Variety Of Network Topologies Research Articles

Age-related network topological difference based on the sleep ECG signal

Objective: Age has been shown to be a crucial factor for the EEG and fMRI small-world networks during sleep. However, the characteristics of the age-related network based on the sleep ECG signal and how the network changes during different sleep stages are poorly understood. This study focuses on exploring the age-related scale-free and small-world network properties of the ECG signal from male subjects during distinct sleep stages, including the wakeful (W), light sleep (LS), deep sleep (DS) and rapid eye movement (REM) stages. Approach: The subjects are divided into two age groups: a younger (age ⩽ 40, n = 11) group and an older group (age > 40, n = 25). Main results: For the scale-free network analysis, our results reveal a distinctive pattern of the scale free network topologies between the two age groups, including the mean degree (), the clustering coefficient (), and the path length () features, such as the slope distribution of in the younger group increased from 1.99 during W to above 2.05 during DS. In addition, the results indicate that the small-world properties can be found across all sleep stages in both age groups. However, the small-world index in the LS and REM stages significantly decreased with age (p = 0.0006 and p = 0.05, respectively). Significance: The comparison analysis result indicates that the network topology variations in the sleep ECG signals are prone to show age-relevant differences that could be used for sleep stage classification and sleep disorder diagnosis.

BHQRSM: Binary Hex Quadratic Residue Security Model to Enhance the Trust in MANETs

Mobile adhoc network (MANET) possesses various security challenges mainly due to its varying network topology. As central coordination is not possible in MANETs, sharing of keys between nodes is a difficult task. In this paper, we present a Binary Hex Quadratic Residue Security Model that does not require any kind of key distribution between the nodes in MANETs. We use a stream of equal weighted hex codes of decimal numbers and Ex-OR operations to generate a security vector which facilitates matching of code words and also determine the active and malicious nodes in the network. Our approach also saves energy as it requires less computational analysis when compared to existing approaches. We validate our approach through simulations results.

Branch current decomposition method for loss allocation in contemporary distribution systems

The presence of distributed generation (DG) units in reconfigured distribution systems introduces complexity in loss allocation (LA). DG integration alters feeder power losses so DG owners (DGOs) may be incentivized or penalized accordingly, whereas network reconfiguration alters feeding path of network user’s thus further increases complexity in LA. The LA method should judiciously allocate losses among load points and simultaneously reward DGOs and distribution network operator (DNO) for their contribution towards loss reduction. Moreover, the LA method should take care of the reactive power transactions of network users. This paper proposes a branch current decomposition method (BCDM) based upon circuit theory for allocating losses in active reconfigured distribution system while giving due consideration to reactive power transactions of network users. BCDM considers virtual branch voltage drops which is well supported by analytical treatment. In addition, Superposition is utilized to incentivize/penalize DGOs. A new LA strategy is proposed for fair allocation of loss/loss incentives among network users and DNO. Proposed method is thoroughly investigated under varying loading, load power factors and under varying network topologies. The comparison results obtained on standard test distribution system highlights the importance of proposed method.

Simulating attacker and defender strategies within a dynamic game on network topology

Successful military counterinsurgency operations increasingly rely upon an advanced understanding of relevant networks and their topologies. This paper evaluates, via simulations, various attacker and defender strategies within a dynamic game on network topology. The simulation is designed to provide insight into the effectiveness of offensive targeting strategies as determined by various centrality measures, given limited states of information and varying network topologies. Improved modeling of complex social behaviors is accomplished through incorporation of a distance-based utility function. Moreover, insights into effective defensive strategies are gained through incorporation of a hybrid model of network regeneration. Two designed experiments investigate the impact of game features on the superlative offensive and defensive strategies. Results indicate that degree centrality, proximal target centrality, and closeness centrality outperform other measures as targeting criteria given varying network topologies and defensive regeneration methods. Furthermore, the attacker state of information is only significant given a topology conducive to defense. The costs of direct relationships significantly impact effective regeneration methods, whereas restructuring methods are insignificant. These results offer preliminary insight into practical attack and defense strategies utilizing a simulation that can be easily adapted for operational applications.

Characteristic of the equivalent impedance for an m×n RLC network with an arbitrary boundary

Considerable progress has been made recently in the development of techniques to determine exactly two-point resistances in networks of various topologies. In particular, a general resistance formula of a non-regular m×n resistor network with an arbitrary boundary is determined by the recursion-transform (RT) method. However, research on the complex impedance network is more difficult than that on the resistor network, and it is a problem worthy of study since the equivalent impedance has many different properties from equivalent resistance. In this study, the equivalent impedance of a non-regular m×n RLC network with an arbitrary boundary is studied based on the resistance formula, and the oscillation characteristics and resonance properties of the equivalent impedance are discovered. In the RLC network, it is found that our formula leads to the occurrence of resonances at the boundary condition holding a series of specific values with an external alternating current source. This curious result suggests the possibility of practical applications of our formula to resonant circuits.

Roadside Unit Caching: Auction-Based Storage Allocation for Multiple Content Providers

Recent improvements in vehicular ad hoc networks are accelerating the realization of intelligent transportation system (ITS), which not only provides road safety and driving efficiency, but also enables infotainment services. Since data dissemination plays an important part in ITS, recent studies have found caching as a promising way to promote the efficiency of data dissemination against rapid variation of network topology. In this paper, we focus on the scenario of roadside unit (RSU) caching, where multiple content providers (CPs) aim to improve the data dissemination of their own contents by utilizing the storages of RSUs. To deal with the competition among multiple CPs for limited caching facilities, we propose a multi-object auction-based solution, which is sub-optimal and efficient to be carried out. A caching-specific handoff decision mechanism is also adopted to take advantages of the overlap of RSUs. Simulation results show that our solution leads to a satisfactory outcome.

Inferring Structural Characteristics of Networks With Strong and Weak Ties From Fixed-Choice Surveys

Knowing the structure of an offline social network facilitates a variety of analyses, including studying the rate at which infectious diseases may spread and identifying a subset of actors to immunize in order to reduce, as much as possible, the rate of spread. Offline social network topologies are typically estimated by surveying actors and asking them to list their neighbors. While identifying close friends and family (i.e., strong ties) can typically be done reliably, listing all of one's acquaintances (i.e., weak ties) is subject to error due to respondent fatigue. This issue is commonly circumvented through the use of so-called “fixed choice” surveys where respondents are asked to name a fixed, small number of their weak ties (e.g., two or ten). Of course, the resulting crude observed network will omit many ties, and using this crude network to infer properties of the network, such as its degree distribution or clustering coefficient, will lead to biased estimates. This paper develops estimators, based on the method of moments, for a number of network characteristics including those related to the first and second moments of the degree distribution as well as the network size, using fixed-choice survey data. Experiments with simulated data illustrate that the proposed estimators perform well across a variety of network topologies and measurement scenarios, and the resulting estimates are significantly more accurate than those obtained directly using the crude observed network, which are commonly used in the literature. We also describe a variation of the Jackknife procedure that can be used to obtain an estimate of the estimator variance.

Interference-aware User Association under Cell Sleeping for Heterogeneous Cloud Cellular Networks

In this letter, we investigate an interference-aware user association scheme with cell sleeping technique in heterogeneous cloud cellular networks where the operation state of each base station (BS) is controlled by a cloud computing center. A user association problem which maximizes the user aggregate utility is formulated. Due to high computational complexity of the traversal method, we propose a distributed heuristic algorithm to get the suboptimal solution. At each cycle, the user selects the best BS by imposing a price which is proportional to the interference the BS provides. The BSs without any associated user will be switched off. Based on the varying network topologies, different combinations of active and switch-off BSs can also be obtained during different cycles. Numerical simulation results indicate that the proposed scheme can achieve remarkable throughput gains under the same power consumption, especially in large scale networks.

A New QoS Routing Northbound Interface for SDN

In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.

A New QoS Routing Northbound Interface for SDN

In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.

Effect of Periodicity in Frequency Responses of Networks From Conducted EMI

In this paper, we consider different types of networks, and investigate the characteristics of the frequency responses of loads, which are distributed in the networks. Without loss of generality, both frequency-independent and frequency-dependent loads are discussed, respectively. Beginning with a transmission-line (TL) network with frequency-independent loads, via the TL theory and Baum–Liu–Tesche equation, we demonstrate that the frequency responses are periodic in the frequency domain, where the periodicity is derived and verified. Subsequently, our study is extended to the complex networks that consist of multiple junctions and branches. By using the statistical method, we generate random loads with different attributes, i.e., resistive, inductive, or capacitive, and mainly study the effect of the number of branches and junctions on the frequency response of targeted load in various networks. From the perspective of protections for the targeted load in networks, results indicate that, for lossless and good dielectric (i.e., low-loss) media, it is crucial to consider the frequency responses at the critical frequencies in a periodical manner, rather than at a single frequency. Furthermore, it is worth noting that, the frequency response of targeted load behaves differently when varying the attributes of other loads in the network. The variation of network topology, i.e., increasing the number of junctions or branches, also influences the frequency response.

Dual phase consensus algorithm for distributed sensor management

We propose the dual phase consensus algorithm (DCPA) to solve distributed sensor-target allocation for multitarget tracking. DPCA combines the benefits of greedy and consensus algorithms to converge to a feasible solution, and then iteratively improves the allocation to aproach the global optimal. Theoretical analysis for convergence and computational and communication complexity of the algorithm is included. This analysis is validated using representative simulation results including sensitivity studies for increasing the number of targets and varying network topologies.

Practicability study on the suitability of artificial, neural networks for the approximation of unknown steering torques

ABSTRACTFor steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.

Efficient Distributed Query Processing

A variety of wireless networks, including applications of Wireless Sensor Networks, Internet of Things, and Cyber-physical Systems, increasingly pervade our homes, retail, transportation systems, and manufacturing processes. Traditional approaches communicate data from all sensors to a central system, and users (humans or machines) query this central point for results, typically via the web. As the number of deployed sensors, and thus generated data streams, is increasing exponentially, this traditional approach may no longer be sustainable or desirable in some application contexts. Therefore, new approaches are required to allow users to directly interact with the network, for example, requesting data directly from sensor nodes. This is difficult, as it requires every node to be capable of point-to-point routing, in addition to identifying a subset of nodes that can fulfil a user's query. This paper presents Dragon, a platform that allows any node in the network to identify all nodes that satisfy user queries, i.e., request data from nodes, and relay the result to the user. The Dragon platform achieves this in a fully distributed way. No central orchestration is required, network overheads are low, and latency is improved over existing comparable methods. Dragon is evaluated on networks of various topologies and different network densities. It is compared with the state-of-the-art algorithms based on summary trees, like Innet and SENS-Join. Dragon is shown to outperform these approaches up to 88% in terms of network traffic required, also a proxy for energy efficiency, and 84% in terms of processing delay.

Dual-Failure Availability Analysis of Span-Restorable Mesh Networks

Modern networks are typically designed to be survivable for single-failure scenarios only. While there does exist some inherent dual-failure survivability, resource limitations generally mean dual failures are not fully protected or restored; there is some nonzero level of unavailability arising due to dual failures. Understanding the complexities of dual-failure related availability, therefore, is an important issue in network design. There are a number of current approaches for evaluating network availability, whether directly, by calculating service path unavailability, or indirectly, via several widely used availability metrics. However, their performance is not as effective as widely believed. After investigating current availability methods, this paper proposes a new method to calculate network service unavailability. An ILP model framework is also built to qualify the new method and evaluate current and new availability analysis methods. Experiments are performed on four test-case networks of various topologies and scales.

The critical node problem in stochastic networks with discrete-time Markov chain

The length of the stochastic shortest path is defined as the arrival probability from a source node to a destination node. The uncertainty of the network topology causes unstable connections between nodes. A discrete-time Markov chain is devised according to the uniform distribution of existing arcs where the arrival probability is computed as a finite transition probability from the initial state to the absorbing state.Two situations are assumed, departing from the current state to a new state, or waiting in the current state while expecting better conditions. Our goal is to contribute to determining the critical node in a stochastic network, where its absence results in the greatest decrease of the arrival probability. The proposed method is a simply application for analyzing the resistance of networks against congestion and provides some crucial information of the individual nodes. Finally, this is illustrated using networks of various topologies.

Probabilistic PMU placement considering topological change in high voltage substations

WAMS and WAMPAC are developed recently in the world electrical networks. PMU forms the basis of WAMS networks by measuring the main electrical parameters (bus voltage and feeder current). It is not necessary to use PMU on all of the network buses for a full observability and many studies are done for optimizing PMU numbers and placement in electrical networks. Considering simple buses for the networks is a common assumption in these studies. While practically, the busbar arrangement is not simple in high voltage substations, especially in 230 and 400kV substations. As a result, it is feasible under different utilization condition that the substations be sectionalized and turns into two separate buses. In this paper a modified PMU placement method is presented considering different busbar arrangement in substations and possibility of network topology variation due to feeders’ connection exchange at substation breakers opening/closing. In the revised method, at first step an optimized placement is aimed for full observability of each network under all configurations and at the second step, an improved placement is the goal in which the network small value of unobservability is acceptable under certain degree of risk. The test results on IEEE standard networks are presented.

A Survey on Geographic Routing Protocols in Delay/Disruption Tolerant Networks

Delay/Disruption Tolerant Networks (DTNs) have been attracting great interest from research community, where data communication naturally does not require contemporaneous end-to-end connectivity. Although they are suffering from a large variation of network topology, numerous previous routing protocols proposed for DTNs still make effort to qualify delivery potential, via network topology information. Geographic routing is an alternative, conceptually, by relying on the geographic information instead of topological information. In the literature, since this technique branch has not been extensively investigated in DTNs, our paper identifies the motivation and challenges for applying geographic routing in DTNs with the state of the art. Also, we highlight the future research directions for this branch.

Pworm: Passive and Real-Time Wormhole Detection Scheme for WSNs

Wormhole attack is one of the severe threats to wireless sensor and ad hoc networks. Most of the existing countermeasures either require specialized hardware or demand high network overheads in order to capture the specific symptoms induced by the wormholes, which in result limits their applicability. In this paper, we exploit an inevitable symptom of wormholes and present Pworm, a passive wormhole detection and localization system based upon the key observation that a large amount of network traffic will be attracted by the wormholes. The proposed scheme is passive, real-time, and efficient against both active and passive wormholes. Our approach silently observes the variations in network topology to infer the wormhole existence and solely relies on network routing information. It does not necessitate specialized hardware or poses rigorous assumptions on network features. We evaluate our scheme through extensive simulations of 100 to 800 nodes for various network scales and show that Pworm is well suited for false alarms, scalability, and time delay in terms of activation as well as detection latencies.

An adaptive vehicular epidemic routing method based on attractor selection model

Vehicular ad hoc networks (VANETs) is an emerging technology that can support many vehicular safety and comfort applications through intervehicle communications. However, VANETs could face a great challenge arising from rapidly varying network topology. It is an essential issue to design an efficient and reliable solution for message dissemination in dynamic VANETs. In this paper, we propose an epidemic routing method with capability of self-adapting to the highly dynamic nature of VANETs. To ensure a good trade-off between reachability and efficiency of message dissemination, an adaptive probabilistic infection and an adaptive limited-time forwarding mechanisms are also proposed for the epidemic broadcasting. Moreover, inspired by the self-adaptability and robustness of the cellular gene regulatory networks, we use the attractor selection mechanism to enhance routing messages in dynamic VANETs. Through comparative simulations under different traffic scenarios, we validate our proposed method and prove that it can guarantee message reachability and achieve high delivery efficiency in terms of message delivery ratio, average routing latency and cost.