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Fractionated spacecraft - a cluster of simple satellites that are wirelessly connected, perform high-resolution sensing functions by running distributed sensor fusion applications. Coordinated swarms of networked Unmanned Aerial Vehicles carry out data collection damage assessment flights over large geographical areas affected by weather events. Fleets of Unmanned Underwater Vehicles collect climate change data from oceans with the help of sensor fusion and motion control applications. Smart data acquisition and control devices implement distributed sensing and control functions for the Smart Electric Grid. Such `cyber-physical cloud computing platforms' present novel challenges because the system is built from mobile embedded devices, is inherently distributed and typically has highly fluctuating connectivity among the modules. Architecting software for these systems raises many challenges not present in traditional cloud computing. Effective management of constrained resources and application isolation without adversely affecting performance are necessary. Autonomous fault management and real-time performance requirements must be met in a verifiable manner. It is also both critical and challenging to support multiple end-users whose diverse software applications have changing demands for computational and communication resources, while operating on different levels and in separate domains of security. The solution presented in this paper is based on a layered architecture consisting of a novel operating system, a middleware layer, and component-structured applications. The component model facilitates the creation of software applications from modular and reusable components that are deployed in the distributed system and interact only through well-defined mechanisms. The complexity of creating applications and performing system integration is mitigated through the use of a domain-specific model-driven development process that relies on a domain-specific modeling language and its accompanying graphical modeling tools, software generators for synthesizing infrastructure code, and the extensive use of model-based analysis for verification and validation.
Authored by Gabor Karsai, Daniel Balasubramanian, Abhishek Dubey, and William Otte
Multi-module Cyber-Physical Systems (CPSs), such as satellite clusters, swarms of Unmanned Aerial Vehicles (UAV), and fleets of Unmanned Underwater Vehicles (UUV) are examples of managed distributed real-time systems where mission-critical applications, such as sensor fusion or coordinated flight control, are hosted. These systems are dynamic and reconfigurable, and provide a "CPS cluster-as-a-service'' for mission-specific scientific applications that can benefit from the elasticity of the cluster membership and heterogeneity of the cluster members. Distributed and remote nature of these systems often necessitates the use of Deployment and Configuration (D\&C) services to manage lifecycle of software applications. Fluctuating resources, volatile cluster membership and changing environmental conditions require resilience. However, due to the dynamic nature of the system, human intervention is often infeasible. This necessitates a self-adaptive D\&C infrastructure that supports autonomous resilience. Such an infrastructure must have the ability to adapt existing applications on the fly in order to provide application resilience and must itself be able to adapt to account for changes in the system as well as tolerate failures. This paper describes the design and architectural considerations to realize a self-adaptive, D\&C infrastructure for CPSs. Previous efforts in this area have resulted in D\&C infrastructures that support application adaptation via dynamic re-deployment and re-configuration mechanisms. Our work, presented in this paper, improves upon these past efforts by implementing a self-adaptive D\&C infrastructure which itself is resilient. The paper concludes with experimental results that demonstrate the autonomous resilience capabilities of our new D\&C infrastructure.
Authored by Subhav Pradhan, William Otte, Abhishek Dubey, Csanad Szabo, Aniruddha Gokhale, and Gabor Karsai
Model- and component-based design have yielded dramatic increase in design productivity in several narrowly focused homogeneous domains, such as signal processing, control and aspects of electronic design. However, significant impact on the design and manufacturing of complex cyber-physical systems (CPS) such as vehicles has not yet been achieved. This paper describes challenges of and solution approaches to building a comprehensive design tool suite for complex CPS. The primary driver for the OpenMETA tool chain was to push the boundaries of the “correct-by-construction” principle to decrease significantly the costly design-build-test-redesign cycles in design flows. In the discussions we will focus on the impact of heterogeneity in modeling CPS. This challenge is compounded by the need for rapidly evolving the design flow by changing/updating the selection of modeling languages, analysis and verification tools and synthesis methods. Based on our experience with the development of OpenMETA and with the evaluation of its performance in a complex CPS design challenge we argue that the current vertically integrated, discipline-specific tool chains for CPS design need to be complemented with horizontal integration layers that support model integration, tool integration and design process integration. This paper will examine the OpenMETA technical approach to construct the new integration layers, provides and overview of the technical framework we established for their implementation and summarize our experience with their application.
Authored by J. Sztipanovits, T Bapty, S. Neema, L Howard, and E Jackson
A distributed spacecraft is a cluster of independent satellite modules flying in formation that communicate via ad-hoc wireless networks. This system in space is a cloud platform that facilitates sharing sensors and other computing and communication resources across multiple applications, potentially developed and maintained by different organizations. Effectively, such architecture can realize the functions of monolithic satellites at a reduced cost and with improved adaptivity and robustness. Openness of these architectures pose special challenges because the distributed software platform has to support applications from different security domains and organizations, and where information flows have to be carefully managed and compartmentalized. If the platform is used as a robust shared resource its management, configuration, and resilience becomes a challenge in itself. We have designed and prototyped a distributed software platform for such architectures. The core element of the platform is a new operating system whose services were designed to restrict access to the network and the file system, and to enforce resource management constraints for all non-privileged processes Mixed-criticality applications operating at different security labels are deployed and controlled by a privileged management process that is also pre-configuring all information flows. This paper describes the design and objective of this layer.
Authored by William Otte, Abhishek Dubey, and Gabor Karsai
Authored by Michael Myers, Ariosto Jorge, Don Yuhas, and Greg Walker
Authored by Gabor Simko, Tihamer Levendovszky, Miklos Maroti, and Janos Sztipanovits
Authored by G. Simko, D. Lindecker, T. Levendovszky, S. Neema, and J. Sztipanovits
Authored by Celaya Jose, Chetan Kulkarni, Gautam Biswas, and Goebel Kai
Authored by Benjamin Babjak, Sandor Szilvasi, and Peter Volgyesi
Authored by David Lindecker, Gabor Simko, Istvan Madari, Tihamer Levendovszky, and Janos Sztipanovits
Fractionated spacecraft is a novel space architecture that uses a cluster of small spacecraft modules (with their own attitude control and propulsion systems) connected via wireless links to accomplish complex missions. Resources, such as sensors, persistent storage space, processing power, and downlink bandwidth can be shared among the members of the cluster thanks to the networking. Such spacecraft can serve as a cost effective, highly adaptable, and fault tolerant platform for running various distributed mission software applications that collect, process, and downlink data. Naturally, a key component in such a system is the software platform: the distributed operating system and software infrastructure that makes such applications possible. Existing operating systems are insufficient, and newer technologies like component frameworks do not address all the requirements of such flexible space architectures. The high degree of flexibility and the need for thorough planning and analysis of the resource management necessitates the use of advanced development techniques. This paper describes the core principles and design of a software component framework for fractionated spacecraft that is a special case of a distributed real-time embedded system. Additionally we describe how a model-driven development environment helps with the design and engineering of complex applications for this platform.
Authored by Abhishek Dubey, Aniruddha Gokhale, Gabor Karsai, William Otte, Daniel Balasubramanian, Sandor Nyako, and Johnny Willemsen
Authored by Gabor Simko, David Lindecker, Tihamer Levendovszky, Ethan Jackson, Sandeep Neema, and Janos Sztipanovits
Authored by William Otte, Abhishek Dubey, Subhav Pradhan, PrithviRaj Patil, Aniruddha Gokhale, Gabor Karsai, and Johnny Willemsen
Authored by William Emfinger, Pranav Kumar, Abhishek Dubey, William Otte, Aniruddha Gokhale, and Gabor Karsai
Authored by Nagabhushan Mahadevan, Abhishek Dubey, Daniel Balasubramanian, and Gabor Karsai
Authored by Daniel Balasubramanian, William Emfinger, Pranav Kumar, William Otte, Abhishek Dubey, and Gabor Karsai
Authored by Benjamin Babjak, Sandor Szilvasi, Peter Volgyesi, Ozgur Yapar, and Prodyot Basu
The systematic design of automotive control applications is a challenging problem due to lack of understanding of the complex and tight interactions that often manifest during the integration of components from the control design phase with the components from software generation and deployment on actual platform/network. In order to address this challenge, we present a systematic methodology and a toolchain using well-defined models to integrate components from various design phases with specific emphasis on restricting the complex interactions that manifest during integration such as timing, deployment, and quantization. We present an experimental platform for the evaluation and testing of the design process. The approach is applied to the development of an adaptive cruise control, and we present experimental results that demonstrate the efficacy of the approach.
Authored by Emeka Eyisi, Zhenkai Zhang, Xenofon Koutsoukos, Joseph Porter, Gabor Karsai, and Janos Sztipanovits
Authored by Nagabhushan Mahadevan, Abhishek Dubey, Daniel Balasubramanian, and Gabor Karsai
Designing cyber-physical systems (CPS) is challenging due to the tight interactions between software, network/platform, and physical components. A co-simulation method is valuable to enable early system evaluation. In this paper, a co-simulation framework that considers interacting CPS components for design of time-triggered (TT) CPS is proposed. Virtual prototyping of CPS is the core of the proposed framework. A network/platform model in SystemC forms the backbone of the virtual prototyping, which bridges control software and physical environment. The network/platform model consists of processing elements abstracted by realtime operating systems, communication systems, sensors, and actuators. The framework is also integrated with a model-based design tool to enable rapid prototyping. The framework is validated by comparing simulation results with the results from a hardware-in-the-loop automotive simulator.
Authored by Zhenkai Zhang, Emeka Eyisi, Xenofon Koutsoukos, Joseph Porter, Gabor Karsai, and Janos Sztipanovits
Authored by Janos Sallai, Peter Volgyesi, Akos Ledeczi, Ken Pence, Ted Bapty, Sandeep Neema, and James Davis
The vision of is that it becomes an open repository for privacy policies at local, state and national level; provides collaboration services for discussing, interpreting, and tracking policies; and by embedding formal policy models with relevant ontologies, it provides a wide range of services for authoring, composing, analyzing policy models, and for exporting executable
Authored by Andras Nadas, Laszlo Juracz, Janos Sztipanovits, Mark Frisse, and Ann Olsen
Authored by Joshua Carl, Zsolt Lattmann, and Gautam Biswas
Authored by Kyoungho An, Sumant Tambe, Andrea Sorbini, Sheeladitya Mukherjee, Javier Povedano-Molina, Michael Walker, Nirjhar Vermani, Aniruddha Gokhale, and Paul Pazandak