The traditions of real-time and embedded system engineering have evolved into a new field of cyber-physical systems (CPSs). The increase in complexity of CPS components and the multi-domain engineering composition of CPSs challenge the current best practices in design and simulation. To address the challenges of CPS simulation, this work introduces a simulator coordination method drawing from strengths of the field of parallel and distributed simulation (PADS), yet offering benefits aimed towards the challenges of coordinating CPS engineering design simulators. The method offers the novel concept of Interpolated Event data types applied to Kahn Process Networks in order to provide simulator coordination. This can enable conservative and optimistic coordination of multiple heterogeneous and homogeneous simulators, but provide important benefits for CPS simulation, such as the opportunity to reduce functional requirements for simulator interfacing compared to existing solutions. The method is analyzed in theoretical properties and instantiated in software tools SimConnect and SimTalk. Finally, an experimental study applies the method and tools to accelerate Spice circuit simulation with tradeoffs in speed versus accuracy, and demonstrates the coordination of three heterogeneous simulators for a CPS simulation with increasing component model refinement and realism. / text

This thesis develops adaptive simulation control techniques that differentiate between competing system configurations. Here, a system is a real world environment under analysis. In this context, proposed modifications to a system denoted by different configurations are evaluated using large-scale hybrid simulation. Adaptive control techniques, using ranking and selection methods, compare the relative worth of competing configurations and use these comparisons to control the number of required simulation observations. Adaptive techniques necessitate embedded statistical computations suitable for the variety of data found in detailed simulations, including hybrid and agent-based simulations. These embedded statistical computations apply efficient sampling methods to collect data from simulations running on a network of workstations. The National Airspace System provides a test case for the application of these techniques to the analysis and design of complex systems, implemented here in the Reconfigurable Flight Simulator, a large-scale hybrid simulation. Implications of these techniques for the use of simulation as a design activity are also presented.

Network emulation has been widely used to aid in the development and evaluation of real-time applications. Many of today s applications and protocols need to be tested and evaluated in large scale network environments such as the Internet, which requires emulation tools that meet the requirements of scale, accuracy, timeliness. Due to physical resource constraints in network emulators, existing emulation tools fail to meet these requirements as they are either limited to small and static networks, use simplified network models, or fail to deliver timely emulation results. If more physical resources are devoted to network emulation by utilizing high performance computing facilities, the accuracy and scalability of network emulation can be greatly improved. However, for many users, high performance computing facilities may not be readily available in a local laboratory environment, and co-locating application code with a remote high performance computing facility may be cumbersome and inconvenient. This thesis proposes a network emulation approach called ROSENET (RemOte SErver-based Network EmulaTion) that utilizes a distributed server-based architecture in which local low-fidelity emulators provide real-time QoS predictions to distributed applications, coupled with a remote large scale high-fidelity simulator that continuously updates and calibrates the local low-fidelity emulators. A library-based modeling approach based on online simulation data collection is proposed and a system identification modeling technique is presented. Experimental results examining emulation end-to-end delay and loss show that ROSENET provides a promising approach to network emulation supporting accuracy and scale while meeting real-time constraints. Challenges faced in applying ROSENET to real world applications are addressed through two case studies including applying synthetic workload on DARPA s NMS network topology for large scale network simulation and a contemporary real-time distributed VoIP application Skype.

In this dissertation, we describe the portable, open-source distributed simulation framework (WINDS) targeting simulations of wireless network infrastructures that we have developed. We present the simulation framework which uses modular architecture and apply the framework to studies of mobility pattern effects, routing and intrusion detection mechanisms in simulations of large-scale wireless ad hoc, infrastructure, and totally mobile networks. The distributed simulations within the framework execute seamlessly and transparently to the user on a symmetric multiprocessor cluster computer or a network of computers with no modifications to the code or user objects. A visual graphical interface precisely depicts simulation object states and interactions throughout the simulation execution, giving the user full control over the simulation in real time. The network configuration is detected by the framework, and communication latency is taken into consideration when dynamically adjusting the simulation clock, allowing the simulation to run on a heterogeneous computing system. The simulation framework is easily extensible to multi-cluster systems and computing grids. An entire simulation system can be constructed in a short time, utilizing user-created and supplied simulation components, including mobile nodes, base stations, routing algorithms, traffic patterns and other objects. These objects are automatically compiled and loaded by the simulation system, and are available for dynamic simulation injection at runtime. Using our distributed simulation framework, we have studied modern intrusion detection systems (IDS) and assessed applicability of existing intrusion detection techniques to wireless networks. We have developed a mobile agent-based IDS targeting mobile wireless networks, and introduced load-balancing optimizations aimed at limited-resource systems to improve intrusion detection performance. Packet-based monitoring agents of our IDS employ a CASE-based reasoner engine that performs fast lookups of network packets in the existing SNORT-based intrusion rule-set. Experiments were performed using the intrusion data from MIT Lincoln Laboratories studies, and executed on a cluster computer utilizing our distributed simulation system.