Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2017.0662

Scale invariance in natural and artificial collective systems : a review

In this paper, we present a novel local-world model of wireless sensor networks (WSN) with two kinds of nodes: sensor nodes and sink nodes, which is different from other models with identical nodes and links. The model balances energy consumption by limiting the connectivity of sink nodes to prolong the life of the network. How the proportion of sink nodes, different energy distribution and the local-world scale would affect the topological structure and network performance are investigated. We find that, using mean-field theory, the degree distribution is obtained as an integral with respect to the proportion of sink nodes and energy distribution. We also show that, the model exhibits a mixed connectivity correlation which is greatly distinct from general networks. Moreover, from the perspective of the efficiency and the average hops for data processing, we find some suitable range of the proportion p of sink nodes would make the network model have optimal performance for data processing.

A local-world heterogeneous model of wireless sensor networks with node and link diversity

We propose an energy-aware dynamic routing strategy in order to provide balanced energy consumption in wireless sensor networks, hence, prolonging the lifetime of the network. The proposed routing algorithm uses local betweenness centrality to estimate the energy consumption of the neighboring nodes around a given local sensor node, without requiring global information about the network topology or energy consumption, and to divert traffic from nodes that are more heavily used. Because nodes with large local betweenness centrality consume energy more quickly, the network lifetime can be prolonged by redistributing energy consumption to nodes with smaller local betweenness centrality. Simulation results showed that the proposed routing strategy has advantages over shortest path routing with respect to extending network lifetime and balancing energy consumption in wireless sensor networks, yet does not introduce significant additional transmission overhead or a longer average path length.

https://journals.sagepub.com/doi/pdf/10.1155/2013/307038

Energy-Aware Routing in Wireless Sensor Networks Using Local Betweenness Centrality

Neighborhood area networks (NANs) are critical infrastructure in smart grid to support communications. With the development of wireless communication technologies, there is a great potential for large-scale wireless-mesh NANs to be deployed to smart grid systems. While there exist theoretical models of complex networks, they are not directly applicable in the generation of network topology for wireless-mesh NANs due to their lack of some specifications unique in smart grid, leading to difficulties in theoretical studies of smart grid NANs. Among various topological structures, scale-free networks are considered as a potential resolution. This paper proposes a systematic approach to generate scale-free topology of wireless-mesh NANs in smart grid. A theoretical analysis confirms the scale-free feature of the network topology generated from the approach. To reveal the characteristics of our approach in comparison with widely used models of general complex networks, simulations are conducted on various network parameters including network diameter, average path length, clustering coefficient, and fractal dimension. The simulation results show that our approach for generating wireless-mesh NAN topology is fundamentally different from these compared models, and thus is a new type of complex-network model. Specifically, our model is suitable for wireless-mesh NANs in smart grid.

/pdf/generating-scale-free-topology-for-wireless-neighborhood-5fu9z4h22h.pdf

Generating Scale-Free Topology for Wireless Neighborhood Area Networks in Smart Grid

We discuss the role and importance of dynamics in the brain and biological neural networks, and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

/pdf/nonlinear-dynamics-based-digital-logic-and-circuits-1hda1cpp1h.pdf

Nonlinear dynamics based digital logic and circuits

Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

Complex networks-based energy-efficient evolution model for wireless sensor networks

This paper explores piecewise-linear systems to construct dynamic logic architecture. We present three schemes to obtain various basic logic gates, adders, and memory by using piecewise-linear systems. These schemes can switch easily among different operational roles by changing parameters. The proposed schemes are computationally efficient and easy to use. It is convenient for us to study and analyze them with the theory of linear systems.

Hong Luo

Papers

Complex networks-based energy-efficient evolution model for wireless sensor networks

Harnessing piecewise-linear systems to construct dynamic logic architecture.

On the design of stable, consistent, and conservative high-order methods for multi-material hydrodynamics