Hazard alerting and situational awareness in advanced air transport cockpits

Advances in avionics and display technology have significantly changed the cockpit environment in current 'glass cockpit' aircraft. Recent developments in display technology, on-board processing, data storage, and datalinked communications are likely to further alter the environment in second and third generation 'glass cockpit' aircraft. The interaction of advanced cockpit technology with human cognitive performance has been a major area of activity within the MIT Aeronautical Systems Laboratory. This paper presents an overview of the MIT Advanced Cockpit Simulation Facility. Several recent research projects are briefly reviewed and the most important results are summarized

PINT: Probabilistic In-band Network Telemetry

© 2020 ACM. Commodity network devices support adding in-band telemetry measurements into data packets, enabling a wide range of applications, including network troubleshooting, congestion control, and path tracing. However, including such information on packets adds significant overhead that impacts both flow completion times and application-level performance. We introduce PINT, an in-band network telemetry framework that bounds the amount of information added to each packet. PINT encodes the requested data on multiple packets, allowing per-packet overhead limits that can be as low as one bit. We analyze PINT and prove performance bounds, including cases when multiple queries are running simultaneously. PINT is implemented in P4 and can be deployed on network devices.Using real topologies and traffic characteristics, we show that PINT concurrently enables applications such as congestion control, path tracing, and computing tail latencies, using only sixteen bits per packet, with performance comparable to the state of the art

Dynamics of change in the US air transportation system

Thesis (Ph. D. in Technology, Management, and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology, Management, and Policy Program, 2008."June 2008."Includes bibliographical references (p. 227-244).The US Air Transportation System is currently facing a number of challenges including an increasing demand for travel and growing environmental requirements. In order to successfully meet future needs, the system will need to transition from its current state using a combination of technology, infrastructure, procedure, and policy changes. However, the complexities of the air transportation system make implementing changes a challenge. In particular, the multi-stakeholder nature of the system poses a significant barrier to transition. Historically, many changes in the air transportation system were driven by safety concerns and implemented following accidents which provided the momentum to overcome transition barriers. As a result of past changes, the system has become increasingly safe resulting in the emergence of new drivers for change. Security has emerged as a driver following the terrorist attacks of 9/11/2001 in the US and a number of system changes have since been implemented. Currently, capacity is one of the largest drivers of change. Addressing capacity issues requires solutions that can be accepted by stakeholders, and pass the necessary certification and approval requirements for implementation. The contribution of aviation to global greenhouse gas emissions is also becoming a significant driver for change in the system. The goal of this work is to understand how the air transportation system changes in response to safety, security, capacity, and environmental drivers for transition. In order to understand the dynamics of transition, historical cases of system change were studied. Twenty seven such cases have been analyzed to construct a feedback process model of transition and to explore specific change dynamics observed.(cont.) These dynamics include: understanding the role of crisis events as catalyst for change; the effect that timing of solution development has on the overall time constant for change; the role that stakeholder objectives play in the transition process, and the use of approval and certification processes to stall or block change. understanding the process of change in the US Air Transportation System can inform future changes in aviation as well as in other systems with similar properties.by Aleksandra L. Mozdzanowska.Ph.D

A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

Joint University Program for Air Transportation Research, 1991-1992

This report summarizes the research conducted during the academic year 1991-1992 under the FAA/NASA sponsored Joint University Program for Air Transportation Research. The year end review was held at Ohio University, Athens, Ohio, June 18-19, 1992. The Joint University Program is a coordinated set of three grants sponsored by the Federal Aviation Administration and NASA Langley Research Center, one each with the Massachusetts Institute of Technology (NGL-22-009-640), Ohio University (NGR-36-009-017), and Princeton University (NGL-31-001-252). Completed works, status reports, and annotated bibliographies are presented for research topics, which include navigation, guidance and control theory and practice, intelligent flight control, flight dynamics, human factors, and air traffic control processes. An overview of the year's activities for each university is also presented

Source-Routed Multicast Schemes for Large-Scale Cloud Data Center Networks

Data centers (DCs) have been witnessing unprecedented growth in size, number and complexity in recent years. They consist of tens of thousands of servers interconnected by fast network switches, hosting and enabling numerous applications with various traffic characteristics and requirements. As a result, DC networks have been presented with several unique challenges, pertaining to the scaling and allocation of network resources during the forwarding and moving of data across the different DC servers. Traffic routing in general and multicast routing in particular are important functions in DC networks, especially that modern cloud DCs tend to exhibit one-to-many communication traffic patterns. Unfortunately, recent multicast routing approaches that adopt IP multicast suffer from scalability and load balancing issues, and do not scale well with the number of supported multicast groups when used for cloud DC networks. In this thesis, we propose a set of new, complementary schemes that overcome these challenges. More specifically, firstly, we study existing DC network topologies, and propose Circulant Fat-Tree topology, an improvement over the traditional Fat-Tree topology with better properties to suit nowadays DC networks. Then, we review and classify recent studies that investigate and measure the traffic behavior of operational DC networks. We focus on the way they collect the traffic as well as on the key findings made in these studies. Secondly, we propose Bert, a source-initiated multicast routing scheme for DCs. Bert scales well with both the number and the size of multicast groups, and does so through clustering, by dividing the members of the multicast group into a set of clusters with each cluster employing its own forwarding rules. In essence, Bert yields much lesser multicast traffic overhead than state-of-the-art schemes. Thirdly, we propose, Ernie, a scalable and load-balanced multicast source routing scheme. Ernie introduces a novel method for scaling out the number of supported mul- ticast groups. In particular, it appropriately constructs and organizes multicast header information inside packets in a manner that allows core/root switches to only forward down the needed information. Ernie also introduces an effective multicast traffic load balancing technique across downstream links. Specifically, it prudently assigns multicast groups to core switches to ensure the evenness of load distribution across the downstream links

Software-defined datacenter network debugging

Software-defined Networking (SDN) enables flexible network management, but as networks evolve to a large number of end-points with diverse network policies, higher speed, and higher utilization, abstraction of networks by SDN makes monitoring and debugging network problems increasingly harder and challenging. While some problems impact packet processing in the data plane (e.g., congestion), some cause policy deployment failures (e.g., hardware bugs); both create inconsistency between operator intent and actual network behavior. Existing debugging tools are not sufficient to accurately detect, localize, and understand the root cause of problems observed in a large-scale networks; either they lack in-network resources (compute, memory, or/and network bandwidth) or take long time for debugging network problems. This thesis presents three debugging tools: PathDump, SwitchPointer, and Scout, and a technique for tracing packet trajectories called CherryPick. We call for a different approach to network monitoring and debugging: in contrast to implementing debugging functionality entirely in-network, we should carefully partition the debugging tasks between end-hosts and network elements. Towards this direction, we present CherryPick, PathDump, and SwitchPointer. The core of CherryPick is to cherry-pick the links that are key to representing an end-to-end path of a packet, and to embed picked linkIDs into its header on its way to destination. PathDump is an end-host based network debugger based on tracing packet trajectories, and exploits resources at the end-hosts to implement various monitoring and debugging functionalities. PathDump currently runs over a real network comprising only of commodity hardware, and yet, can support surprisingly a large class of network debugging problems with minimal in-network functionality. The key contributions of SwitchPointer is to efficiently provide network visibility to end-host based network debuggers like PathDump by using switch memory as a "directory service" — each switch, rather than storing telemetry data necessary for debugging functionalities, stores pointers to end hosts where relevant telemetry data is stored. The key design choice of thinking about memory as a directory service allows to solve performance problems that were hard or infeasible with existing designs. Finally, we present and solve a network policy fault localization problem that arises in operating policy management frameworks for a production network. We develop Scout, a fully-automated system that localizes faults in a large scale policy deployment and further pin-points the physical-level failures which are most likely cause for observed faults

Joint University Program for Air Transportation Research, 1988-1989

The research conducted during 1988 to 1989 under the NASA/FAA-sponsored Joint University Program for Air Transportation Research is summarized. The Joint University Program is a coordinated set of three grants sponsored by NASA Langley Research Center and the Federal Aviation Administration, one each with the Massachusetts Institute of Technology, Ohio University, and Princeton University. Completed works, status reports, and annotated bibliographies are presented for research topics, which include computer science, guidance and control theory and practice, aircraft performance, flight dynamics, and applied experimental psychology. An overview of the year's activities for each university is also presented