Kia Dalili

Emergence of Modularity in System of Systems: Complex Networks in Heterogeneous Environments

Effective use of modularity in distributed systems is key to accommodating the complexity arising from having diverse requirements and stakeholders and increased environmental uncertainties. Moreover, modularity facilitates efficient dynamic resource allocation in the system. In this paper, a formal framework that links various classes of systems modularity to distributed decision complexities is presented by formulating modularity as an emergent phenomenon arising from environmental heterogeneity. This paper also demonstrates behavioral and mathematical formulations of the problem and agent-based simulation of sample networked systems to verify the results.

Optimal Modularity for Fractionated Spacecraft: The Case of System F6

Abstract In recent years, distributed and networked architecture has been suggested as a new approach to manage uncertainty, accommodate multiple stakeholders and increase scalability and evolvablity in spacecraft systems. This departure from monolithic rigid architectures provides the space systems with more flexibility and robustness in response to uncertainties that the system confronts during its lifetime. Distributed architecture, however, does not come with only advantages and can increase cost and complexity of the system and result in potential instabilities and undesired emergent behaviors. In this paper, we build a model using a configuration based on a simplified variation of System F6 architecture that is being developed as a part of a DARPA program on fractionated spacecraft. Using a modularity/fractionation decision framework, developed in our group, we calculate the net value that is gained (or lost) by moving from a monolithic to a fractionated architecture and show how the sign and magnitude of this value change as a function of uncertainties in the environment and various system parameters.

From Modular to Distributed Open Architectures: A Unified Decision Framework

This paper introduces a conceptual, yet quantifiable, architecture framework by extending the notion of system modularity in its broadest sense. Acknowledging that modularity is not a binary feature and comes in various types and levels, the proposed framework introduces higher levels of modularity that naturally incorporate decentralized architecture on the one hand and autonomy in agents and subsystems on the other. This makes the framework suitable for modularity decisions in Systems of Systems and for analyzing the impact of modularity on broader surrounding ecosystems. The stages of modularity in the proposed framework are naturally aligned with the level of variations and uncertainty in the system and its environment, a relationship that is central to the benefits of modularity. The conceptual framework is complemented with a decision layer that makes it suitable to be used as a computational architecture decision tool to determine the appropriate stage and level of modularity of a system, for a given profile of variations and uncertainties in its environment. We further argue that the fundamental systemic driving forces and trade-offs of moving from monolithic to distributed architecture are essentially similar to those for moving from integral to modular architectures. The spectrum, in conjunction with the decision layer, could guide system architects when selecting appropriate parameters and building a system-specific computational tool from a combination of existing tools and techniques. To demonstrate the applicability of the framework, a case for fractionated satellite systems based on a simplified demo of the DARPA F6 program is presented where the value of transition from a monolithic architecture to a fractionated architecture, as two consecutive levels of modularity in the proposed spectrum, is calculated and ranges of parameters where fractionation increases systems value are determined.

Optimal System's Complexity, An Architecture Perspective

Abstract Systems Complexity is driven by more connectivity among constituents and increased environmental uncertainties. Modularity is a systems mechanism to manage complexity in the presence of environmental heterogeneities. Here, a general design decision framework for modularity and fractionation in complex systems is presented. This framework incorporates spatial and temporal heterogeneity of the environment, adaptability of the system and costs associated with modularity. It is argued that as the space-time heterogeneity of the environment increases, higher levels of modularity are needed. To determine the optimal level of complexity in a modular design, a four-level modularity pyramid is introduced. This pyramid takes into account functional and physical dimensions of modularity and allows for resource sharing to enables dynamic modularity. Moving up from each level is quantified by an M+ operation that calculates the net value of increased modularity for each sub-system.

Distributed or Monolithic? A Computational Architecture Decision Framework

Distributed architectures have become ubiquitous in many complex technical and socio-technical systems because of their role in improving uncertainty management, accommodating multiple stakeholders, and increasing scalability and evolvability. This departure from monolithic architectures provides a system with more flexibility and robustness in response to uncertainties that it may confront during its lifetime. Distributed architecture does not provide benefits only, as it can increase cost and complexity of the system and result in potential instabilities. The mechanisms behind this tradeoff, however, are analogous to those of the widely-studied transition from integrated to modular architectures. In this paper, we use a conceptual decision framework that unifies modularity and distributed architecture on a five-stage systems architecture spectrum. We add an extensive computational layer to the framework and explain how this can enhance decision making about the level of modularity of the architecture. We then apply it to a simplified demonstration of the Defense Advanced Research Projects Agency (DARPA) fractionated satellite program. Through simulation, we calculate the net value that is gained (or lost) by migrating from a monolithic architecture to a distributed architecture and show how this value changes as a function of uncertainties in the environment and various system parameters. Additionally, we use value at risk as a measure for the risk of losing the value of distributed architecture, given its inherent uncertainty.

Dynamic modularity: A distributed decision mechanism in system of systems

Effective use of modularity in distributed systems is a key to accommodate complexity arising from having multiple stakeholder requirements and increased environmental uncertainties and facilitates efficient dynamic resource allocation of the system. In this paper, a formal framework that links various classes of systems modularity to distributed decision complexities is presented by formulating modularity as an emergent phenomenon rising from environmental heterogeneity. The work also demonstrates behavioral and mathematical formulation of the problem as well as agent-based simulation of sample networked systems to verify the results.