Potential Network Topologies Research Articles

Topology comparative assessment for hybrid medium-voltage AC/DC networks

Recently, there has been significant growth in integrating renewable energy generation and electric vehicles and deploying new technologies into the electrical networks, leading to new challenges for planning, design, operation, control and protection of the distribution grid. In particular, an increasing amount of large-scale DC load and generation is expected to be connected to the distribution system, especially at the MV level. Thus, adoption of new grid topologies is required and among others, hybrid AC/DC networks have emerged as an attractive pathway to meet new grid operational requirements. This paper evaluates future hybrid AC/DC distribution systems at the MV level, considering potential network topologies and new technologies. Steady-state analysis is performed to compare five topologies of hybrid MV AC/DC networks. Key technologies for such hybrid grids such as voltage source converters and fast charging stations are considered. The results provide quantitative comparisons between topologies regarding large-scale DC load and generation integration capability, contingency operation, sensitivity analysis. Several challenges presented to the protection and fault location that are caused by the adoption of new topologies are also identified. The topologies are compared by network losses, voltage and power factor constraints, analysing the different benefits and drawbacks of the hybrid AC/DC topologies.

Designing genetic perturbation experiments for model selection under uncertainty

Deterministic dynamic models play a crucial role in elucidating the function of biological networks. However, the underlying biological mechanisms are often only partially known, and different biological hypotheses on the unknown molecular mechanisms lead to multiple potential network topologies for the model. Limitations in generating comprehensive quantitative data often prevent identification of the correct model topology and additionally leave substantial uncertainty about a model’s parameter values. Here, we introduce an experiment design method for model discrimination under parameter uncertainty. We focus on genetic perturbations, such as gene deletions, as our possible experimental interventions. We start from an initial dataset and a single model whose topology includes all different hypotheses. We obtain the set of models compatible with the initial dataset, their posterior probabilities, and the distribution of compatible parameter values using our previously published topological filtering approach. We then employ a fully Bayesian approach to identify the genetic perturbation that yields the maximal expected information gain in a subsequent experiment. This approach explicitly accounts for parameter uncertainty; it also naturally allows comparing an arbitrary number of candidate models simultaneously. In contrast to previous approaches, our intervention alters the topology of the dynamic system rather than selecting optimal inputs, observables, or time-points for measurements. We demonstrate its applicability with an in-silico study based on a published real-world biological example.

Study on PLC with Switch Management in Intelligent Manufacturing Network

abstract This paper discusses a new solution for switch management in intelligent manufacturing network. It makes PLC (Programmable Logic Controller) communication module have the switch management features and exchange I/O data in manufacturing network. The switch manager has used the chip of the Ethernet switch device 88E6165. The Marvell 88E6165 device embedded in communication devices is a single-chip 6 port gigabit Ethernet switch with five integrated gigabit Ethernet transceivers. It performs the tasks of switch management, a series of services and applications are supported in PLC when it is running in a manufacturing network. It also analyzes the potential network topologies in which our customers may use the communication module and how the communication module’s architecture facilitates these topologies. Actors associated with the switch management service are described further. It proposes a new mechanism to minimize the congestion based on the measure of taking an adaptive decision during transferring multicast messages to handle multicast message growing with industrial Ethernet for manufacturing systems. Proposed approach is to accomplish a device requesting to start and stop the reception of the multicast streams. It joins and leaves message requests through IGMP. Final, an application prototype system contains various devices and the global architecture is proposed to provide transparency between control network and device (IO) network.

In silico assessment of cell‐free systems

Cell-free extract (CFX)-derived biocatalytic systems are usually embedded in a complex metabolic network, which makes chemical insulation of the production system necessary by removing enzymatic connections. While insulation can be performed by different methods, the identification of potentially disturbing reactions can become a rather lengthy undertaking requiring extensive experimental analysis and literature review. Therefore, a tool for network topology analysis in cell-free systems was developed based on genome scale metabolic models. Genome scale metabolic models define a potential network topology for living cells, and can be adapted to the characteristics of cell-free systems by: (i) removal of compartmentalization, (ii) application of different objective functions, (iii) enabling the accumulation of all metabolites, (iv) applying different constraints for substrate supply, and (v) constraining the reaction space through cofactor availability, microarray data, feasible reaction rates, and thermodynamics. The resulting computational tool successfully predicted for Escherichia coli-derived CFXs a previously identified undesired pathway for dihydroxyacetone phosphate (DHAP) production from adenosine phosphates. The tool was then applied to the identification of potentially interfering pathways to further insulate a DHAP-producing multi-enzyme system based on CFX.

Node numbering in a topological structure of interconnection network

The topological design of a computer communication network assigns the links and link capacities for connecting network nodes within several constraints, with a goal to achieve a specified performance at a minimal cost. A reasonable approach is to generate a potential network topology. This paper presents a spanning tree based method for systematic numbering of nodes in any communication network. When the nodes are numbered in a systematic manner the potential network topology generated will have lesser amount of perturbation before an acceptable network is found.

A Computational Framework for Ultrastructural Mapping of Neural Circuitry

Circuitry mapping of metazoan neural systems is difficult because canonical neural regions (regions containing one or more copies of all components) are large, regional borders are uncertain, neuronal diversity is high, and potential network topologies so numerous that only anatomical ground truth can resolve them. Complete mapping of a specific network requires synaptic resolution, canonical region coverage, and robust neuronal classification. Though transmission electron microscopy (TEM) remains the optimal tool for network mapping, the process of building large serial section TEM (ssTEM) image volumes is rendered difficult by the need to precisely mosaic distorted image tiles and register distorted mosaics. Moreover, most molecular neuronal class markers are poorly compatible with optimal TEM imaging. Our objective was to build a complete framework for ultrastructural circuitry mapping. This framework combines strong TEM-compliant small molecule profiling with automated image tile mosaicking, automated slice-to-slice image registration, and gigabyte-scale image browsing for volume annotation. Specifically we show how ultrathin molecular profiling datasets and their resultant classification maps can be embedded into ssTEM datasets and how scripted acquisition tools (SerialEM), mosaicking and registration (ir-tools), and large slice viewers (MosaicBuilder, Viking) can be used to manage terabyte-scale volumes. These methods enable large-scale connectivity analyses of new and legacy data. In well-posed tasks (e.g., complete network mapping in retina), terabyte-scale image volumes that previously would require decades of assembly can now be completed in months. Perhaps more importantly, the fusion of molecular profiling, image acquisition by SerialEM, ir-tools volume assembly, and data viewers/annotators also allow ssTEM to be used as a prospective tool for discovery in nonneural systems and a practical screening methodology for neurogenetics. Finally, this framework provides a mechanism for parallelization of ssTEM imaging, volume assembly, and data analysis across an international user base, enhancing the productivity of a large cohort of electron microscopists.

On the topological design of a Computer Network

The goal of the topological design of a Computer Communication Network is to achieve a specified performance at a minimal cost. Unfortunately, the problem is completely intractable. A reasonable approach is to generate a potential network topology. One heuristic for generating a potential network topology is due to Steiglitz, Weiner and Kleitman. This heuristic begins by numbering the nodes at random. This paper presents a systematic method for numbering the nodes. When the nodes are numbered in a systematic manner, the potential network topology generated will need lesser amount of perturbation before an acceptable network is found.

Wavelength division multiplexing in optical fibre sensor systems and networks: a review

Wavelength division multiplexing (WDM) offers a potentially powerful technique for use within single optical fibre sensor systems and multiple sensor networks. The paper commences with a short review of the spectrally modulated and dual wavelength referenced, intensity modulated optical sensors. A WDM system employing multimode fibre and LED sources is then discussed. This is followed by descriptions of particular WDM optical sensor system developments in order to illustrate the approaches currently adopted. Potential network topologies for WDM multiple sensor networks are then introduced, with some description of the major implementational constraints to provide an indication of possible future developments.

New Designs for Dense Processor Interconnection Networks

Distributed computer systems can be modeled using graph theory to evaluate potential network topologies. A good network from a communication standpoint should have a small diameter because this allows all pairs of processors to communicate quickly. This paper presents a new construction method for interconnection networks, which is a generalization of the chordal ring networks of Arden and Lee. The graphs produced by this method are the largest known for many degrees and diameters.

Methods of potential network topology description

Power system topology evaluation starts from switch states and a comprehensive description of breakers, isolators, busbars, transformers, lines, etc., and their potential connections. For the latter task a variety of methods and application structures were developed especially in the context of the description of busbar-type substations. The paper establishes a frame of basic topology description methods and discusses applied and proposed methods in relation to that frame.