1,656 research outputs found

    Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

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    A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u

    Contrasting Views of Complexity and Their Implications For Network-Centric Infrastructures

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    There exists a widely recognized need to better understand and manage complex “systems of systems,” ranging from biology, ecology, and medicine to network-centric technologies. This is motivating the search for universal laws of highly evolved systems and driving demand for new mathematics and methods that are consistent, integrative, and predictive. However, the theoretical frameworks available today are not merely fragmented but sometimes contradictory and incompatible. We argue that complexity arises in highly evolved biological and technological systems primarily to provide mechanisms to create robustness. However, this complexity itself can be a source of new fragility, leading to “robust yet fragile” tradeoffs in system design. We focus on the role of robustness and architecture in networked infrastructures, and we highlight recent advances in the theory of distributed control driven by network technologies. This view of complexity in highly organized technological and biological systems is fundamentally different from the dominant perspective in the mainstream sciences, which downplays function, constraints, and tradeoffs, and tends to minimize the role of organization and design

    Lost generation: Reflections on resilience and flexibility from an energy system architecture perspective

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    Whole energy system modelling is a valuable tool to support the development of policy to decarbonise energy systems, and has been used extensively in the UK for this purpose. However, quantitative insights produced by such models necessarily omit potentially important features of physical and engineering reality. The authors argue that important socio-technical insights can be gained by studying critical events such as the loss of 2.1 GW generation from the electricity system of Great Britain on 9th August 2019, in conjunction with literature on the behaviour of complex systems. Among these insights is the idea that models of the operation and evolution of energy systems can never be complete. Both system behaviour (operation) and the emergence and evolution of structure in such systems are formally uncomputable. This provides a starting point for a discussion of the need for additional tools, drawn from the System Architecture literature, to support the design and realisation of future, fully-decarbonised systems with high penetrations of renewable energy. Desirable properties of System Architectures, including current and future Energy System Architectures, are discussed. These include resilience and flexibility, for which there is an extensive literature. They also include the properties of comprehensibility, which helps to make complex systems easier to operate, and of evolvability, for which a working definition is offered
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