Sharif Digital Repository

Controlling networked structures has many applications in science and engineering. In this paper, we consider the problem of pinning control (pinning the dynamics into the reference state), and optimally placing the driver nodes, i.e., the nodes to which the control signal is fed. Considering the local controllability concept, a metric based on the eigenvalues of the Laplacian matrix is taken into account as a measure of controllability. We show that the proposed optimal placement strategy considerably outperforms heuristic methods including choosing hub nodes with high degree or betweenness centrality as drivers. We also study properties of optimal drivers in terms of various centrality... 

In the past few years, the study of complex networks has attracted the attention of researchers. Many real networks, ranging from technological networks such as the Internet to biological networks, have been considered as special types of complex networks. Through application of the network science, important structural properties of such networks have been analyzed and the mechanisms that form such characteristics have been introduced. In this paper, we address the structural characteristics of a technological network called Vehicular Ad hoc Networks (VANETs). Recent studies reveal that the communication graph of VANETs has some interesting characteristics including: the Gaussian degree... 

We address the performance of the 802.11p protocol in terms of the packet delivery ratio (PDR) and the packet reception ratio (PRR) for broadcasting safety messages in highway environments. Regarding the semi-sparse and intermediate traffic, we try to answer to questions such as what are the upper, dominant and lower bounds of PDR and PRR in each traffic condition? How they may deviate from their average values? and What fraction of vehicles may experience such bounds? To answer to such questions, we propose to consider the communication graph formed among vehicles as a special type of the complex networks and we apply the recently proposed obligatory attachment ruleto synthesize such... 

Molecular dynamics (MD) simulations have been widely used to study the structure of metallic glasses (MGs) at atomic scale. However, ultrafast cooling rates in MD simulations create structures that are substantially under-relaxed. In this study, we introduce long-term pressurized annealing up to 1 μs slightly below the glass-transition temperature, Tg, in MD simulation, which effectively relaxes the structure of Cu64Zr36 MG toward experimental conditions. It is found that applying hydrostatic pressure up to 2 GPa relaxes the MG to low-energy states whereas higher pressures retard relaxation events. In the sample annealed at 2 GPa pressure, equivalent cooling rate reaches to 3.7 × 107 K/s,... 

This letter presents a complex network model for the BitTorrent; the most popular peer-to-peer network. Three important topological characteristics; (i) degree distribution, (ii) clustering coefficient and (iii) average path length of this network are analytically modeled. The analytical computations are confirmed by simulations. Moreover, the accuracy of the proposed model was confirmed by exploiting a BitTorrent simulator  

Observability of complex systems/networks is the focus of this paper, which is shown to be closely related to the concept of contraction. Indeed, for observable network tracking it is necessary/sufficient to have one node in each contraction measured. Therefore, nodes in a contraction are equivalent to recover for loss of observability, implying that contraction size is a key factor for observability recovery. Here, developing a polynomial order contraction detection algorithm, we analyze the distribution of contractions, studying its relation with key network properties. Our results show that contraction size is related to network clustering coefficient and degree heterogeneity.... 

Observability of complex systems/networks is the focus of this paper, which is shown to be closely related to the concept of contraction. Indeed, for observable network tracking it is necessary/sufficient to have one node in each contraction measured. Therefore, nodes in a contraction are equivalent to recover for loss of observability, implying that contraction size is a key factor for observability recovery. Here, using a polynomial order contraction detection algorithm, we analyze the distribution of contractions, studying its relation with key network properties. Our results show that contraction size is related to network clustering coefficient and degree heterogeneity. Particularly, in... 

Recent progress in the areas of network science and control has shown a significant promise in understanding and analyzing epidemic processes. A well-known model to study epidemics processes used by both control and epidemiological research communities is the susceptible–infected–susceptible (SIS) dynamics to model the spread of disease/viruses over contact networks of infected and susceptible individuals. The SIS model has two metastable equilibria: one is called the endemic equilibrium and the other is known as the disease-free or healthy-state equilibrium. Control theory provides the tools to design control actions (allocating curing or vaccination resources) in order to achieve and... 

In this paper, we study large-scale networks in terms of observability and controllability. In particular, we compare the number of unmatched nodes in two main types of Scale-Free (SF) networks: the Barabási-Albert (BA) model and the Holme-Kim (HK) model. Comparing the two models based on theory and simulation, we discuss the possible relation between clustering coefficient and the number of unmatched nodes. In this direction, we propose a new algorithm to reduce the number of unmatched nodes via link addition. The results are significant as one can reduce the number of unmatched nodes and therefore number of embedded sensors/actuators in, for example, an IoT network. This may significantly... 

In this letter, we study large-scale networks in terms of observability and controllability. In particular, we compare the number of unmatched nodes in two main types of Scale-Free (SF) networks: the Barabási-Albert (BA) model and the Holme-Kim (HK) model. Comparing the two models based on theory and simulation, we discuss the possible relation between clustering coefficient and the number of unmatched nodes. In this direction, we propose a new algorithm to reduce the number of unmatched nodes via link addition. The results are significant as one can reduce the number of unmatched nodes and therefore number of embedded sensors/actuators in, for example, an IoT network. This may significantly... 

Observability and estimation are closely tied to the system structure, which can be visualized as a system graph-a graph that captures the inter-dependencies within the state variables. For example, in social system graphs such inter-dependencies represent the social interactions of different individuals. It was recently shown that contractions, a key concept from graph theory, in the system graph are critical to system observability, as (at least) one state measurement in every contraction is necessary for observability. Thus, the size and number of contractions are critical in recovering for loss of observability. In this paper, the correlation between the average-size/number of... 

The rapid development of scientific fields in this modern era has raised the concern for prospective scholars to find a proper research field to conduct their future studies. Thus, having a vision of future could be helpful to pick the right path for doing research and ensuring that it is worth investing in. In this study, we use article keywords of computer science journals and conferences, assigned by INSPEC controlled indexing, to construct a temporal scientific knowledge network. By observing keyword networks snapshots over time, we can utilize the link prediction methods to foresee the future structures of these networks. We use two different approaches for this link prediction problem.... 

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a...