Delay-independent asymptotic stability in monotone systems

Monotone systems comprise an important class of dynamical systems that are of interest both for their wide applicability and because of their interesting mathematical properties. It is known that under the property of quasimono-tonicity time-delayed systems become monotone, and some remarkable properties have been reported for such systems. These include, for example, the fact that for linear systems global asymptotic stability of the undelayed system implies global asymptotic stability for the delayed system under arbitrary bounded delays. Nevertheless, extensions to nonlinear systems have thus far relied on various restrictive conditions, such as homogeneity and subhomogeneity, and it has been conjectured that these can be relaxed. Our aim in this paper is to show that this is feasible for a general class of nonlinear monotone systems, by deriving asymptotic stability results in which simple properties of the undelayed system lead to delay-independent stability. In particular, one of our results is to show that if the undelayed system has a convergent trajectory that is unbounded in all components as t → -∞ then the system is globally asymptotically stable for arbitrary time-varying delays. This follows from a more general result derived in the paper where delay-independent regions of attraction are quantified from the asymptotic behavior of individual trajectories of the undelayed system. This result recovers various known delay-independent stability results, and several examples are included in the paper to illustrate the significance of the proposed stability conditions.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ACC.2015.717206

Received Signal Strength for Randomly Distributed Molecular Nanonodes

We consider nanonodes randomly distributed in a circular area and characterize the received signal strength when a pair of these nodes employ molecular communication. Two communication methods are investigated, namely free diffusion and diffusion with drift. Since the nodes are randomly distributed, the distance between them can be represented as a random variable, which results in a stochastic process representation of the received signal strength. We derive the probability density function of this process for both molecular communication methods. Specifically for the case of free diffusion we also derive the cumulative distribution function, which can be used to derive transmission success probabilities. The presented work constitutes a first step towards the characterization of the signal to noise ratio in the considered setting for a number of molecular communication methods.Comment: 6 pages, 6 figures, Nanocom 2017 conferenc

CBDI: Combined Banzhaf & Diversity Index for Finding Critical Nodes

Critical node discovery plays a vital role in assessing the vulnerability of a network to an abrupt change, such as an adversarial attack or human intervention. In this paper, we propose a new metric to characterize the criticality of a node in an arbitrary network which we refer to as the Combined Banzhaf & Diversity Index (CBDI). The metric utilizes a diversity index which is based on the variability of a node’s attributes relative to its neighbors and the Banzhaf Power Index which characterizes the degree of participation of a node in forming shortest paths. The Banzhaf power index is inspired from the theory of voting games in game theory. We evaluate the performance of the new metric using simulations. Our results indicate that in a number of network topologies, the proposed metric outperforms other proposals which have appeared in the literature. The proposed CBDI index chooses more critical nodes which, when removed, degrade network performance to a greater extent than if critical nodes based on other criticality metrics were removed

Power system stability enhancement through the optimal, passivity-based, placement of SVCs

Over the last decades, several techniques have been proposed for the optimal placement of FACTS devices across power systems. Although these techniques were shown to improve \il{power system} operation, they are usually computationally intractable while having serious inherent limitations. In this paper, we present a novel approach to guide the SVC location identification in order to enhance power system stability. Specifically, the proposed method exploits findings in passivity-based control analysis and design in order to address the most vulnerable -in terms of passivity- buses of the system and consequently the optimal locations for SVC installation. We then show how the incorporation of SVCs at the aforementioned buses can passivate the system and provide \il{guarantees} for increased stability. Furthermore, we provide a brief discussion regarding the sizing and the number of required SVC devices in order to guarantee such stability improvement. Finally, we illustrate our results with simulations on the IEEE 68 bus system and show that both the dynamic response and the damping of the system are significantly improved

Increasing user controllability on device specific privacy in the Internet of Things

With recent advancements in information technology more and more devices are integrated in the Internet of Things. These devices gather significant amount of private information pertinent to a user and while, in some cases it helps in improving the life style of an individual, in others it raises major privacy concerns. This trade-off between utility and privacy is highly dependent upon the devices in consideration and as the utility of the generated data increases, the privacy of an individual decreases. In this paper, we formulate a utility-privacy trade-off that enables a user to make appliance specific decisions as to how much data can be shared. This is achieved by parametrizing the degree of privacy allowed for each device and enabling the user to configure the parameter of each device. We use the smart metering application as the test case scenario for the proposed approach. We evaluate its performance using simulations conducted on the ECO data set. Our results indicate that, the proposed approach is successful in identifying appliances with an accuracy of 81.8% and a precision of 70.1%. In addition, it is demonstrated that device specific changes of the configuration parameters allow the degree of privacy achieved for the particular device and the utility to be well controlled, thus demonstrating the effectiveness of the proposed approach. Moreover, it is shown that, as expected, devices with higher power consumption contribute more to the overall privacy and utility achieved. A comparative study is also conducted and the proposed approach is shown to outperform the existing ElecPrivacy approach by producing a trace that is harder to identify, as reported after testing the Weiss’ and Baranski’s algorithm, both of which are well known Non-Intrusive Load Monitoring algorithms. Finally, it is demonstrated that the addition of noise, which is an integral part of the propose approach, can greatly improve performance

Spectral Partitioning for Node Criticality

Finding critical nodes in a network is a significant task, highly relevant to network vulnerability and security. We consider the node criticality problem as an algebraic connectivity minimization problem where the objective is to choose nodes which minimize the algebraic connectivity of the resulting network. Previous suboptimal solutions of the problem suffer from the computational complexity associated with the implementation of a maximization consensus algorithm. In this work, we use spectral partitioning concepts introduced by Fiedler, to propose a new suboptimal solution which significantly reduces the implementation complexity. Our approach, combined with recently proposed distributed Fiedler vector calculation algorithms enable each node to decide by itself whether it is a critical node. If a single node is required then the maximization algorithm is applied on a restricted set of nodes within the network. We derive a lower bound for the achievable algebraic connectivity when nodes are removed from the network and we show through simulations that our approach leads to algebraic connectivity values close to this lower bound. Similar behaviour is exhibited by other approaches at the expense, however, of a higher implementation complexity

Combined Banzhaf & Diversity Index (CBDI) for critical node detection

Critical node discovery plays a vital role in assessing the vulnerability of a computer network to malicious attacks and failures and provides a useful tool with which one can greatly improve network security and reliability. In this paper, we propose a new metric to characterize the criticality of a node in an arbitrary computer network which we refer to as the Combined Banzhaf & Diversity Index (CBDI). The metric utilizes a diversity index which is based on the variability of a node׳s attributes relative to its neighbours and the Banzhaf power index which characterizes the degree of participation of a node in forming shortest paths. The Banzhaf power index is inspired from the theory of voting games in game theory. The proposed metric is evaluated using analysis and simulations. The criticality of nodes in a network is assessed based on the degradation in network performance achieved when these nodes are removed. We use several performance metrics to evaluate network performance including the algebraic connectivity which is a spectral metric characterizing the connectivity robustness of the network. Extensive simulations in a number of network topologies indicate that the proposed CBDI index chooses more critical nodes which, when removed, degrade network performance to a greater extent than if critical nodes based on other criticality metrics were removed

Nodal dynamics, not degree distributions, determine the structural controllability of complex networks

Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set (PDS), is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.Comment: 1 Figures, 6 page