Cluster 6.1.1:   Modeling for Distributed Systems

Task 6.1.1.1. -- Multi-modeling

We will develop methods for composing distinct models, including those of physical dynamics, control logic, energy, networking behavior, fault models, and computation. Hierarchically heterogeneous model composition will be supported through the development and refinement of abstract semantics and interface theories. Finally, systematic techniques supporting model transformations will be designed to convert models of one type into another.

Task 6.1.1.2. -- Cyberphysical Models

We will develop methods for joint design of computational components, networking, and physical dynamics. Our approach will be to specify executable semantics for discrete events and continuous dynamics

Task 6.1.1.3. -- Fault Models

We propose to incorporate into our modeling framework faults as first-class citizens to allow for fault analysis at multiple levels of abstractions. In our research we will include also models of aircraft energy generation equipment with the related fault models.

Cluster 6.1.2:   Verification

Task 6.1.2.1. -- Robustness and Verification

We will develop the foundations of a modern framework for testing the robustness of distributed control systems.

Task 6.1.2.2. -- Abstraction, Modeling, and Interface Specification

We will develop new automatic abstraction methods for multi-scale distributed systems. Our approach will be to use a combination of algorithmic verification and statistical learning for inferring interface specifications and generating environment models automatically.

Task 6.1.2.3. -- Automated Diagnostics

We will develop algorithmic techniques for detection, isolation and diagnosis of faults in the system. We will develop a hierarchical, model-based approach to diagnosis of distributed control systems.

Task 6.1.2.4. -- Integrated Design and Verification

Cluster 6.1.3:   Distributed Control Algorithms

Task 6.1.3.1. -- Distributed Real Time Control

We will develop methods for orchestrating distributed computer-controlled actions. Our approach will be to use concurrent models of computation with timed semantics, together with distributed and partially-ordered models of time.

Task 6.1.3.2. -- Optimal Distributed Control and Estimation in the Presence of Communication Costs

We will develop on-line algorithms for improving overall sensing performance, while balancing this improvement with the costs of communication in dynamic architectures.

Task 6.1.3.4. -- Taxonomy of structure versus behavior

We will develop a taxonomy of communication architectures that enable high performance in various distributed sense and control functions. We will analyze expander graphs and other graph types. We will develop multi-scale analogs via hierarchies. We will develop dynamic self-organization algorithms for large-scale sense and control networks based on these principles.

Task 6.1.3.5. -- Foundation for the Quantitative Analysis and Design of Control Networks

Cluster 6.1.4:   Security and Trust

Task 6.1.4.1. -- Coalitional Security

We will develop models for security of coalitions that are particularly suited for multi-scale systems. The models will account for members (subsystems) that might participate in several coalitions simultaneously, as well as dynamic coalitions.

Cluster 6.1.5:   Reliable and Robust Distributed Systems Architectures

Task 6.1.5.1. -- Dynamic resource brokerage

We propose to develop a structured software framework that allows various agents (representing resources) to discover availability, share the information with other agents through a hierarchical repository, find the optimal solution given the demand and availability, and configure the system accordingly, all of this in light of the reigning security settings. The resulting architecture will be applied to some of the application drivers of the Center – with energy considered as the most precious resource to be traded.

Task 6.1.5.2. -- Architectural selection

We will develop algorithms and models to select the architecture (e.g., type of objects, number of objects, and their locations) of a distributed system by minimizing an appropriate set of metrics that may include power consumed, monetary costs, reliability, and accuracy. Particular attention will be given to the selection of protocols, physical interconnects including wired and wireless solutions, buffers and gateways for the communication infrastructure.

Cluster 6.1.6:   Avionics Test Bed

Task 6.1.6.1. -- Integrated power management in aircraft

We will apply the methodologies and algorithms, developed in the other tasks, to the power generation and fly-by-wire subsystems in modern aircraft. In particular, the verification and validation problem involving multiple conditions involving distributed architectures for control of more electric aircraft will be addressed by using a combination of complexity management techniques such as abstraction, decomposition and stochastic modeling of uncertain environment behavior.

Task 6.1.6.2. -- Dynamic configuration of aircraft for energy-efficiency

We will explore dynamical reconfiguration and coordination of subsystems using awareness of current and predicted environment, operations and constraints. In current systems, these tradeoffs are largely performed at design time, with sufficient redundancy to provide fault-tolerance. We plan to develop techniques for future systems that will reconfigure their operations in real-time, requiring significantly more sophisticated architectures to insure high confidence, robust operations while at the same time substantially increasing efficiency and operability.