysis and Modeling Branch, ACT-520) has been responsive to the FAA Airport Capacity Program customers for the past 22 years, developing, testing, and applying airfield and airspace simulation models. More than 90 capacity studies have been completed with ACT-520 personnel contributing their technical expertise to the Airport Design Teams. The teams are comprised of FAA personnel, airport operators, air carriers, other airport users and aviation industry representatives at major airports throughout the US.</div> <div class="htmlview paragraph">Initial studies focused on modeling airport operations from final approach, taxi, gate operations and departure processing. Later in the program, local airspace studies were included in some airport study efforts. Both airport and airspace studies include either a full scale design team study or a less detailed tactical initiative. Recently, National Airspace System (NAS) modeling personnel joined the group providing system modeling expertise in the NAS Architecture and Flight 2000 programs.</div> <div class="htmlview paragraph">An arsenal of analysis tools and computer simulation programs has been developed and tested to accomplish each task. The group has experience using the models they have developed or improved upon (ADSIM, RDSIM, RQSIM, etc.), have obtained from other FAA entities (SIMMOD, NASPAC, RAAM, etc.) and have acquired under contract or agreements (The Airport Machine, TAAM, MIT Delays Model, etc.). This modeling capability permitted the group to perform simulations of improvements in the categories of airfield, facilities and equipment, ATC operational, and airport policy improvements. The delay effects of aircraft demand (schedules), fleet mix, runway configurations, weather, aircraft separation standards, etc., were measured in the studies.</div> <div class="htmlview paragraph">Future studies will require new model development particularly in the arena of system wide impacts measured on an annual basis. The requirement for an analyst to know both the model inputs and the working of the model's code will continue to apply for a successful study. As in the past, no universal model will answer every question and existing models will require enhancements to reflect unique requirements. Because of the increases in computing speed and memory, the fidelity of simulations can be enhanced in the near future through new hardware acquisitions.</div> <div class="htmlview paragraph">ACT 520's past participation in this enterprise has generated an understanding of the interrelationships of various airport and airline systems. Our seven senior analysts and eight junior analysts combined with their professional expertise are ready to address the FAA Administrator's concerns about capacity.</div>

This paper extends the process for validating the Airspace Concept Evaluation System using real-world historical flight operational data. System inputs such as flight plans and airport en-route capacities, are generated and processed to create a realistic reproduction of a single day's operations within the National Airspace System. System outputs such as airport throughput, delays, and en-route sector loads are then compared to real world operational metrics and delay statistics for the reproduced day. The process is repeated for 4 historical days with high and low traffic volume and delay attributed to weather. These 4 days are simulated using default en-route capacities and variable en-route capacities used to emulate weather. The validation results show that default enroute capacity simulations are closer to real-world data for low weather days than high weather days. The use of reduced variable enroute capacities adds a large delay bias to ACES but delay trends between weather days are better represented.

For a system to be managed, it must be measured. The National Airspace System (NAS), the collection of airspace and airport resources in and under the control of the United States (U.S.), is a very complex system which presents great challenges of measurement and management. One key measure of en route airspace efficiency is flying time, i.e., the amount of time it takes for an aircraft to travel through en route airspace on its flight from origin to destination airport. A number of factors influence flying time, the most obvious being the winds. Other important factors are: traffic congestion, air traffic management (ATM) interventions, route structure, industry strategies, and weather. In this paper, we calculate en route flying time in the aggregate and compare a subset of data for the years 2001 and 2002. We account for aircraft equipment type and adjusted flying time for wind effects. In addition, we have selected for analysis a sample of only good weather days (15 in each of the 2 years). The results show that 2002 has slightly shorter flying times than 2001, on the order of 20–25 seconds shorter. Although we did not investigate the causes for the change, we conjecture that the lower levels of traffic after the Fall of 2001 are causing less congestion and less delay. New automation and procedural initiatives may also be contributing to the improvement. Introduction The Federal Aviation Administration (FAA) is charged with the safe, efficient movement of air traffic in U.S. airspace. In recent years, the FAA has begun initiatives to measure efficiency of airspace usage. The measurements are useful for determining the impact of automation and procedural enhancements. Such measurements are also useful for identifying problem areas in the NAS, which can be targeted for remediation. Changes in efficiency may be examined as a function of time. This study assessed system efficiency using en route flying times, comparing 2001 versus 2002. Although several studies have been performed in the past calculating changes in en route flying distance, the authors are familiar with one time-based analysis in the open literature. Bolczak, et al. used Estimated Time of Arrival (ETA) data to analyze a trend in flying time, and discover some year-to-year changes. Other studies of flight times are in the literature, though they have not compared actual or modeled values across years. An early simulation of Free Flight, Ball, et al. analyzed flying times for flights without the constraints of route structuring. Efficiency may be defined as the level of utilization of a resource, with consideration of the cost or effort undertaken to achieve that level. † Free Flight is an industry/government initiative which provides greater freedom for pilots and airlines to select planned and flown routes and take-off times. Free Flight supports collaboration between airspace managers and airspace users. 1 American Institute of Aeronautics and Astronautics Willemain examined sources of variability in flying times for certain city pairs. The Bureau of Transportation Statistics has collected flight time statistics and hosts a web site which allows the public to access this information. In this study, results are presented in aggregated form, with some detail with respect to city pairs. Differences were found in the flying time metrics: 2002 has slightly lower flying times than 2001. The causes for this difference are not discussed.

An initial benefits assessment of NASA's Distributed Air/Ground Traffic Management has been co nducted. The single -year, national airspace system -wide benefits were estimated for each of three concept elements: En Route Free Maneuvering, En Route Trajectory Negotiation, and Terminal Arrival Self -Spacing . The study included several analytic compon ents including the identification of benefit mechanisms, forecasting of future traffic demand, trajectory modeling, schedule construction, airport and airspace capacity modeling, human performance modeling of controller workload, regional airspace simulati on (including conflict detection/resolution and trajectory optimization), demand/capacity balancing, and economic valuation. The results show that the two en route concept elements allow significantly more future demanded flights to be accommodated while the terminal area concept enables substantially lower levels of annual delay.

W-CDMA is the strongest candidate as the air interface technology of the third generation mobile communication systems, which are expected to support multimedia services with QoS requirements. In this paper, we review the W-CDMA technology and consider the issues in multimedia support. We propose the dynamic resource scheduling mechanism for QoS provisioning in W-CDMA through optimal power assignment and code hopping. Our framework is able to carry variable QoS multimedia traffic, efficiently serving a wide range of classes with CBR, VBR, ABR and UBR characteristics. Dynamic resource scheduling improves capacity and throughput performance. Other advantages are power saving and faster convergence to the desired power level.

DRDC Valcartier has initiated, through a PRECARN partnership project, the development of an advanced simulation testbed for the evaluation of the effectiveness of Network Enabled Operations in a coastal large volume surveillance situation. The main focus of this testbed is to study concepts like distributed information fusion, dynamic resources and networks configuration management, and self synchronising units and agents. This article presents the requirements, design and first implementation builds, and reports on some preliminary results. The testbed allows to model distributed nodes performing information fusion, dynamic resource management planning and scheduling, as well as configuration management, given multiple constraints on the resources and their communications networks. Two situations are simulated: cooperative and non-cooperative target search. A cooperative surface target behaves in ways to be detected (and rescued), while an elusive target attempts to avoid detection. The current simulation consists of a networked set of surveillance assets including aircraft (UAVs, helicopters, maritime patrol aircraft), and ships. These assets have electrooptical and infrared sensors, scanning and imaging radar capabilities. Since full data sharing over datalinks is not feasible, own-platform data fusion must be simulated to evaluate implementation and performance of distributed information fusion. A special emphasis is put on higher-level fusion concepts using knowledge-based rules, with level 1 fusion already providing tracks. Surveillance platform behavior is also simulated in order to evaluate different dynamic resource management algorithms. Additionally, communication networks are modeled to simulate different information exchange concepts. The testbed allows the evaluation of a range of control strategies from independent platform search, through various levels of platform collaboration, up to a centralized control of search platforms.

The relationship between airport congestion and passenger delays at an airport is determined by many factors. Among these factors are scheduled and actual flight times, flight itineraries, airport capacity, and turn around time between flights. From the existing recorded data, it is possible to present a general profile of both airport congestion and passenger delays, measured with respect to the published schedule, at major airports within the US. This paper illustrates the discrepancy between the two measurements. Airport congestion may be masked by flight schedules which account for routine arrival delays and/or with slack time provided for turn around at an airport. It is possible for an airport to be heavily utilized, with little or unnoticeable at-gate delays (measured with respect to scheduled arrival time). On the other hand, at-gate delays can occur at under-utilized airports. Arrival and departure queuing delays are better indicators of airport congestion than passenger delays. Average flight at-gate delays are derived from performance data and compared with simulation results for 30 of the busiest airports in USA for a good weather day. The effects of variations in schedule flight time and slack time are studied parametrically in the simulation and calibrated to match the recorded baseline national airspace system (NAS) delay profiles. This paper illustrates a technique for estimating NAS-wide impact of propagated flight delays, based upon a method for calibration a system-level simulation against real world delays as well as delays derived from other simulations.

PurposeAn important and challenging question for air transportation regulators and airport operators is the definition and specification of airport capacity. Annual capacity is used for long-term planning purposes as a degree of available service volume, but it poses several inefficiencies when measuring the true throughput of the system because of seasonal and daily variations of traffic. Instead, airport throughput is calculated or estimated for a short period of time, usually one hour. This brings about a mismatch: air traffic forecasts typically yield annual volumes, whereas capacity is measured on hourly figures. To manage the right balance between airport capacity and demand, annual traffic volumes must be converted into design hour volumes, so that they can be compared with the true throughput of the system. This comparison is a cornerstone in planning new airport infrastructures, as design-period parameters are important for airport planners in anticipating where and when congestion occurs. Although the design hour for airport traffic has historically had a number of definitions, it is necessary to improve the way air traffic design hours are selected. This study aims to provide an empirical analysis of airport capacity and demand, specifically focusing on insights related to air traffic design hours and the relationship between capacity and delay.Design/methodology/approachBy reviewing the empirical relationships between hourly and annual air traffic volumes and between practical capacity and delay at 50 European airports during the period 2004–2021, this paper discusses the problem of defining a suitable peak hour for capacity evaluation purposes. The authors use information from several data sources, including EUROCONTROL, ACI and OAG. This study provides functional links between design hours and annual volumes for different airport clusters. Additionally, the authors appraise different daily traffic distribution patterns and their variation by hour of the day.FindingsThe clustering of airports with respect to their capacity, operational and traffic characteristics allows us to discover functional relationships between annual traffic and the percentage of traffic in the design hour. These relationships help the authors to propose empirical methods to derive expected traffic in design hours from annual volumes. The main conclusion is that the percentage of total annual traffic that is concentrated at the design hour maintains a predictable behavior through a “potential” adjustment with respect to the volume of annual traffic. Moreover, the authors provide an experimental link between capacity and delay so that peak hour figures can be related to factors that describe the quality of traffic operations.Originality/valueThe functional relationships between hourly and annual air traffic volumes and between capacity and delay, can be used to properly assess airport expansion projects or to optimize resource allocation tasks. This study offers new evidence on the nature of airport capacity and the dynamics of air traffic design hours and delay.

This paper documents the results of fast-time simulations evaluating potential capacity benefits of procedure concepts developed for parallel approaches to closely spaced parallel runways (CSPR) at airports with runway spacing less than 2,500 feet. Currently, simultaneous arrival operations at CSPR airports rely on visual meteorological conditions (VMC). In inclement weather when visual procedures can no longer be applied, simultaneous arrivals must be discontinued. Application of standard aircraft separations based on instrument flight rules (IFR) effectively results in the loss of arrival operations on one of the two runways, significantly reducing the arrival capacity of CSPR airports. Proposed wind-dependent parallel approach concepts promise improvements in arrival capacity at CSPR airports by enabling continued operations of dual arrival streams in instrument meteorological conditions (IMC). The concepts permit dependent parallel arrival operations when meteorological conditions are determined to render approach paths free of wake vortices from preceding aircraft. The operations are expected to increase capacity during IMC and decrease weather-related delays at CSPR airports. Simulation results for 9 CSPR airports in the National Airspace System (NAS) suggest significant potential capacity benefits ranging from 2 to 18 additional arrival operations per hour depending upon the concept and airport. The paper outlines the proposed wake independent straight-in parallel approach concept and 12 procedural derivatives. It describes the model developed to visualize the operations and the Monte Carlo approach taken to quantify potential capacity benefits.

Emergency projects' optimal resource scheduling covers a complex and dynamic environment. The theory of constraints confirms that a bottleneck determines the whole system's performance. Dynamic scheduling of bottlenecks can simplify the complex system's problems. Firstly, the problem's characteristics were analyzed from the aspects of the optimal goals, which are the machine environment, processing characters, and constraints. The mathematical model was then built, and using the hybrid rescheduling strategy and the improved genetic algorithm, the dynamic scheduling of the bottleneck resources was accomplished. Finally, an example case demonstrates the algorithm's feasibility and effectiveness.