44,667 research outputs found
Optimal redundancy against disjoint vulnerabilities in networks
Redundancy is commonly used to guarantee continued functionality in networked
systems. However, often many nodes are vulnerable to the same failure or
adversary. A "backup" path is not sufficient if both paths depend on nodes
which share a vulnerability.For example, if two nodes of the Internet cannot be
connected without using routers belonging to a given untrusted entity, then all
of their communication-regardless of the specific paths utilized-will be
intercepted by the controlling entity.In this and many other cases, the
vulnerabilities affecting the network are disjoint: each node has exactly one
vulnerability but the same vulnerability can affect many nodes. To discover
optimal redundancy in this scenario, we describe each vulnerability as a color
and develop a "color-avoiding percolation" which uncovers a hidden
color-avoiding connectivity. We present algorithms for color-avoiding
percolation of general networks and an analytic theory for random graphs with
uniformly distributed colors including critical phenomena. We demonstrate our
theory by uncovering the hidden color-avoiding connectivity of the Internet. We
find that less well-connected countries are more likely able to communicate
securely through optimally redundant paths than highly connected countries like
the US. Our results reveal a new layer of hidden structure in complex systems
and can enhance security and robustness through optimal redundancy in a wide
range of systems including biological, economic and communications networks.Comment: 15 page
Robustness and evolution: concepts, insights and challenges from a developmental model system.
International audienceRobustness, the persistence of an organismal trait under perturbations, is a ubiquitous property of complex living systems. We here discuss key concepts related to robustness with examples from vulva development in the nematode Caenorhabditis elegans. We emphasize the need to be clear about the perturbations a trait is (or is not) robust to. We discuss two prominent mechanistic causes of robustness, namely redundancy and distributed robustness. We also discuss possible evolutionary causes of robustness, one of which does not involve natural selection. To better understand robustness is of paramount importance for understanding organismal evolution. Part of the reason is that highly robust systems can accumulate cryptic variation that can serve as a source of new adaptations and evolutionary innovations. We point to some key challenges in improving our understanding of robustness.Heredity advance online publication, 13 December 2006; doi:10.1038/sj.hdy.6800915
Degenerate neutrality creates evolvable fitness landscapes
Understanding how systems can be designed to be evolvable is fundamental to
research in optimization, evolution, and complex systems science. Many
researchers have thus recognized the importance of evolvability, i.e. the
ability to find new variants of higher fitness, in the fields of biological
evolution and evolutionary computation. Recent studies by Ciliberti et al
(Proc. Nat. Acad. Sci., 2007) and Wagner (Proc. R. Soc. B., 2008) propose a
potentially important link between the robustness and the evolvability of a
system. In particular, it has been suggested that robustness may actually lead
to the emergence of evolvability. Here we study two design principles,
redundancy and degeneracy, for achieving robustness and we show that they have
a dramatically different impact on the evolvability of the system. In
particular, purely redundant systems are found to have very little evolvability
while systems with degeneracy, i.e. distributed robustness, can be orders of
magnitude more evolvable. These results offer insights into the general
principles for achieving evolvability and may prove to be an important step
forward in the pursuit of evolvable representations in evolutionary
computation
Robustness and evolution: concepts, insights and challenges from a developmental model system
Robustness, the persistence of an organismal trait under perturbations, is a ubiquitous property of complex living systems. We here discuss key concepts related to robustness with examples from vulva development in the nematode Caenorhabditis elegans. We emphasize the need to be clear about the perturbations a trait is (or is not) robust to. We discuss two prominent mechanistic causes of robustness, namely redundancy and distributed robustness. We also discuss possible evolutionary causes of robustness, one of which does not involve natural selection. To better understand robustness is of paramount importance for understanding organismal evolution. Part of the reason is that highly robust systems can accumulate cryptic variation that can serve as a source of new adaptations and evolutionary innovations. We point to some key challenges in improving our understanding of robustness
Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems
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
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Degeneracy: a design principle for achieving robustness and evolvability
Robustness, the insensitivity of some of a biological system's
functionalities to a set of distinct conditions, is intimately linked to
fitness. Recent studies suggest that it may also play a vital role in enabling
the evolution of species. Increasing robustness, so is proposed, can lead to
the emergence of evolvability if evolution proceeds over a neutral network that
extends far throughout the fitness landscape. Here, we show that the design
principles used to achieve robustness dramatically influence whether robustness
leads to evolvability. In simulation experiments, we find that purely redundant
systems have remarkably low evolvability while degenerate, i.e. partially
redundant, systems tend to be orders of magnitude more evolvable. Surprisingly,
the magnitude of observed variation in evolvability can neither be explained by
differences in the size nor the topology of the neutral networks. This suggests
that degeneracy, a ubiquitous characteristic in biological systems, may be an
important enabler of natural evolution. More generally, our study provides
valuable new clues about the origin of innovations in complex adaptive systems.Comment: Accepted in the Journal of Theoretical Biology (Nov 2009
Degeneracy: a link between evolvability, robustness and complexity in biological systems
A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology.
This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability
Structural Vulnerability Analysis of Electric Power Distribution Grids
Power grid outages cause huge economical and societal costs. Disruptions in
the power distribution grid are responsible for a significant fraction of
electric power unavailability to customers. The impact of extreme weather
conditions, continuously increasing demand, and the over-ageing of assets in
the grid, deteriorates the safety of electric power delivery in the near
future. It is this dependence on electric power that necessitates further
research in the power distribution grid security assessment. Thus measures to
analyze the robustness characteristics and to identify vulnerabilities as they
exist in the grid are of utmost importance. This research investigates exactly
those concepts- the vulnerability and robustness of power distribution grids
from a topological point of view, and proposes a metric to quantify them with
respect to assets in a distribution grid. Real-world data is used to
demonstrate the applicability of the proposed metric as a tool to assess the
criticality of assets in a distribution grid
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