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The Modeling, Simulation, and Operational Control of Aerospace Communication Networks THE MODELING, SIMULATION, AND OPERATIONAL CONTROL OF AEROSPACE COMMUNICATION NETWORKS by BRIAN JAMES BARRITT Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Thesis Adviser: Dr. Francis L. Merat Department of Electrical Engineering and Computer Science CASE WESTERN RESERVE UNIVERSITY August, 2017 The Modeling, Simulation, and Operational Control of Aerospace Communication Networks Case Western Reserve University Case School of Graduate Studies We hereby approve the thesis1 of BRIAN JAMES BARRITT for the degree of Doctor of Philosophy Frank Merat Committee Chair, Adviser June 30, 2017 Department of Electrical, Computer, and Systems Engineering Michael Rabinovich Committee Member June 30, 2017 Department of Computer Science Daniel Saab Committee Member June 30, 2017 Department of Electrical, Computer, and Systems Engineering Mark Allman Committee Member June 30, 2017 Department of Computer Science 1We certify that written approval has been obtained for any proprietary material contained therein. Dedicated to Sharon Barritt, who gave me roots and wings... Table of Contents List of Tables vi List of Figures vii Acknowledgementsx Abstract xi Chapter 1. Introduction1 Chapter 2. Modeling and Simulation5 Approach 9 Software 18 Trade Studies 19 Conclusions and Future Work 22 Chapter 3. Temporospatial SDN 24 Software-Defined Networking 24 Temporospatial SDN 27 Implementation 34 Conclusions 42 Chapter 4. Use Case: LEO Constellations 43 TS-SDN vs. Dynamic Routing 50 Next Steps and Future Work 58 Conclusions 59 Chapter 5. Use Case: High Altitude Platforms 60 iv Network Architecture 61 Mesh & Backhaul Challenges 63 Temporospatial SDN 65 SDN and Distributed Routing in HAPS 65 Conclusions 72 Chapter 6. Suggested Future Research 74 NBI and CDPI Standardization 74 Network Functions Virtualization 75 Mobile, 5G, and CORD 76 Delay Tolerant Networking 78 Complete References 80 v List of Tables 4.1 OLSR Configuration Tuning Parameters 48 4.2 Simulation Results Summary 57 5.1 Comparison of Three Mesh Routing Protocols 66 5.2 Comparison time at startup (in seconds) 69 vi List of Figures 2.1 An example protocol stack diagram for a LEO constellation that provides Internet access. A high fidelity virtual network model can be built by modeling the ground segment topology, network protocols, and network application traffic in a network simulator while modeling the space-to-ground links, inter-satellite links, and air interface physical layers (highlighted) in a spatial temporal information system, such as STK. 10 2.2 STK Networking Architecture 14 2.3 Screenshot from STK’s Report & Graph Manager showing return-link TCP throughput over time for an example mission scenario of a Cubesat downloading science data during communication through a ground station in Poker Flat, Alaska. TCP’s slow-start algorithm for congestion avoidance is evident in the slow ramp-up in throughput in the beginning of the plot. 19 2.4 End-to-end voice application latency is observed to change over time, with a substantial increase occurring after the TDRS hand-off.1 20 2.5 The saw-tooth pattern in application packet latency is due to the insertion of ”idle frames” into the Advanced Orbiting Systems (AOS) space data link protocol.1 21 3.1 A high-level overview of the software-defined networking architecture2 25 vii 3.2 The network data model represents the nodes (vertices) and links (edges) in the topology and includes all accessible wired and wireless links. The data model is time-dynamic; each directional edge is associated with a set of time intervals of predicted accessibility with predicted link metrics throughout each accessible interval. 37 3.3 The network topology is annotated with required end-to-end packet connectivity and provisioned flow capacities. 37 3.4 A traffic engineered solution is created by finding a satisficing subgraph or spanning tree. 38 3.5 Our implementation includes a topology and routing service, which jointly optimizes the wireless network topology and routing while transitioning it through phases in time. 40 4.1 Example polar orbiting LEO constellation, from the ns2.35 manual, generated using SAVI3. 47 4.2 Simplified Simulation Network Topology 51 4.3 A TCP time-sequence plot, generated using the tcptrace tool4, showing multiple costly retransmission timeouts (RTOs) resulting from the soft handover event. 54 4.4 A TCP time-sequence plot, generated using the tcptrace tool4, showing that additional RTO events occur with the hard handovers. 55 5.1 While it is relatively common for Internet access networks to accommodate mobility in the Access Layer, high-altitude platform viii systems and LEO satellite networks must also accommodate mobility in their Distribution Layer. 61 5.2 Visualization of the simulated network topology. 67 5.3 Probability distribution function of mesh routing protocol startup convergence times for all nodes to find a route to a designated EPC node. 70 5.4 Probability distribution function of mesh routing protocol convergence times in repairing a single route upon link failure. 70 ix Acknowledgements I would like to express my sincere gratitude to my advisor, Prof. Frank Merat, for his continuous support of my Ph.D study and related research. I’d also like to thank Dr. Kul Bhasin, for fostering and supporting this area of research and development at NASA Glenn Research Center; Wes Eddy, who was co-author on several of my publications in this field and co-inventor of Astrolink Protocol; and David Mandle, who co-designed and completely implemented the Topology and Routing Service in our Temporospatial SDN implementation. And I’d like to thank Google and X, the Moonshot Factory, for sup- porting my work in this field and for approving publications disclosing our application and implementation of this research on projects there. Additional acknowledgement, appreciation, and credit are due to Mike Fuentes, Ta- tiana Kichkaylo, Nicolas Thiébaud, You Han, Ketan Mandke, Adam Zalcman, and Victor Lin for their collaboration on the ideas, network simulations, implementations, and pa- per publications related to this research. x Abstract The Modeling, Simulation, and Operational Control of Aerospace Communication Networks Abstract by BRIAN JAMES BARRITT A paradigm shift is taking place in aerospace communications. Traditionally, aerospace systems have relied upon circuit switched communications; geostationary communications satellites act as bent-pipe transponders and are not burdened with packet processing and the complexity of mobility in the network topology. But factors such as growing mission complexity and NewSpace development practices are driving the rapid adoption of packet-based network protocols in aerospace networks. Mean- while, several new aerospace networks are being designed to provide either low la- tency, high-resolution imaging or low-latency Internet access while operating in non- geostationary orbits – or even lower, in the upper atmosphere. The need for high data- rate communications in these networks is simultaneously driving greater reliance on beamforming, directionality, and narrow beamwidths in RF communications and free- space optical communications. This dissertation explores the challenges and offers novel solutions in the modeling, simulation, and operational control of these new aerospace networks. In the concept, design, and development phases of such networks, the dissertation motivates the use of xi network simulators to model network protocols and network application traffic instead of relying solely on link budget calculations. It also contributes a new approach to net- work simulation that can integrate with spatial temporal information systems for high- fidelity modeling of time-dynamic geometry, antenna gain patterns, and wireless signal propagation in the physical layer. And towards the operational control of such networks, the dissertation introduces Temporospatial Software Defined Networking (TS-SDN), a new approach that leverages predictability in the propagated motion of platforms and high-fidelity wireless link modeling to build a holistic, predictive view of the accessi- ble network topology and provides SDN applications with the ability to optimize the network topology and routing through the direct expression of network behavior and requirements. This is complemented by enhancements to the southbound interface to support synchronized future enactment of state changes in order to tolerate varying de- lay and disruption in the control plane. A high-level overview of an implementation of Temporospatial SDN at Alphabet is included. The dissertation also describes and demonstrates the benefits of the application of TS-SDN in Low Earth Orbiting (LEO) satellite constellations and High Altitude Platform Systems (HAPS). xii 1 1 Introduction For the last two decades there has been a tremendous amount of work on the use of commercial networking protocols for aerospace communications. Today, three ma- jor forces continuing to drive the use of networking protocols in aerospace are (1) mis- sion complexity5, (2) increased adoption of modern consumer electronics technologies and standards, and (3) new potential applications for aerospace platforms in providing broadband Internet service to those who lack economical access. The mission complexity expected for most new flagship aerospace systems, with multiple on-board instruments and payloads, flight computers, and other avionics sys- tems, is driving the industry towards networked platforms, which utilize packet or frame structures for
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