Reliable Topology Research Articles

Dynamic Bond Percolation-Based Reliable Topology Evolution Model for Dynamic Networks

Dynamic Bond Percolation-Based Reliable Topology Evolution Model for Dynamic Networks

Flow Adjustment and Scale-Free Reliable Topology Control for Underwater Acoustic Sensor Networks

Flow Adjustment and Scale-Free Reliable Topology Control for Underwater Acoustic Sensor Networks

LINC00116-encoded microprotein mitoregulin regulates fatty acid metabolism at the mitochondrial outer membrane

LINC00116 encodes a microprotein first identified as Mitoregulin (MTLN), where it was reported to localize to the inner membrane of mitochondria to regulate fatty acid oxidation and oxidative phosphorylation. These initial discoveries were followed by reports with differing findings about its molecular functions and submitochondrial localization. To clarify the apparent discrepancies, we constructed multiple orthogonal methods of determining the localization of MTLN, including split GFP-based reporters that enable efficient and reliable topology analyses for microproteins. These methods unequivocally demonstrate MTLN primarily localizes to the outer membrane of mitochondria, where it interacts with enzymes of fatty acid metabolism including CPT1B and CYB5B. Loss of MTLN causes the accumulation of very long-chain fatty acids (VLCFAs), especially docosahexaenoic acid (DHA). Intriguingly, loss of MTLN protects mice against western diet/fructose-induced insulin-resistance, suggests a protective effect of VLCFAs in this context. MTLN thus serves as an attractive target to control the catabolism of VLCFAs.

Eurytemora gracilicauda (Copepoda: Calanoida) in the Russian Arctic

As a result of studying the populations of Eurytemora genus crustaceans from the internal reservoirs of the drainage basin of the White, Pechora Seas, the Lena deltas, Island of Wrangel and Kamchatka peninsula was set that the species Eurytemora gracilicauda is common along the entire northern border of Russian Eurasia. It was shown that the species distribution for populations from the rockpools of the Kandalaksha Bay of the White Sea, from Lake on Kashin Island in the Pechora Sea and from the Lena River Delta was sequentially along the coast of the Arctic. Studies are based on genetic (parts of CO1 and ITS1 genes) and morphological analyzes of the studied populations. The synonymy of the Kamchatka species E. kurenkovi and E. gracilicauda was confirmed by the morphological analysis. Variation coefficients (CV), calculated for the populations of females from the White Sea, the Lena River delta and from the Kamchatka do not exceed 10%, which indicates a low morphological variability of the species. The most widely represented in the genetic analysis, the White Sea population has a low level of genetic variability, which, together with significant tolerance to the fluctuations of salinity in the rockpools in which it lives, may indicate its recent introduction to the region. A phylogenetic reconstruction was not revealed reliable topology for the species E. gracilicauda. It was shown that E. gracilicauda is not related to the affinis group species. Molecular Clocks with use part of CO1 gene and paleontological calibration revealed the speciation of E. gracilicauda species on the Paleocene – Late Cretaceous boundary. We also can hypothesize a Laurasian origin of the Eurytemora genus.

Mapping time-dependent magnetic topologies of active stars

ABSTRACT Throughout the last decades, Zeeman–Doppler Imaging (ZDI) has been intensively used to reconstruct large-scale magnetic topologies of active stars from time-series of circularly polarized (Stokes V) profiles. ZDI being based on the assumption that the topology to be reconstructed is constant with time (apart from being sheared by differential rotation), it fails at describing stellar magnetic fields that evolve on time-scales similar to the observing period. We present a new approach, called TIMeS (for Time-dependent Imaging of Magnetic Stars), to derive the time-dependent large-scale magnetic topologies of active stars, from time-series of high-resolution Stokes V spectra. This new method uses the combined concepts of sparse approximation and Gaussian process regression to derive the simplest time-dependent magnetic topology consistent with the data. Assuming a linear relation between the Stokes V data and the reconstructed magnetic image, TIMeS is currently applicable to cases in which the magnetic field is not too strong (with an upper limit depending on v sin i). We applied TIMeS to several simulated data sets to investigate its ability to retrieve the poloidal and toroidal components of large-scale magnetic topologies. We find that the proposed method works best in conditions similar to those needed for ZDI, reconstructing reliable topologies with minor discrepancies at very low latitudes whose contribution to the data is small. We, however, note that TIMeS can fail at reconstructing the input topology when the field evolves on a time-scale much shorter than the stellar rotation cycle.

Intersatellite Laser Link Planning for Reliable Topology Design in Optical Satellite Networks: A Networking Perspective

The development of reusable rockets makes it possible to launch a massive number of low earth orbit satellites for Internet access. These satellites are expected to be connected by inter-satellite links (ISLs) to provide global Internet service to end-users on the surface of the earth. From the infrastructure’s perspective, the ISLs can be implemented with lasers, forming the optical satellite networks. The design of terrestrial optical networks is usually traffic-driven, meaning more links/bandwidth are deployed to the traffic-intensive areas. But, the orbiting nature of satellites determines that laser ISLs are also moving at high velocities, making the presence of corresponding bandwidth loosed coupled with a specific area. As a result, the traffic-driven network design methodology will be inapplicable to the optical satellite networks. In this work, we model the optical satellite networks and define the laser ISL planning problem, Accordingly, we propose an ISL removal algorithm to remove parts of the ISLs from the grid-mesh topology to improve the average bandwidth utilization ratio (i.e., bandwidth efficiency) while maintaining networks’ reliability and availability. We conduct a simulation study based on the Starlink constellation to evaluate the grid-mesh topology and to investigate the proposed algorithm’s impact on the network performance. Results show that the bandwidth resource in the grid-mesh topology can hardly be used efficiently and removing certain ISLs properly can improve the bandwidth efficiency of optical satellite networks significantly. We also gain another interesting insight that maintaining too many ISLs will not improve, but degrade the network availability.

Understanding the Genetic Diversity of Picobirnavirus: A Classification Update Based on Phylogenetic and Pairwise Sequence Comparison Approaches

Picobirnaviruses (PBVs) are small, double stranded RNA viruses with an ability to infect a myriad of hosts and possessing a high degree of genetic diversity. PBVs are currently classified into two genogroups based upon classification of a 200 nt sequence of RdRp. We demonstrate here that this phylogenetic marker is saturated, affected by homoplasy, and has high phylogenetic noise, resulting in 34% unsolved topologies. By contrast, full-length RdRp sequences provide reliable topologies that allow ancestralism of members to be correctly inferred. MAFFT alignment and maximum likelihood trees were established as the optimal methods to determine phylogenetic relationships, providing complete resolution of PBV RdRp and capsid taxa, each into three monophyletic groupings. Pairwise distance calculations revealed these lineages represent three species. For RdRp, the application of cutoffs determined by theoretical taxonomic distributions indicates that there are five genotypes in species 1, eight genotypes in species 2, and three genotypes in species 3. Capsids were also divided into three species, but sequences did not segregate into statistically supported subdivisions, indicating that diversity is lower than RdRp. We thus propose the adoption of a new nomenclature to indicate the species of each segment (e.g., PBV-C1R2).

Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing.

The continuous development of fifth-generation (5G) networks is the main driving force for the growth of Internet of Things (IoT) applications. It is expected that the 5G network will greatly expand the applications of the IoT, thereby promoting the operation of cellular networks, the security and network challenges of the IoT, and pushing the future of the Internet to the edge. Because the IoT can make anything in anyplace be connected together at any time, it can provide ubiquitous services. With the establishment and use of 5G wireless networks, the cellular IoT (CIoT) will be developed and applied. In order to provide more reliable CIoT applications, a reliable network topology is very important. Reaching a consensus is one of the most important issues in providing a highly reliable CIoT design. Therefore, it is necessary to reach a consensus so that even if some components in the system is abnormal, the application in the system can still execute correctly in CIoT. In this study, a protocol of consensus is discussed in CIoT with dual abnormality mode that combines dormant abnormality and malicious abnormality. The protocol proposed in this research not only allows all normal components in CIoT to reach a consensus with the minimum times of data exchange, but also allows the maximum number of dormant and malicious abnormal components in CIoT. In the meantime, the protocol can make all normal components in CIoT satisfy the constraints of reaching consensus: Termination, Agreement, and Integrity.

Topology and hydraulic permeability estimation of explosively created fractures through regular cylindrical pore network models

Purpose This research study aims to develop regular cylindrical pore network models (RCPNMs) to calculate topology and geometry properties of explosively created fractures along with their resulting hydraulic permeability. The focus of the investigation is to define a method that generates a valid geometric and topologic representation from a computational modelling point of view for explosion-generated fractures in rocks. In particular, extraction of geometries from experimentally validated Eulerian smoothed particle hydrodynamics (ESPH) approach, to avoid restrictions for image-based computational methods. Design/methodology/approach Three-dimensional stabilized ESPH solution is required to model explosively created fracture networks, and the accuracy of developed ESPH is qualitatively and quantitatively examined against experimental observations for both peak detonation pressures and crack density estimations. SPH simulation domain is segmented to void and solid spaces using a graphical user interface, and the void space of blasted rocks is represented by a regular lattice of spherical pores connected by cylindrical throats. Results produced by the RCPNMs are compared to three pore network extraction algorithms. Thereby, once the accuracy of RCPNMs is confirmed, the absolute permeability of fracture networks is calculated. Findings The results obtained with RCPNMs method were compared with three pore network extraction algorithms and computational fluid dynamics method, achieving a more computational efficiency regarding to CPU cost and a better geometry and topology relationship identification, in all the cases studied. Furthermore, a reliable topology data that does not have image-based pore network limitations, and the effect of topological disorder on the computed absolute permeability is minor. However, further research is necessary to improve the interpretation of real pore systems for explosively created fracture networks. Practical implications Although only laboratory cylindrical rock specimens were tested in the computational examples, the developed approaches are applicable for field scale and complex pore network grids with arbitrary shapes. Originality/value It is often desirable to develop an integrated computational method for hydraulic conductivity of explosively created fracture networks which segmentation of fracture networks is not restricted to X-ray images, particularly when topologic and geometric modellings are the crucial parts. This research study provides insight to the reliable computational methods and pore network extraction algorithm selection processes, as well as defining a practical framework for generating reliable topological and geometrical data in a Eulerian SPH setting.

An efficient approach to find reliable topology of stochastic flow networks under cost constraint

Computer and communication networks are often stochastic capacitated networks due to partial or complete failure of network components such as links and nodes. Therefore, in practice, network components have different associated costs based on their bandwidth and failure probabilities. Different topologies which are composed of different components of the network may provide various reliability values for a given cost constraint. Finding a topology of a stochastic flow network that can pass a set of demand from multiple sources to multiple destinations with maximum reliability under given cost constraint is an important problem. This work presents an efficient approach to find such topologies in two phases: First, it finds the upper boundary topologies which are subset of topologies that satisfy the cost constraint and are more reliable amongst the others. Second, it evaluates the reliability of upper boundary topologies and chooses the one that provides maximum reliability. Reliability evaluation is computationally hard problem. Proposed method minimizes number of reliability evaluations of topologies through upper boundary topologies. Further, it presents two efficient methods for obtaining the upper boundary flow vectors which are required for reliability evaluation of the upper boundary topologies. We implemented the proposed methods in MATLAB and analyzed their performance using the benchmark networks available in the literature.

Enhancing the Reliability of Cellular Internet of Things through Agreement

Because the Internet of Things (IoT) can provide a global service network through various smart devices, the IoT has been widely used in smart transportation, smart cities, smart healthcare, and factory automation through the Internet connection. With the large-scale establishment and 5G (fifth generation) wireless networks, the cellular Internet of Things (CIoT) will continue to be developed and applied to a wide range of applications. In order to provide a reliable application of CIoT, a safe and reliable network topology MECIoT is proposed in this study. To improve the reliability and fault-tolerant capability of the network proposed, the problem of reaching agreement should be revisited. Therefore, the applications in the system can still be performed correctly even if some processing units (PUs) in the system have failed. In this study, a new protocol is proposed to allow all normal PUs in MECIoT to reach an agreement with the minimum amount of data exchanges required and the maximum number of failed PUs allowed in MECIoT. In the end, the optimality of the protocol has been proven by mathematical method.

A new Evolutionary Structural Optimization method and application for aided design to reinforced concrete components

The Evolutionary Structural Optimization (ESO) has been applied to find the optimal structural topology for design and construction purposes. However, its efficiency is low due to the imperfect deletion criteria. This paper presents an improved elimination criterion and the Windowed Evolutionary Structural Optimization (WESO) method. The former considers the structural average strain energy as the elimination criteria in the optimization, with the elimination rate set as a self-adaption state by an adjustable window. Thus, the problems of low optimization efficiency and distorted optimization results in the traditional ESO can be solved to a certain extent. The WESO method can then be extended and applied with a complex finite element model. It is found that the method has better optimal ability in handling discrete elements in vast structures. Compared with the other method, the WESO method has high computational efficiency and offers more stable and reliable topology than the Michell theoretical solution. Lastly, upon developing the optimal topology for a double-deck structure, it is shown that the WESO method has a great potential in civil engineering applications.

Topology optimization in lightweight design of a 3D-printed flapping-wing micro aerial vehicle

Topology optimization is an effective method to obtain a lightweight structure that meets the requirements of structural strength. Whether the optimization results meet the actual needs mainly depends on the accuracy of the material properties and the boundary conditions, especially for a tiny Flapping-wing Micro Aerial Vehicle (FMAV) transmission system manufactured by 3D printing. In this paper, experimental and numerical computation efforts were undertaken to gain a reliable topology optimization method for the bottom of the transmission system. First, the constitutive behavior of the ultraviolet (UV) curable resin used in fabrication was evaluated. Second, a numerical computation model describing further verified via experiments. Topology optimization modeling considering nonlinear factors, e.g. contact, friction and collision, was presented, and the optimization results were verified by both dynamic simulation and experiments. Finally, detailed discussions on different load cases and constraints were presented to clarify their effect on the optimization. Our methods and results presented in this paper may shed light on the lightweight design of a FMAV.

Information Theoretic Generalized State Estimation in power systems

This paper introduces an Information Theoretic approach for Generalized State Estimation, aiming at achieving reliable topology and state variables co-estimation results, even in the presence of both topology errors and gross measurements. Attention is focused on the final bad data processing stage in which only relevant parts of the power network are represented at the bus-section level. The proposed generalized strategy applied at physical level relies on the superior outlier rejection properties of state estimators based on Maximum Correntropy, a concept borrowed from Information Theoretical Learning. A single objective function unifies the treatment of analog measurements and topology data, leading to an algorithm that does not require re-estimation runs for bad data suppression, and is simpler and more efficient than previously proposed co-estimation methods. Case studies conducted for distinct test-systems are presented, including various types of topology errors and simultaneous occurrence of topology and gross measurement errors. The results suggest that the proposed information-theoretic co-estimation algorithm is able to successfully provide bad data-free real-time network models even in the presence of multiple topology errors, simultaneous gross measurements and inaccurate topology information. Finally, additional tests confirm its superior computational performance as compared with other co-estimation algorithms.

Reliability Analysis of High Gain Integrated DC–DC Topologies for Xenon Lamp Applications

Emerging switched-mode power supplies incorporated applications demand reliable, less volume and high efficient dc–dc converters. The persistent usage of the dc–dc converters in various applications makes their reliability a significant concern. Hence, this paper deals with a family of non-isolated high gain integrated dc–dc converter topologies derived from a quadratic converter. The reliability analysis is carried out using electronic equipment reliability handbook, MIL-HDBK-217F. For the first time, reliability prediction is done based on the working environment of the power electronic equipments. We developed the reliability prediction for the converters used in the lighting application such as automotive headlamp and aircraft landing lights. The mean time to failure for both the environment is calculated. The reliability comparison is carried out for the proposed topologies and the most reliable converter is chosen. Also, all the converter topologies are simulated using nL5 simulator to confirm their theoretical results. Finally, a laboratory prototype for 40 W with input voltage of 12 V is implemented for the most reliable topology to validate the steady-state analysis.

Integrated method for performance analysis of reliability-based topologically optimized components

The available robust and reliable topology optimization methods provide quick and efficient design output in an uncertain environment. However, the whole domain of performance function remains hidden during this design process. In the interest of the designer, it is required to know the overall behavior of performance functions in deterministic as well as uncertain/realistic environment. The current work achieves this by proposing an integrated methodology, which combines the design of experiments approach and reliability-based topology optimization. The proposed method enables the designer to simulate performance functions in a desired design-factors space, including uncertainties, via reliability value. For this analysis, compliance, maximum deflection, mechanical advantage, and von Mises stress values are selected as performance functions. Volume fraction, applied force, and dimensions or aspect ratio are chosen as design/control factors. The uncertainties of these design factors are captured using reliability-based topology optimization. The uncertainties due to noncontrollable factors such as material property, load direction, and magnitude are incorporated using the design of experiments approach. Under these uncertainties, the performance of topologically optimized problem is simulated for different experimental combinations of the design factors. The experimental combinations for uncertainties and design factors are generated using Taguchi's orthogonal array. Simulated results are analyzed using techniques such as analysis of mean and variance, signal-to-noise ratio, and response surface method. These analyses help in identifying statistical significance of factors and uncertainties, performance variations, and equivalence relation of performance vs. factor. The proposed methodology is illustrated by selecting monolithic structures such as, on MBB, cantilever beam, and force inverter mechanism.

Novel node deployment scheme and reliability quantitative analysis for anIoT-based monitoring system

The Internet of things (IoT) is highly suitable for military, environmental, agricultural, and other remote real-time monitoring applications. A reliable topology ensures a stable and dependable monitoring system. Considering the research of an IoT-based air pollution monitoring system for industrial emissions as background, this study proposes a novel dual redundant node deployment scheme. Specifically, hexagonal clustering is proposed for the internal regions. In addition, relationship and quantification formulas for a monitoring area are presented, and the communication range, total number of layers of the topology, and number of cluster headers are determined. Interruptions in a monitoring system may reduce the quality of IoT services. Therefore, sensor nodes are also deployed around the monitoring area (in outer regions). The basic external area is modeled and proposed as a rectangular, 1-covered isosceles triangle deployment plan with the objective of minimizing the number of sensor nodes. A quantitative formula is given using the sensing radius, width of the rectangle, and adjacent distance between nodes. Reliability is a critical index in IoT-based applications. Thus, the reliability of a hexagonal clustering topology is presented using reliability block diagrams. For a reliable remote transmission model, different redundant systems are implemented. Furthermore, the reliability value and mean time to failures are calculated. The results are later compared and analyzed quantitatively. This study presents important theoretical and application-based knowledge that can guarantee reliable service for an IoT-based monitoring system.

Reliability-based topology design for large-scale networks

Network topology has a critical effect on its reliability. Due to the complexity of networks, how to design a more reliable network topology is one of the fascinating and significant challenges. In this paper, inspired by the multi-scale model of biological systems which range from gene to individual cells, and up to the individual organism, we provide a novel method to design a reliable topology of large-scale networks. By means of fractal theory and its application in complex networks, a network topology can be described as consisting of the superposition of basic units, called fractal-cells, which are made up of several components and their connections. Based on this fractal-cell structure, we find that a fractal-cell network has structural similarity with its primitive structure, and then develop a method to build a reliable topology which is generated from a primitive ring structure. Numerical simulation compared with the existing methods and performing on real networks show that our proposed method is effective.

Reliability-Oriented Networking Planning for Meshed VSC-HVDC Grids

This paper proposes a reliability-oriented planning method to design reliable topologies for meshed high-voltage direct-current (HVdc) grids. Based on the proposed steady-state model for HVdc grids, a bi-level and multiobjective planning problem is formulated. The optimization model not only regards reliability as an independent objective, but also takes the power flow controllers (PFCs) into account. Compared with conventional methods, it overcomes the curse of dimensionality and solves the optimal allocation of PFCs. Then, the nondominated sorting genetic algorithm II is employed to solve the upper-level problem. For lower-level problems, an algorithm based on minimum spanning trees is proposed to optimally allocate PFCs, and an improved least frequently used cache algorithm and an optimum-test algorithm are developed to promote the computing efficiency of reliability evaluation. The European Supergrid and a Chinese ultra-HVdc system are adopted as test systems to validate the proposed method. Case studies prove that the proposed method provides an effective tool for the planning of HVdc grids. Also, results show that the cache technique and the optimum-test algorithm can reduce more than 70% of the total elapsed time.

Topology Control in MANETs Using the Bayesian Pursuit Algorithm

A way of optimizing energy consumption in mobile ad hoc networks is topology control. Various topology control algorithms have been proposed, but a few of them have used meta-heuristic methods such as genetic algorithms, neural networks, and learning automata. This paper presents a new algorithm based on the Bayesian pursuit (BPST) algorithm. The proposed algorithm predicts node mobility parameters by learning from the environment and uses these parameters to predict link availability duration. The algorithm, then, finds the paths with maximum lifetime by removing the links with a short lifetime using the local Dijkstra algorithm. In this way, an efficient and reliable topology is constructed. The paper also provides the proof of the convergence of the propounded BPST algorithm. The simulation results show that this algorithm can efficiently reduce energy consumption and improve throughput and end-to-end delay as two parameters of the quality of service.