Solution Route Research Articles

Creation of the method of multipath routing using known paths in software-defined networks

The object of the research is the creation of a multipath routing algorithm for software-defined networks (SDN) including known paths, subject of the research is network parameters, designed according to a certain topology and using the developed algorithm. One of the most problematic aspects of contemporary computer networks (including applied SDN networks) is overloading. This results in harder control and limiting traffic and amount of users. Most routing algorithms that are used today have a rather large time complexity. In the course of the study, the following methods were used: study of known routing solutions for SDN networks and results of their application, method of path metric computation on the given topology by the amount of «hops» (transitions between network nodes), optimization of procedure for finding the path using SDN technology capabilities. These methods were united and integrated into the development of the overall routing algorithm, which is proposed in this article. The proposed multipath routing algorithm allows for the improvement of the process of traffic construction in the SDN network. This was achieved by decreasing the time complexity of the routing algorithm through the usage of previously known paths in the topology without the need to construct new ones. Involvement in the modification of the algorithm of forming distance vectors facilitated timely network reconfiguration in case its state changed. Using a centralized SDN controller made it possible to increase the stability of the network and save all configuration data in one place. The above factors make it possible to deploy an SDN network on an Edge architecture. Obtained results of the application of the multipath routing algorithm allow to consider it effective when compared with previously proposed algorithms, based on obtained results from a practical network model, where the proposed multipath routing algorithm is used. This is because the research task was formed correctly, and the solution for this task gave correct results. Results of using the described algorithm are demonstrated, and an analysis of the obtained results is conducted, which makes it possible to confirm the accuracy of scientific research.

Surface defect-rich ZnO nanostructures with high yellow-orange luminescence

ZnO nanostructures such as nanoislands, nanosheets, microflowers and nanoparticles were obtained successfully using a facile and rapid solution route employing low temperatures and reduced molar concentrations from precursor without using any surfactant agent or additional procedures. In this route, we use ZnCl2 as precursor ranging from 0.05 to 0.4 M and two hydrothermal times (2 and 4 h) to obtain different ZnO morphologies. According to SEM micrographs, the morphology of ZnO nanostructures showed a strong dependence on the ZnCl2 concentration and hydrothermal synthesis time. ZnO microflowers were obtained at 0.05 M during 2 h, while ZnO nanoislands, nanoparticles and nanosheets were observed at 0.05, 0.2 and 0.4 M, respectively, in 4 h. X-Ray diffraction and Raman results showed the wurtzite-type ZnO structure and good crystallinity in all cases. In addition, both techniques confirmed the best crystalline quality in ZnO nanoparticles followed by ZnO nanosheets. Finally, according to photoluminescence measurements, all samples exhibit a high yellow-orange emission, associated to a large number of surface defect states, such as oxygen and zinc interstitials. The largest amount of zinc interstitials and zinc vacancies were observed in ZnO nanoislands, while ZnO microflowers have the highest visible emission (followed by ZnO nanoparticles) which in turn, offered the lowest excitonic recombination from the conduction band to the valence band, which may result in a higher photocatalytic efficiency.

GenES-MDA: A generic open-source software package to solve inverse problems via the Ensemble Smoother with Multiple Data Assimilation

Ensemble Kalman filter methods have been successfully applied for data assimilation and parameter estimation through inverse modeling in various scientific fields. We have developed a new generic software package for the solution of inverse problems implementing the Ensemble Smoother with Multiple Data Assimilation (genES-MDA). It is an open-source, platform-independent Python-based program. Its aim is to facilitate the management and configuration of the ES-MDA through several programming tools that help in the preparation of the different steps of ES-MDA. genES-MDA has a flexible workflow that can be easily adapted for the implementation of different variants of the ensemble Kalman filter and for the solution of generic inverse problems. This paper presents a description of the package and some application examples. genES-MDA has been tested in three synthetic case studies: the solution of the reverse flow routing for the estimation of the inflow hydrograph to a river reach using observed water levels and a calibrated forward model of the river system, the identification of a hydraulic conductivity field using piezometric observations and a known forward flow model, and the estimation of the release history of a contaminant spill in an aquifer from measured concentration data and a known flow and transport model. The results of all these tests have demonstrated the flexibility of genES-MDA and its capabilities to efficiently solve different types of inverse problems.

Community logistics for dynamic vehicle dispatching: The effects of community departure “time” and “space”

The rise of e-commerce has completely transformed the dynamicity and problem nature of last-mile delivery, owing to significant B2C customer demand in compact urban areas. Given the unprecedented growths of urban last-mile deliveries, this paper proposes a novel postponement prioritized-route optional approach, namely Community Logistics (CL), as a new logistics tool to manage dynamic arrivals of delivery requests received in e-commerce hubs. Each vehicle is responsible for serving a “community”. At each decision epoch, fragmented e-commerce delivery requests arrived at the depot are either allocated to a community or postponed to later epochs for actual last-mile delivery. With an objective of consolidating newly arrived requests, we develop two dynamic policies – temporal and spatial, respectively for temporally delaying vehicle’s departure and spatially allocating more pre-partitioned geographical cells into one community. The main contribution of this study lies in a spatiotemporal relativity analysis and a comparative analysis. The former demonstrates the essence of incorporating both dynamic community departure times and dynamic community regions into managing urban e-commerce deliveries, whereas the latter validates the merits of Community Logistics against dynamic vehicle routing solutions. In the end, we call for further developments of community logistics strategies to address the impacts of urban deliveries due to the rise of e-commerce and online shopping.

Analysis of non-noble plasmonic enhanced solar distillation using computed optical activities

Solar distillation is an immensely promising, renewable energy-based solution route for potable water production from grey water. Noble plasmonic nanoparticles (e.g., Au, Ag) are typically employed in solar distillation systems for efficiency enhancement. However, their high cost renders such technologies economically nonviable. In this study, we evaluate the prospect of using Cu-coated Al as non-noble plasmonic nanoparticles for solar distillation based on the energy balance across various parts of a solar still (basin, glass cover and fluid). We compute the absorption and scattering cross-sections of these nanoparticles, and hence their optical activity. We show that particles of sizes <60 nm have greater absorption cross-section as compared to scattering cross-section in the ultraviolent (200 to 360 nm) and visible light spectrum (360 to 700 nm). The effects of nanoparticle concentration (0.004 % to 0.024 % of sizes 10–22 nm) in the nanofluid on the yield of distillate, energy efficiency and temperature of the fluid are analyzed. We report that Al-Cu nanoparticles enhance energy efficiency of a conventional solar still by as much as 64 % at a concentration of 0.012 %. The efficiency increases with increasing nanoparticle concentration and begins to saturate after 0.012 % concentration.

Superparamagnetic Iron Oxide Nanoparticles (SPIONs) and Reduced Graphene Oxide (RGO) Based Nanocomposites Prepared by Low-Temperature Route and Their Anticancer Properties

In this work, a facile low temperature solution route was reported for the preparation of monodisperse Fe3O4 nanoparticles and their reduced graphene oxide (RGO) based nanocomposites and used as anticancer agents. X-ray diffraction spectroscopy XRD and Raman studies revealed the high crystalline nature of the Fe3O4 nanoparticles and the presence of characteristic peaks of RGO in Fe3O4/RGO nanocomposites. Transmission electron microscopy (TEM) micrographs showed the morphology of the RGO nanosheets decorated by Fe3O4 nanoparticles with sizes ranging from 10–15 nm. High resolution (HR)-TEM study revealed the formation of Fe3O4/RGO nanocomposites with the interplanar spacing corresponding to the (311) plane of Fe3O4. The anti-cancer properties of Fe3O4/RGO nanocomposites against A549 cells were investigated using MTT, NRU assay, morphology of cells, and ROS generation analyses and compared with the pure Fe3O4 nanoparticles. In comparison between both the pure Fe3O4 and Fe3O4/RGO nanocomposites, more damage to the A549 cells resulted from the nanocomposites at a similar concentration of 100 μg/ml. The cell viability test showed that 36% cell viability was observed at a concentration of 100 μg/ml for Fe3O4/RGO nanocomposites. Additionally, the percentage of ROS generation for Fe3O4/RGO nanocomposites was higher than that of Fe3O4 at a concentration of 100 μg/ml. These results suggested that the as-synthesized nanocomposites might be a potential candidate for future anticancer agents.

Synthesis of copper nanoparticles on cellulosic fabrics and evaluation of their multifunctional performances

Two different kinds of copper nanoparticles (CuNPs) (brown colour and greenish colour) were synthesised by using simple solution route and applied by exhaust method to achieve multidimensional functionalization on one of the most popular cellulose materials e.g., cotton fabric. The synthesised CuNPs imparted different colours to the said textile due to different conditions of synthesis and localized surface plasmon resonance. Physico-chemical characterizations of the synthesized nanoparticles were performed by using scanning electron microscope (SEM) and energy dispersive X-ray (EDX) analysis whereas the optical properties of the nanoparticles were studied using UV–visible spectroscopy. The prepared CuNPs of both the types demonstrated very good antimicrobial activity up to 97%. In addition, cotton fabric treated with CuNPs showed very high catalytic activity for reduction of 4-nitroaniline (4-NA) in presence of sodium borohydride to phenylene diamine (4-PD). Washing durability and rubbing fastness of the treated fabric have also been measured by following standard testing methods and found to be very good with a rating 4.Graphical abstract

Efficient Detailed Routing for FPGA Back-End Flow Using Reinforcement Learning

Over the past few years, the computation capability of field-programmable gate arrays (FPGAs) has increased tremendously. This has led to the increase in the complexity of the designs implemented on FPGAs and to the time taken by the FPGA back-end flow. The FPGA back-end flow comprises of many steps, and routing is one of the most critical steps among them. Routing normally constitutes more than 50% of the total time taken by the back-end flow and an optimization at this step can lead to overall optimization of the back-end flow. In this work, we propose enhancements to the routing step by incorporating a reinforcement learning (RL)-based framework. In the proposed RL-based framework, we use the ϵ-greedy approach and customized reward functions to speed up the routing step while maintaining similar or better quality of results (QoR) as compared to the conventional negotiation-based congestion-driven routing solution. For experimentation, we use two sets of widely deployed, large heterogeneous benchmarks. Our results show that, for the RL-based framework, the ϵ-greedy greedy approach combined with a modified reward function gives better results as compared to purely greedy or exploratory approaches. Moreover, the incorporation of the proposed reward function in the RL-based framework and its comparison with a conventional routing algorithm shows that the proposed enhancement requires less routing time while giving similar or better QoR. On average, a speedup of 35% is recorded for the proposed routing enhancement as compared to negotiation-based congestion-driven routing solutions. Finally, the speedup of the routing step leads to an overall reduction in the execution time of the back-end flow of 25%.

Energy optimization using swarm intelligence for IoT-Authorized underwater wireless sensor networks

Several data forwarding and clustering techniques have been proposed to improve Underwater Wireless Sensor Networks (UWSNs) performance, but void communications, packet collisions, and energy efficiency remain unresolved. We introduce a novel routing solution for energy and QoS-efficient data transmission from the underwater sensor node to the surface sink using Swarm Intelligence (SI). The protocol Energy Optimization using the Routing Optimization (EORO) is proposed to overcome the existing challenges. We design Effective Fitness Function-based Particle Swarm Optimization (EFF-PSO) to choose the optimal forwarder node for UWSN data delivery. In EORO, forwarding relay nodes are discovered by the intended source node using location information first. Then EFF-PSO algorithm is applied to select the optimal relay node considering the rich set of parameters. Four parameters of each forwarder node are used for fitness computation as residual energy, packet transmission ability, node connectivity, and distance. These parameters are deliberately chosen to reduce energy consumption, latency, and throughput by avoiding packet collisions. EORO surpassed underlying routing solutions in throughput, energy consumption, latency, and Packet Delivery Ratio (PDR).

Morphology control in nickel cobaltite synthesised via solution routes for electrochemical applications

Research on the synthesis of electrode materials has seen a transition from a “mix and try” approach to a systematic design of nanostructures resulting in exciting morphologies and architectures. Recent research efforts delve rigorously into utilizing the exquisite shape dependant and defect-induced property of electrode materials for phenomenal enhancements in the device performance. Among various strategies for the morphology control at the nano/micro level, the solution-based chemical processes offer pathways for the growth of various morphologies enabling the utility of materials chemistry for enhanced properties. Nickel cobaltite has been explored as an active electrode material for various energy storage and conversion devices, including batteries, supercapacitors, and electrocatalysts. Synthesis of an impressive range of composite structures of nickel cobaltite has already been reviewed and reported. In this article, we collate and review the approaches for morphology control and defect engineering strategies adopted for nickel cobaltite nanostructures. The effect of synthetic parameters such as precursor effects, type of precipitant and additives, calcination temperature etc. On the morphology tuning and defect engineering are analysed. This review aims to establish a structure-property correlation based on the synthesis conditions and the electrochemical properties of nickel cobaltite for meeting the desired needs in various application areas.

Dynamic Virtual Topology Aided Networking and Routing for Aeronautical Ad-Hoc Networks

Aeronautical Ad-hoc Networks (AANETs) have been proposed as the promising complement to terrestrial networks for promoting the global interconnection to provide in-flight network service, emergency communication, vessel traffic service, etc. However, the large network scale of AANETs may induce severe synchronization overhead when the traditional topology-based networking algorithms are adopted. Moreover, the high-dynamic topology and changeable flight routes make the existing position-based routing algorithms suffer loop routing and forwarding failure. Motivated by these problems, this paper aims at developing efficient and low-cost networking and routing algorithms relying on the concept of dynamic virtual topology which organizes the disordered topology of AANETs into a structural and simplified one. The basic idea is that each connected aircraft is assigned with a unique and sequentially increased Virtual Identifier (VID) and thus all the connected aircrafts are organized into a virtual cluster consisting of one trunk and several branches. An event-driven synchronization mechanism is leveraged for maintaining the virtual topology as well as relieving the communication burden imposed by periodical broadcasting. By jointly considering the geographic locations and the virtual locations of aircrafts, we formulate the routing problem in AANETs as a weighted distance minimization problem, and further propose a novel routing algorithm, namely Trunk-Branch Cooperation aided Routing (TBCR) algorithm. Specifically, TBCR employs the geographic greedy forwarding strategy for enhancing its flexibility and boosts the routing efficiency by adopting the loop-free virtual topology based local forwarding. For extending the networking and routing algorithms to the global range, a multi-domain routing solution is also provided. Extensive experimental results show that the proposed Virtual Topology based Networking (VTN) cooperated with TBCR can reduce at least 30% average end-to-end transmission delay in large-scale AANETs and provide more than 90% lower synchronization overhead than the existing solutions.

Towards a Continuous Solution of the $d$-Visibility Watchman Route Problem in a Polygon With Holes

A new heuristic solution framework is proposed to address the challenging <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">watchman route problem</i> (WRP) in a polygonal domain, which can be viewed as an offline version of the robot exploration task. The solution is the shortest route from which the robot can visually inspect a known 2D environment. Our framework considers a circular robot with radius <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$r$</tex-math></inline-formula> equipped with an omnidirectional sensor with limited visibility range <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d$</tex-math></inline-formula> . Instead of a standard <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">decoupled</i> solution, the framework generates a set of specifically constrained regions covering the domain and then solves the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">traveling salesman problem with continuous neighborhoods</i> (TSPN) to obtain the solution route. The TSPN is solved by another proposed heuristic algorithm that finds a discretized solution first and then improves it back in the continuous domain. The whole framework is evaluated experimentally, compared to two approaches from the literature, and shown to provide the highest-quality solutions. The current version of the framework is one step from a fully continuous approach to the WRP that we will address in the future.

Electric vehicle routing models and solution algorithms in logistics distribution: A systematic review.

With the development of green logistics and the promotion of new energy vehicle development policies domestically and abroad, electric vehicles have been put into logistics and distribution as an alternative to traditional fuel vehicles. The Electric Vehicle Routing Problem (EVRP) has attracted widespread attention from the academic community. This paper comprehensively examines the latest research progress on electric vehicle routing models and solution algorithms in logistics and distribution. Firstly briefly introduces EVRP models considering battery losses; secondly, based on the composition of the EVRP objective function and constraints, EVRP models are classified into four types: EVRP considering load and battery life constraints, EVRP with a time window and considering charging strategies, the study of vehicle routing problems for hybrid fleets, and EVRP combined with charging/swapping station location. Then, briefly introduce exact algorithms, traditional heuristics, meta-heuristics, and hybrid algorithms for solving EVRP models. Moreover, it analyzes the main meta-heuristics that are more widely used. Finally, this review points out the development trend of EVRP theoretical methods.

Solution route to process BaZnO2:Eu3+ nano-phosphor for White-LED applications

We report a novel approach for the synthesis of single-phase BaZnO2:Eu3+nano-phosphor, using a hot-injection technique without a vacuum system. This synthesis method is rapid (∼90 min) and cost-effective compared to synthesizing the bulk phosphor. The X-ray diffraction (XRD) pattern indicates the trigonal crystal structure with space group P3121 (No.152). Transmission Electron Microscopy (TEM) images discovered the oval-shaped morphology in the nanosize region with an average particle size of ∼20 nm. The elemental composition analysis of the phosphor was done using energy dispersive X-ray analysis (EDAX). Furthermore, good thermal stability has been revealed via luminescence spectrum under the excitation of 467 nm and a retained 67% of the initial at 150 °C. Commission Internationale de l’Eclairage (CIE) color-coordinates (0.65,0.34) are in the range of orange-red region (595 nm and 610 nm) with 96.35% color purity for BaZnO2:Eu3+ nano-phosphor. The activation energy was calculated and found to be 0.25eV. Results perfectly recognized the suitability of these phosphors for the generation of white light-emitting diodes, which are otherwise difficult to synthesize at such a low temperature (300 °C). To the best of the author's knowledge, this is the first-hand report on the synthesis of europium doped BaZnO2nano-phosphor via hot injection technique.

A Robust Graph Theoretic Solution of Routing in Intelligent Networks

Implementation of robust routing is very critical in network communication. Connecting devices like routers maintain databases for the whole network topology in the routing table. Each router needs to keep these tables updated with the best possible routes so that an efficient communication can always take place in nondelay tolerant intelligent networks that include military and tactical systems, vehicular communication networks, underwater acoustic networks, and intelligent sensor networks. The fast construction of shortest-path tree (SPT) is important to devise an efficient routing in a nondelay tolerant networks. That is why a simple and efficient algorithm is the need of the time. A robust routing solution SPT with O V + E time complexity is proposed to supersede the existing landmark.

A two-stage UAV routing problem with time window considering rescheduling with random delivery reliability

Reliability is an important metric for unmanned aerial vehicles (UAVs) to perform important, complex, and dangerous tasks. In addition, reliability influences the operational cost in UAVs routing. In order to reduce the operational cost of UAVs tasks, a method of routing strategy optimization is proposed from a view of mission reliability in this paper to address the limitations in routing scheduling. Different from previous studies on the UAVs routing optimization problem, this paper proposes a method that can reduce the operational costs of UAVs tasks based on the mission reliability. This method includes two stages: the pre-optimization stage and the rescheduling stage. In the pre-optimization stage, an optimal UAVs route solution is obtained for all the targets, while in the rescheduling stage, new UAVs are dispatched to the unvisited targets in the pre-optimization stage based on the new optimal UAVs route.

Sunlight-driven photocatalytic degradation of organic dyes in wastewater by chemically fabricated ZnO/Cs4SiW12O40 nanoheterojunction

Nanosized heterojunction is an attractive nanophotocatalyst for removing organic pollutants under activation by simulated sunlight. Herein, we synthesized a ZnO/Cs4SiW12O40 nanoheterojunction through a chemical approach. ZnO nanoparticles (NPs) with a diameter of approximately 200 nm were prepared by the hydrothermal method, while Cs4SiW12O40 nanospheres were synthesized by a solution route. The band gap of the constructed ZnO/Cs4SiW12O40 nanoheterojunction reached 2.65 eV, with an optical response threshold of 467 nm. Under simulated sunlight, the nanoheterojunction could degrade as much as 85.7% of Rhodamine B (RhB) in 90 min. Moreover, the nanoheterojunctions retained their excellent photocatalytic performance (76.9%) even after being recycled four times. The scavenging test of the free radical illustrated that the hole, hydroxyl radical, and superoxide anion radical are the main active radicals in the photocatalytic process. In addition, an electrochemical test demonstrated that the photogenerated carriers could be separated considerably well because the heterojunction structure has a suitable energy band alignment between ZnO and Cs4SiW12O40. The present work illustrates that ZnO/Cs4SiW12O40 nanoheterojunctions can prove highly useful for environmental remediation.

RapidLayout: Fast Hard Block Placement of FPGA-optimized Systolic Arrays Using Evolutionary Algorithm

Evolutionary algorithms can outperform conventional placement algorithms such as simulated annealing, analytical placement, and manual placement on runtime, wirelength, pipelining cost, and clock frequency when mapping hard block intensive designs such as systolic arrays on Xilinx UltraScale+ FPGAs. For certain hard-block intensive designs, the commercial-grade Xilinx Vivado CAD tool cannot provide legal routing solutions without tedious manual placement constraints. Instead, we formulate hard block placement as a multi-objective optimization problem that targets wirelength squared and bounding box size. We build an end-to-end placement-and-routing flow called RapidLayout using the Xilinx RapidWright framework. RapidLayout runs 5–6 \( \times \) faster than Vivado with manual constraints and eliminates the weeks-long effort to manually generate placement constraints. RapidLayout enables transfer learning from similar devices and bootstrapping from much smaller devices. Transfer learning in the UltraScale+ family achieves 11–14 \( \times \) shorter runtime and bootstrapping from a 97% smaller device delivers 2.1–3.2 \( \times \) faster optimizations. RapidLayout outperforms (1) a tuned simulated annealer by 2.7–30.8 \( \times \) in runtime while achieving similar quality of results, (2) VPR by 1.5 \( \times \) in runtime, 1.9–2.4 \( \times \) in wirelength, and 3–4 \( \times \) in bounding box size, while also (3) beating the analytical placer UTPlaceF by 9.3 \( \times \) in runtime, 1.8–2.2 \( \times \) in wirelength, and 2–2.7 \( \times \) in bounding box size.

Geometric Solutions for General Actuator Routing on Inflated-Beam Soft Growing Robots

Continuum and soft robots can leverage complex actuator shapes to take on useful shapes while actuating only a few of their many degrees of freedom. Continuum robots that also grow increase the range of potential shapes that can be actuated and enable easier access to constrained environments. Existing models for describing the complex kinematics involved in general actuation of continuum robots rely on simulation or well-behaved stress-strain relationships, but the non-linear behavior of the thin-walled inflated-beams used in growing robots makes these techniques difficult to apply. Here we derive kinematic models of single, generally routed tendon paths on a soft pneumatic backbone of inextensible but flexible material from geometric relationships alone. This allows for forward modeling of the resulting shapes with only knowledge of the geometry of the system. We show that this model can accurately predict the shape of the whole robot body and how the model changes with actuation type. We also demonstrate the use of this kinematic model for inverse design, where actuator designs are found based on desired final robot shapes. We deploy these designed actuators on soft pneumatic growing robots to show the benefits of simultaneous growth and shape change.

Transitioning an Existing SDI Facility to IP

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Not all media production facilities have the ability to create a new “greenfield” Internet Protocol (IP) production campus. Many facilities need to grow and transition organically over time and, as more production equipment becomes IP or IP ready, it makes sense to begin to purchase equipment that has SMPTE ST 2110 interfaces. Initially, this means putting IP gateways around the products that are put into service. A good example may be that a facility needs to grow, and the routing matrix size required exceeds what is tenable with serial digital interface (SDI) (SMPTE ST 259M). A SMPTE ST 2110 routing solution may make both financial sense and also planning sense for the future of that facility. In this article, we look at what it takes to make those initial steps to IP, then the steps eventually required to transition to an all-IP media campus, and to truly take advantage of the capabilities and convergences that an IP facility can offer</i> .