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Mr. Follen has been invited talk on subject of Greening of Aerospace and Aviation Canada-Ohio Aerospace Summit 2013, February 25-26, 2013. This two-day, bi-national aerospace and aviation conference will focus on identifying business and research opportunities providing meaningful industry updates with ample opportunity to network and scheduled business-to-business and researcher-to-researcher meetings.
In this paper, performance of a first-in, first-out (FIFO), selective retransmission scheme for the deep-space Ka-band link is presented and compared to the performance of a comparable X-band link. In this analysis, 16 months of water vapor radiometer (WVR) and advanced water vapor radiometer (AWVR) data from the three Deep Space Network (DSN) Communication Complexes (DSCC) were used to emulate weather effects on X-band and Ka-band links from Mars. Mars Reconnaissance Orbiter (MRO) X-band and Ka-band telecommunications parameters were used for spacecraft telecommunications capabilities. One pass per week per complex was selected from MRO's Deep Space Network (DSN) schedule from April 1, 2006 to August 31, 2007 for a total of 207 passes (69 passes per complex) for this analysis. For each pass both X-band and Ka-band links were designed using at most two data rates so that the expected pass capacity would be maximized subject to a minimum availability requirement (MAR). In conjunction with the WVR/AWVR data, elevation profiles of the selected passes and models for the performance of the antennas in the DSN were used to emulate the performance of both links. It was assumed that the retransmission of the data takes place not on the same pass as the original transmission but during subsequent passes. The data collected before a pass was assumed to be a fraction of the expected capacity of the pass as calculated through the link design process. Infinite spacecraft storage was assumed to obtain an upper bound on the spacecraft storage requirement. The independent parameters of this analysis were MAR and the ratio of data collected before a pass to the expected pass capacity. Since the selected passes did not occur at regular intervals, the delay in this analysis was measured in terms of number of passes. The throughput was measured in terms of number of bits received successfully on the ground. The results indicate that reasonable delay performance could be achieved with very high throughput for relatively low MAR values for data collection to expected pass capacity ratio of around 97% for Ka-band. The results indicate that, except for very low average delay requirements, the Ka-band link provides more than twice the throughput of the X-band link for the same amount of power consumed by the spacecraft. In addition, the results indicate that the required storage onboard the spacecraft is not prohibitive and good performance could be achieved by using a buffer size less than three times the maximum amount of data collected before a pass.
In this paper, performance of a first-in, first-out (FIFO), selective retransmission scheme for the deep-space Ka-band link is presented and compared to the performance of a comparable X-band link. In this analysis, 16 months of water vapor radiometer (WVR) and advanced water vapor radiometer (AWVR) data from the three Deep Space Network (DSN) Communication Complexes (DSCC) were used to emulate weather effects on X-band and Ka-band links from Mars. Mars Reconnaissance Orbiter (MRO) X-band and Ka-band telecommunications parameters were used for spacecraft telecommunications capabilities. One pass per week per complex was selected from MRO's Deep Space Network (DSN) schedule from April 1, 2006 to August 31, 2007 for a total of 207 passes (69 passes per complex) for this analysis. For each pass both X-band and Ka-band links were designed using at most two data rates so that the expected pass capacity would be maximized subject to a minimum availability requirement (MAR). In conjunction with the WVR/AWVR data, elevation profiles of the selected passes and models for the performance of the antennas in the DSN were used to emulate the performance of both links. It was assumed that the retransmission of the data takes place not on the same pass as the original transmission but during subsequent passes. The data collected before a pass was assumed to be a fraction of the expected capacity of the pass as calculated through the link design process. Infinite spacecraft storage was assumed to obtain an upper bound on the spacecraft storage requirement. The independent parameters of this analysis were MAR and the ratio of data collected before a pass to the expected pass capacity. Since the selected passes did not occur at regular intervals, the delay in this analysis was measured in terms of number of passes. The throughput was measured in terms of number of bits received successfully on the ground. The results indicate that reasonable delay performance could be achieved with very high throughput for relatively low MAR values for data collection to expected pass capacity ratio of around 97% for Ka-band. The results indicate that, except for very low average delay requirements, the Ka-band link provides more than twice the throughput of the X-band link for the same amount of power consumed by the spacecraft. In addition, the results indicate that the required storage onboard the spacecraft is not prohibitive and good performance could be achieved by using a buffer size less than three times the maximum amount of data collected before a pass.
This presentation covers fundamental requirements and considerations for developing schedulers in airport operations. We first introduce performance and functional requirements for airport surface schedulers. Among various optimization problems in airport operations, we focus on airport surface scheduling problem, including runway and taxiway operations. We then describe a basic methodology for airport surface scheduling such as node-link network model and scheduling algorithms previously developed. Next, we explain how to design a mathematical formulation in more details, which consists of objectives, decision variables, and constraints. Lastly, we review other considerations, including optimization tools, computational performance, and performance metrics for evaluation.
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Final paper is attached. The NASA developed Core Flight System (cFS) is a reusable software architecture that has been used on multiple spaceflight missions. By using this framework, missions are able to reuse code from other missions, as well as leverage deployment onto similar computer architectures (i.e. not "reinvent the wheel" on each new mission). The success in the cFS concept can be seen in the large number of projects using cFS at FSW-2018. The Habulous project is an Earth-based testbed, used for hardware and software that may one day be used on a future space habitat unit, with many participating groups from various NASA centers and aerospace organizations around the country. The distributed nature of the various teams mean that defining (and following) an interface definition is critical on the project. Additionally, since various groups use various types of computer hardware (32/64-bit, big/little endian, Linux/VxWorks/Windows) many additional complications exist in interfacing all the various components into a final integrated system. cFS is used on the majority the flight software (FSW) in running in Habulous. But some subsystems have elected to not use cFS, and use a software bridge (called SBN_lib) to interact with the other cFS nodes in Habulous. In order to most efficiently develop the FSW, a central database is used to define and store each message sent by cFS. A Command and Data Dictionary (CDD) is something nearly universal on spacecraft, but as a team we worked to develop the CDD before the SW development was complete, and not treat it like "as built" documentation. To manage the CDD, the cFS Command and Data Dictionary (CCDD) tool was chosen (available from NASA as open source software). The CCDD tool has successfully been used to automate/autocode a large amount of software used on Habulous, as we are hoping to use it to define even more items in the future (time-triggered Ethernet (TTE) network maps, CPU scheduling). Additionally, Habulous has been exploring the use of cFS on wildly heterogeneous CPUs, and how to coordinate all those various machines using/extending the software bus – network (SBN) application in cFS, as well as TTE to coordinate message passing between various synchronized machines. The major topics to be covered in the presentation are: (1) Updating to the CCSDS_v2 extended headers (and using CPU# as subsystem ID). (2) Managing all the message identification numbers for each cFS message sent/received on any of the various CPUs. (3) Using the CCDD information to automatically generate the C-header files that define the structure for all software bus (SB) commands/telemetry messages. (4) Using the CCDD to automatically generate XML Telemetry and Command Exchange (XTCE) files, which streams display production/integration/testing in a web based display architecture (5) Extending/customizing SBN to pass messages among computers on multiple networks. (6) Using "Protobetter" inside SBN to manage different endian-ness/architectures. (7) Using SBN_lib to allow non-cFS node to communicate with cFS nodes. (8) Developing TTE network and schedule tables for all the various CPUs to use.
We address the problem of navigating a set of moving agents, e.g. automated guided vehicles, through a transportation network so as to bring each agent to its destination at a specified time. Each pair of agents is required to be separated by a minimal distance, generally agent-dependent, at all times. The speed range, initial position, required destination, and required time of arrival at destination for each agent are assumed provided. The movement of each agent is governed by a controlled differential equation (state equation). The problem consists in choosing for each agent a path and a control strategy so as to meet the constraints and reach the destination at the required time. This problem arises in various fields of transportation, including Air Traffic Management and train coordination, and in robotics. The main contribution of the paper is a model that allows to recast this problem as a decoupled collection of problems in classical optimal control and is easily generalized to the case when inertia cannot be neglected. Some qualitative insight into solution behavior is obtained using the Pontryagin Maximum Principle. Sample numerical solutions are computed using a numerical optimal control solver.
NASA’s Deep Space Network (DSN) is a mission critical facility that supports many different space missions,from LEO to deep space exploration. In recent years, as the network has suffered from increasing oversubscription, more restrictions have been added to reduce the amount of manual scheduling labor necessary to come to consensus. In this paper, we describe a new auto-mated scheduling tool which takes advantage of these restrictions to bring the scheduling problem closer to feasibility. In addition, we describe an algorithm to reduce problem inputs given a partially-solved problem,thereby bringing the problem even closer to feasibility
Decentralized operating systems that control large multicomputers need techniques to schedule competing parallel programs called task forces. Wave scheduling is a probabilistic technique that uses a hierarchical distributed virtual machine to schedule task forces by recursively subdividing and issuing wavefront-like commands to processing elements capable of executing individual tasks. Wave scheduling is highly resistant to processing element failures because it uses many distributed schedulers that dynamically assign scheduling responsibilities among themselves. The scheduling technique is trivially extensible as more processing elements join the host multicomputer. A simple model of scheduling cost is used by every scheduler node to distribute scheduling activity and minimize wasted processing capacity by using perceived workload to vary decentralized scheduling rules. At low to moderate levels of network activity, wave scheduling is only slightly less efficient than a central scheduler in its ability to direct processing elements to accomplish useful work.
The International VLBI Service for Geodesy and Astrometry (IVS) has observed the weekly IVS-R1 (R1) and IVS-R4 (R4) series of sessions since 2002. These regular series are generally stable in the sense that the networks were designed to be similar from week to week. The uniformity of these series has allowed researchers to conduct many scientific investigations. The IVS also observes with other networks that allow continued sampling of data from all VLBI stations, but the R1 and R4 observing sessions are a dominant part of overall VLBI observing accounting for 1841 sessions out of a total of 3129 24-hour sessions from 2002.0 to 2020.0 (where the last R1 and R4 in 2019 was on December 30 and December 26, respectively). In this paper, we investigate the evolution of these series in terms of their observing networks. We also discuss the construction of the R1 and R4 networks and the scheduling of these sessions. The performance of these networks in terms of the formal precision of polar motion have improved by factors of 2–3 over the period from 2002.0 to 2018.0. UT1 precision improved by a factor of about 1.2–1.5. The main reason for this improvement is the increased size of the networks. We also discuss the effect on this improvement arising from changes in the data rate and the number of observed sources. There is some degradation in performance after 2018 that is most likely due to a decline in the number of available network stations.
The goal of Delay Tolerant Networking (DTN) is to provide the missing ingredient for the ever-growing collection of communicating nodes in our solar system to become a Solar System Internet (SSI). Great strides have been made in modeling particular types of DTNs, such as schedule- or discovery-based. Now, analogously to the Internet, these smaller DTNs can be considered routing domains which must be stitched together to form the overall SSI. In this paper, we propose a framework for cross-domain routing in DTNs as well as methodologies for detecting these sub-domains. Example time-varying networks are given to demonstrate the techniques proposed. A basic component is the mathematical theory of sheaves, which unifies the underlying model of DTN routing algorithms, by giving rise to routing sheaves – these can be defined for the dynamic and scheduled networks as noted above, and can also be used to define the interfaces between these domains in order to route across them. An immediate application would be routing across discovery-based networks connected by scheduled networks. These DTN subdomains remain elusive, however, and need to become well-defined and properly sized for tractable computability. In particular, a balance must be determined between areas that are too large (i.e. large matrix computations) versus areas that are too small (i.e. “many” single-noded domains). Moreover, the connections between the domains should, at least locally, be chosen to optimize data flow and connectivity: we address this in three ways. First, tools from persistent homology are given to understand underlying structures, reminiscent of hierarchies in the Internet Protocol (IP) addressing. Second, we construct a notion of temporal graph curvature based on network geometry to analyze flows induced by dynamical processes on these networks. Finally, Schrodinger Bridges, a tool arising from statistical physics, are proposed as a method of constructing flows on time-evolving networks with desirable properties such as speed, robustness, and load sensitivity. We construct an approach to temporal hypergraphs to simultaneously model unicast, multicast, and broadcast, using the language of scheme theory, and then consider DTN network coding as a way to achieve network-level computation and organization. The paper concludes with a discussion and ideas for future work.
The work described in this paper was inspired by a surprisingly effective neural network developed for scheduling astronomical observations on the Hubble Space Telescope. Our heuristic constraint satisfaction problem (CSP) method was distilled from an analysis of the network. In the process of carrying out the analysis, we discovered that the effectiveness of the network has little to do with its connectionist implementation. Furthermore, the ideas employed in the network can be implemented very efficiently within a symbolic CSP framework. The symbolic implementation is extremely simple. It also has the advantage that several different search strategies can be employed, although we have found that hill-climbing methods are particularly well-suited for the applications that we have investigated. We begin the paper with a brief review of the neural network. Following this, we describe our symbolic method for heuristic repair.
The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.
A computer model is described which uses mixed-integer linear programming to provide optimal DSN spacecraft schedules given a mission set and specified scheduling requirements. A solution technique is proposed which uses Bender's method and a heuristic starting algorithm.
We identified a fairness problem in a network-based key-value storage system using Intel Storage Performance Development Kit (SPDK) in a multitenant environment. In such an environment, each tenant’s I/O service rate is not fairly guaranteed compared to that of other tenants. To address the fairness problem, we propose OctoFAS, a two-level fair scheduler designed to improve overall throughput and fairness among tenants. The two-level scheduler of OctoFAS consists of (i) inter-core scheduling and (ii) intra-core scheduling. Through inter-core scheduling, OctoFAS addresses the load imbalance problem that is inherent in SPDK on the storage server by dynamically migrating I/O requests from overloaded cores to underloaded cores, thereby increasing overall throughput. Intra-core scheduling prioritizes handling requests from starving tenants over well-fed tenants within core-specific event queues to ensure fair I/O services among multiple tenants. OctoFAS is deployed on a Linux cluster with SPDK. Through extensive evaluations, we found that OctoFAS ensures that the total system throughput remains high and balanced, while enhancing fairness by approximately 10% compared to the baseline, when both scheduling levels operate in a hybrid fashion.
A detailed Lunar Ultraviolet Telescope Experiment (LUTE) program plan representing major decisions and tasks leading to those decisions for program execution are presented. The purpose of this task was to develop an integrated plan of project activities for the LUTE project, and to display the plan as an integrated network that shows the project activities, all critical interfaces, and schedules. The integrated network will provide the project manager with a frame work for strategic planning and risk management throughout the life of the project.
The Network Queueing System (NQS) was designed to schedule jobs based on limits within queues. As systems obtain more memory, the number of queues increased to take advantage of the added memory resource. The problem now becomes too many queues. Having a large number of queues provides users with the capability to gain an unfair advantage over other users by tailoring their job to fit in an empty queue. Additionally, the large number of queues becomes confusing to the user community. The High Speed Processors group at the Numerical Aerodynamics Simulation (NAS) Facility at NASA Ames Research Center developed a new approach to batch job scheduling. This new method reduces the number of queues required by eliminating the need for queues based on resource limits. The scheduler examines each request for necessary resources before initiating the job. Also additional user limits at the complex level were added to provide a fairness to all users. Additional tools which include user job reordering are under development to work with the new scheduler. This paper discusses the objectives, design and implementation results of this new scheduler
The Air Force Space Command schedules telemetry, tracking and control activities across the Air Force Satellite Control network. The Range Scheduling Aid (RSA) is a rapid prototype combining a user-friendly, portable, graphical interface with a sophisticated object-oriented database. The RSA has been a rapid prototyping effort whose purpose is to elucidate and define suitable technology for enhancing the performance of the range schedulers. Designing a system to assist schedulers in their task and using their current techniques as well as enhancements enabled by an electronic environment, has created a continuously developing model that will serve as a standard for future range scheduling systems. The RSA system is easy to use, easily ported between platforms, fast, and provides a set of tools for the scheduler that substantially increases his productivity.