Shiwen Sun

Impact of individual response strategy on the spatial public goods game within mobile agents

The management and deployment of public resources has become an active topic within scientific communities, and attracted the substantial attention from a great number of interdisciplinary researches, including social, natural, biological sciences and economics. Among them, public goods game provides an effectively theoretical framework to deeply understand the evolution of collective cooperation and to solve this challenging problem. In this paper, we investigate the cooperative behaviors among mobile agents which are located on a sparse square lattice and can make an estimate on the current situations for themselves, and we put forward several models considering different mobility rules and strategy update order to further model real scenarios. Large quantities of simulations indicate that strategy update order can obviously change the evolution of collective cooperation, but the mobility rule can play a different role for a specific update order in our models. Current results will be of high relevance to deepen our knowledge on the cooperation mechanisms within realistic and mobile circumstances.

HETEROGENEOUS LINK WEIGHT PROMOTES THE COOPERATION IN SPATIAL PRISONER'S DILEMMA

The spatial structure has often been identified as a prominent mechanism that substantially promotes the cooperation level in prisoners dilemma game. In this paper we introduce a weighting mechanism into the spatial prisoners dilemma game to explore the cooperative behaviors on the square lattice. Here, three types of weight distributions: exponential, power-law and uniform distributions are considered, and the weight is assigned to links between players. Through large-scale numerical simulations we find, compared with the traditional spatial game, that this mechanism can largely enhance the frequency of cooperators. For most ranges of b, we find that the power-law distribution enables the highest promotion of cooperation and the uniform one leads to the lowest enhancement, whereas the exponential one lies often between them. The great improvement of cooperation can be caused by the fact that the distributional link weight yields inhomogeneous interaction strength among individuals, which can facilitate the formation of cooperative clusters to resist the defectors invasion. In addition, the impact of amplitude of the undulation of weight distribution and noise strength on cooperation is also investigated for three kinds of weight distribution. Current researches can aid in the further understanding of evolutionary cooperation in biological and social science.

Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices

A spatial PGG model on interdependent networks is proposed.The reputation value is commonly determined by two corresponding partners.Three different reputation governing rules are proposed.The introduction of reputation greatly promotes the evolution of cooperation.The higher the reputation referring probability, the higher the cooperation level. In this paper, we mainly probe into the evolution of cooperation in the spatial public goods game on interdependent lattices by introducing the reputation inferring mechanism into the strategy selection. During the strategy update, the individual reputation is commonly determined by two corresponding partners on interdependent lattices, where the imitated neighbors are chosen in accordance with the average, maximum and minimum of reputation values between two partners within the neighborhood of a focal player. A large plethora of simulations indicate that three reputation computing rules all lead to the promotion of cooperation when compared to the traditional public goods game model. Among them, the promotion of cooperation under the average and minimum schemes are relatively better than that produced by the maximum rule. The detailed cluster formation and reputation distribution are provided to illustrate the slight difference between the outcomes under these three decision making criterions, in which the choice of learning objects is governed by their reputations. Thus, we can conclude that current results are further conducive to understanding the universal and persuasive cooperation within many natural, biological, social and even man-made systems.

Impact of Degree Heterogeneity on Attack Vulnerability of Interdependent Networks

The study of interdependent networks has become a new research focus in recent years. We focus on one fundamental property of interdependent networks: vulnerability. Previous studies mainly focused on the impact of topological properties upon interdependent networks under random attacks, the effect of degree heterogeneity on structural vulnerability of interdependent networks under intentional attacks, however, is still unexplored. In order to deeply understand the role of degree distribution and in particular degree heterogeneity, we construct an interdependent system model which consists of two networks whose extent of degree heterogeneity can be controlled simultaneously by a tuning parameter. Meanwhile, a new quantity, which can better measure the performance of interdependent networks after attack, is proposed. Numerical simulation results demonstrate that degree heterogeneity can significantly increase the vulnerability of both single and interdependent networks. Moreover, it is found that interdependent links between two networks make the entire system much more fragile to attacks. Enhancing coupling strength between networks can greatly increase the fragility of both networks against targeted attacks, which is most evident under the case of max-max assortative coupling. Current results can help to deepen the understanding of structural complexity of complex real-world systems.

On Structural Properties of Large-Scale Software Systems: From the Perspective of Complex Networks

From the viewpoint of network, large-scale computer software system scan be regarded as complex networks composed of interacting units at different levels of granularity (such as functions, classes, packages, source files, etc.). In this paper, the collaboration relationships between header files in the source node of Linux kernels, which are representative examples of large-scaleopen-source software systems, are analyzed by constructing weighted network-Header File Collaboration Network (HFCN). Through using appropriate non-weighted and weighted quantities, the complex structural properties, the weight distribution and the impact between them of these networks are characterized and analyzed. These results can provide a better description of the organizational principles at the basis of the architecture of source codes in large computer software systems.

Cascading crashes induced by the individual heterogeneity in complex networks

Abstract Deep understanding of the birth, growth and evolution of the real-life systems has been widely investigated, but the dynamics of system crashes are far beyond our knowledge. To this end, we propose a dynamical model to illustrate the collapsing behavior of complex networks, in which each node may leave the current networks since it has too few neighbors or has lost more than a specific proportion of its neighboring links. Different from previous works, the probability of being removed from the network for each node will be correlated with its original degree once the leaving conditions are satisfied, which includes the positive or negative correlation with the original degree, and totally independent probability deployment, and the individual heterogeneity has been integrated into these three probability setup schemes. Plenty of numerical simulations have indicated that the leaving probability setup scheme will greatly impact the system crashing behaviors under three different topologies including random, exponential and scale-free networks. In particular, the positively correlated scheme will substantially improve the survival of systems and further enhance the resilience of scale-free networks. To a great degree, the current results can help us to be further acquainted with the crashing dynamics and evolutionary properties of complex systems.

Structural Controllability of Optimized Networks with Onion-Like Topologies

Recently, an optimization method has been proposed to increase the ability of complex networks to resist intentional attacks on hub nodes. The finally optimized networks exhibit a novel type of “onion-like” structure. At the same time, structural controllability of complex networks also has been a hot research topic in recent years. Thus, structural controllability of “onion-like” networks deserves sufficient discussion. In this study, we explored the relationship between the attack robustness and structural controllability of scale-free networks before and after optimization. After implementing large quantity of numerical simulations, it has been found that the optimized scale-free networks have both increased robustness and enhanced structural controllability. Current research results can shed some light on the deep understanding of structural complexity and dynamical properties of real-world networked systems.

Mining Important Topological Properties in Large-Scale Computer Software Systems Based on Complex Networks

Recently, large-scale computer software systems have attached a great deal of attention when they are regarded as complex networks composed of interacting units. In this paper, the collaboration relationships between header files in the source code of Linux kernels are analyzed by constructing a weighted File Collaboration Network(FCN): each node represents a header file, two nodes are connected if corresponding header files are both included in the same source file at least once, also the link weight is assigned to evaluate the intensity of co inclusion of two header files. Through using appropriate non-weighted and weighted quantities, structural properties of FCNs are characterized and analyzed. The study of large-scale softwares from the viewpoint of complex networks can provide a better description of the organizational principles and evolving mechanism of complex software systems.

Generalized collaboration networks in software systems: a case study of Linux kernels

The collaboration relationships between header files in the source code of Linux kernels are analyzed by constructing a weighted Header File Collaboration Network (HFCN): each node represents a header file; two nodes are connected if corresponding header files are both included in the same source file at least once; also the link weight is assigned to evaluate the intensity of co-inclusion of two header files. Through using appropriate non-weighted and weighted quantities, structural properties of two kinds of HFCN networks(HFCN-I and HFCN-II) are characterized and analyzed. The study of Linux kernels from the viewpoint of complex networks can provide a better description of the organizational principles and evolving mechanism of complex software systems.