Cluster System Research Articles

Proactive resource management for cloud of services environments

Microservices offer advantages such as better fault isolation, smaller and faster deployments, scalability, and speeding up the development of new applications through the composition of services. However, its large-scale use and specific requirements increase the challenges of monitoring and management. To meet these challenges, we propose a monitoring and management system for microservices, containers and container clusters that autonomously predicts load variations and resource scarcity, which is capable of making new resources available in order to ensure the continuity of the process without interruptions. Our solution’s architecture allows for customizable service-specific metrics that are used by the load predictor to anticipate resource consumption peaks and proactively allocate them. In addition, our management system, by identifying/predicting low demand, frees up resources making the system more efficient. We evaluated our service management solution in the AWS environment, environment characterized by high mobility, dynamic topologies caused by disconnection, dropped packets and delay issues. Our results show that our solution improves the efficiency of escalation policies, and reduces response time by improving the QoS/QoE of the system.

Acute Effects of Different Conditioning Activities on Amateur Soccer Players.

Several warm-up activities are used to prepare soccer players for training and games. However, few studies have focused on comparing different activities (strength vs. stretching) in young and amateur athletes, especially for performance improvement in explosive actions. Thus, in order to compare the effect of four conditioning activities on jump and sprint performances, 12 soccer athletes (age: 19±0.8; weight (kg): 72.8±8.0; height (cm): 180±6.7) performed four warm-up activities: strength exercise (cluster system), combined exercise, plyometric exercise, and static stretching (control). The countermovement jump (CMJ) and 30-meter run (30-m Sprint) were performed 10 min after each experimental condition. A ONE-WAY ANOVA test of repeated measures was conducted with a Tukey's post-hoc test to compare the conditions. The strength conditioning activity protocol (33.68±2.87) showed a significant difference for the CMJ from static stretching (30.96±3.16) (p>0.05). There were significant differences regarding the 30-m Sprint test between strength conditioning (4.72±0.19) and combined activities (4.71±0.21) compared to static stretching (4.84±0.21) (p>0.05). In conclusion, the combined conditioning activity and strength protocols can be chosen in warm-up activities instead of static stretching (control condition) for improved immediate sprint and jump abilities in amateur soccer players.

Clustering systems of phylogenetic networks.

Rooted acyclic graphs appear naturally when the phylogenetic relationship of a set X of taxa involves not only speciations but also recombination, horizontal transfer, or hybridization that cannot be captured by trees. A variety of classes of such networks have been discussed in the literature, including phylogenetic, level-1, tree-child, tree-based, galled tree, regular, or normal networks as models of different types of evolutionary processes. Clusters arise in models of phylogeny as the sets [Formula: see text] of descendant taxa of a vertex v. The clustering system [Formula: see text] comprising the clusters of a network N conveys key information on N itself. In the special case of rooted phylogenetic trees, T is uniquely determined by its clustering system [Formula: see text]. Although this is no longer true for networks in general, it is of interest to relate properties of N and [Formula: see text]. Here, we systematically investigate the relationships of several well-studied classes of networks and their clustering systems. The main results are correspondences of classes of networks and clustering systems of the following form: If N is a network of type [Formula: see text], then [Formula: see text] satisfies [Formula: see text], and conversely if [Formula: see text] is a clustering system satisfying [Formula: see text] then there is network N of type [Formula: see text] such that [Formula: see text].This, in turn, allows us to investigate the mutual dependencies between the distinct types of networks in much detail.

Principal's Strategy in Managing Tahfiz Learning

This study aims to explain the principal's strategy in developing Tahfiz Qur'an learning at MI Miftahul Ulum Ringinlarik. Data sources were obtained from teachers, students, and vice curriculum at MI Miftahul Ulum Ringinlarik. Observation, interviews, and documentation carry out data collection techniques. The MI Miftahul Ulum Ringinlarik observation stage was carried out in January 2023 and finished in February 2023. During the interview, principals, managers, teachers, and students were respondents at MI Miftahul Ulum Ringinlarik. At the Documentation stage, activities, lesson plans, and syllabi have been collected to become data on the strategy of managing the Tahfiz program as a flagship program at MI Miftahul Ulum Ringinlarik. Data analysis was carried out with the stages of data reduction, data presentation, conclusion, and verification. The study results show that the school principal's role in managing the Tahfiz program at MI Miftahul Ulum Ringinlarik is carried out by implementing a cluster system known as the madrasa system, which is carried out intensively. The principal's strategy in managing the Tahfiz program at MI Miftahul Ulum Ringinlarik is carried out by setting significant goals and analyzing the current conditions and situation at the planning stage. To support the implementation of the Tahfiz program, school principals make improvements to teaching staff, school facilities, and infrastructure and monitor program implementation. Evaluation of program stages at the end of the school year with establishing standards and methods for measuring teacher performance, comparing results with established standards/targets, and taking corrective action by identifying supporting and inhibiting factors.

ПОДРОСТОК С ХРОНИЧЕСКОЙ БОЛЕЗНЬЮ ПОЧЕК — ГОТОВНОСТЬ К ПЕРЕВОДУ ВО ВЗРОСЛУЮ НЕФРОЛОГИЧЕСКУЮ СЛУЖБУ ЗДРАВООХРАНЕНИЯ И ТРУДНОСТИ ПЕРЕХОДНОГО ПЕРИОДА: ОБЗОР ЛИТЕРАТУРЫ, СОБСТВЕННЫЕ НАБЛЮДЕНИЯ

Transition of an adolescent patient with chronic kidney disease (CKD) from pediatric to adult healthcare system is an urgent problem Worldwide. The purpose of this research was to generalize the idea of readiness of adolescents with CKD to transfer into adult nephrology healthcare system, to describe the challenges of such transition period and to determine the roles of participants in the process and their mutual interactions in order to develop and implement the working regional model for organizing the transition of adolescents with CKD within a clustered system of provision of specialized healthcare services. Materials and methods used: a single-center cross-sectional questionnaire surveying of adolescents and young adults with CKD regarding their readiness to transition in two observation groups was carried out on the basis of both adult and pediatric sections of the Samara Oblast Regional Clinical Hospital named after V.D. Seredavin (Samara, Russia) in Jan. 2021-March 2023. Group 1 consisted of young adults aged 18 to 22 y/o with CKD stages 2 to 3; and Group 2 included adolescents aged 13 to 18 y/o with CKD stages 2 to 5. The results were then evaluated with the TRxANSITION Index (formerly TRxANSITION Scale), PedsQL and the SF-36 questionnaire. Adolescents’ parents/caretakers took a survey on the independence of their children as well. Results: the data on the insufficient independence of adolescents were obtained, as follows: 66.7% [34.9-90.1%] (n=8) “never” took medication on their own, 50.0% [21.1-78.9%] (n=6) have never asked their physicians questions (p<0.001), 50.0% [21.1-78.9%] (n=6) “never” and 33.3% [9.9-65.1%] (n=4) “almost never” did they agree to meet with the physician (p=0.005). Adolescents experienced difficulties in both communicating and working together with a physician: 33.3% [9.9-65.1%] (n=4) and 25.0% [5.5-57.2%] (n=3) “difficult,” respectively; 50.0% [21.1-78.9%] (n=6) and 58.3% [27.7-84.8%] (n= 7) “almost difficult,” respectively (p<0.001). On the other hand, “almost everything” and “everything” do they know about their health status 47.1% [23.0-72.2%] (n=8) and 35.4% [14.2-61.7%] (n=6), respectively, of young adults with CKD vs. adolescents (p<0.001). Conclusion: structurization of the participants’ roles in the communication system “patient and his family members - medicine professionals - psychologists - social workers” contributes to the stabilization of an adolescent with CKD during the transition period.

Usage of a computer cluster for physics simulations using bullet engine and OpenCL

The study focuses on using a computer cluster for implementing real-time physical simulations, responding to a growing need for such use in various sectors, including medicine, video processing, automated transport management, robotics, and visualisation. The object of research is cluster and cloud technologies for conducting costly physical simulations for specific sectors, particularly high-budget and entertainment ones, such as cinematography and interactive entertainment. Research methods include using a modified Bullet engine to carry out physical simulations, integrated with OpenCL to work with the cluster. The choice of these technologies was determined by their high performance and adaptability to cluster systems. The research was based on a typical Bullet framework’s benchmark falling tower scene with the primary goal of measuring computational performance in frames per second. Results showed that the use of clusters is not advisable in environments with a low network throughput and the use of non-uniform computers. Under those conditions, simulations using a cluster become unstable with many objects and contacts between them and show a degradation in performance by an average of 50–60 % (to values of 10–20 frames per second). Despite the intermediate results of calculations on the cluster, the study met the expectations within the goals set and resources available. These results have significant implications for the further development of cluster and cloud technologies in physical simulations, providing valuable information about the limitations and capabilities of these systems.

Comparing Globular Cluster System Properties with Host Galaxy Environment* * Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the Data Archive at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. These observations are associated with programs 14219 and 15265.

We present Hubble Space Telescope photometry in the optical (F475X) and near-infrared (F110W) bands of the globular cluster (GC) systems of the inner halos of a sample of 15 massive elliptical galaxies. The targets are selected from the volume-limited MASSIVE survey, and chosen to sample a range of environments from sparsely populated groups to the brightest cluster galaxies in dense clusters. We also present a quantitative model of the relation between (F475X − F110W) color and cluster metallicity [M/H], using simulated GCs. Because much of the GC population in such galaxies is built up through accretion, the metallicity distribution of the GC systems might be expected to vary with galaxy environment. The photometry is used to create a completeness-corrected metallicity distribution for each galaxy in the sample, and to fit a double Gaussian curve to each histogram in order to model the two standard red and blue subpopulations. Finally, the properties of the GC metallicity distribution are correlated against galaxy environment. We find that almost no GCS properties and host galaxy environmental properties are correlated, with the exception of a weak but consistent correlation between blue fraction and nth-nearest-neighbor surface density. The results suggest that the systemic properties of the GC systems, at least in the inner to midhalo regions, are influenced more strongly by the local environment at early times, rather than by the environmental properties we see today.

Distributed reconfigurable model predictive control based load frequency control of microgrid clusters with dynamic topology

Microgrid cluster topology undergoes a dynamic change when an individual microgrid is inserted or removed because of cooperation/non-cooperation issues at certain operating conditions. In this paper, a distributed reconfiguration model predictive control (DRMPC) based frequency control of microgrid clusters considering dynamic topology is presented. Firstly, for the microgrid clusters system with dynamic topology, a predictive model containing the state reference sequence of adjacent sub-microgrids is established to meet the topology adjustment in real time. Secondly, considering the output power constraint of each distributed generation, a DRMPC controller for minimizing the frequency deviation is designed. When the topology is switched, the power deviation of the tie-line is selected as the judgment to ensure that there is no power interaction between sub-microgrids. When the judgment cannot be satisfied in the optimization process, considering the adjacent sub-microgrids' frequency limit and the power deviation of the tie-line convergence requirement between sub-microgrids, a reconstructed optimization function is proposed to accomplish topology switching. Meanwhile, the closed-loop stability of the proposed DRMPC scheme is verified by introducing the terminal equation constraint. Finally, the proposed control strategy is verified by a cluster of five sub-microgrids connected via tie lines.

Capacitating Strategies to Promote Climate Resilient Coconut-based Farming Systems (CR-CBFS) in Vulnerable Coconut Communities of the Philippines

Climate extremes that continuously bring unpredictable weather patterns particularly strong typhoons and rainfall events devastated many coconut-producing areas in the Philippines. These weather patterns affected the livelihood of farmers and the whole supply chain of the coconut industry. Adoption of a clustering system of farmers is a key approach to sustaining the growing needs of the coconut industry. This will ensure the continuous engagement of farmers in coconut farming where good agricultural practices are performed in developing products that meet the domestic and international market standards. However, clustering of climate-resilient integrated farming systems through participation in multi-purpose cooperatives requires scientific guidance, market-driven production and market linkages.This paper integrates learnings from past coconut and coconut-based farming system (CBFS) projects. Further, it highlights the learning-by-doing approach where core trainers are developed to train farmer groups in designing location-specific climate-resilient CBFS using a hybrid curriculum of CR – Farmers Field School (CR – FFS) and Farmer Business School. This improvement in the integrated curriculum can change individual and community perspectives, improve farm practices, reduce the impacts of climate-related hazards and risks, provide sustainable livelihoods and enhance farmers’ participation in agri-enterprises. The CR-CBFS season-long training exercises will integrate climate risks and forecasts in farmers’ decision-making, provide technical and business lenses for improved farm productivity and profitability through the integration of complementary enterprises such as intercropping, livestock, value-adding and processing that consider environmental, socio-cultural and economic factors.

An Energy Efficient On-Off Keying Transmitted Reference Pulse Cluster System for UWB Communications

In order to overcome the long wideband delay line issue of conventional transmitted reference (TR) ultra-wideband (UWB) systems, a transmitted reference pulse cluster (TRPC) structure was proposed and many related studies have been done. This paper presents a new on-off keying TRPC (OOK-TRPC) structure which can save half of the transmitting energy of the original TRPC scheme. Based on this new structure, an energy detector (ED) is applied and estimating methods for its symbol decision threshold are designed under different signal-to-noise ratio conditions. Analytical and simulation results show the energy efficiency of the proposed OOK-TRPC ED scheme. Therefore, from a practical point of view, the designed OOK-TRPC ED, which also can be applied to some previous TRPC related studies, is considered as a highly recommended practice, particularly in wireless sensor networks, internet of things, and wireless body area networks etc, where energy-saving has been becoming increasingly crucial.

Galactic properties that favour star cluster formation: a statistical view

ABSTRACT The presence or absence of star clusters in galaxies, and the properties of star cluster populations compared to their host galaxy properties, are important observables for validating models of cluster formation, galaxy formation, and galaxy assembly. In this work, we apply a Bayesian approach to fit two models to data from surveys of young clusters in star-forming galaxies. The first model is a logistic regression, which allows us to include galaxies which do not have any young clusters. The second model is a hurdle model, which includes galaxies with zero clusters and also incorporates information about the total mass in the cluster system. We investigate two predictors (star formation rate and total stellar mass in the galaxy) and look at clusters younger than 10 or 100 Myr. We find that in all cases, star formation rate is the better predictor for both the probability of hosting clusters and the total mass in the cluster system. We compare our results to similar models for old globular clusters, and conclude that star cluster formation was more abundant and more efficient at higher redshifts, likely because of the high gas content of galaxies at that time.

Formation of Cluster Systems in Chaotic Condensed Media

Purpose. The study of cluster formation in a system of chaotically moving and interacting particles taking into account the Efimov effect and the "golden" section.Methods. Methods of mathematical modeling, quantum mechanics, a model of solid spheres, and a cluster model were used.Results. Within the framework of the proposed work, it is noted that in a three-particle system of particles, it is possible to form their spatial configuration in the form of a "golden" triangle, and in the case of an excited state of two particles, the third particle is far enough away from the other two, it is this configuration that corresponds to the conditions for the occurrence of the Efimov effect in a three-particle system.Based on the mathematical formalism of the description of self-organization processes in the work, it is shown that in chaotic environments within the framework of the Efimov model, with the involvement of the "golden" section in the mutual arrangement of three interacting particles, it is possible to form disk-shaped clusters containing a "magic" number of particles. In the structure of these clusters, the formation of quantum-dimensional regions in the form of a torus is possible. The parameters of such areas are defined.Conclusion. The described model of the formation and decay of disk-shaped clusters, taking into account the Efimov effect and the "golden" section rule, allows us, without resorting to a complex solution of equations in the three-body problem, to obtain important relations following from strict theories. The proposed approach implies the possibility of self-organization of clusters and the formation of quantum-dimensional regions in their structure, for example, in the form of a torus with a potential well, capable of capturing charged particles and determining their energy spectrum, as well as explaining the appearance of spectral bands in the IR spectra of substances.The proposed approach may be of practical importance, for example, for predicting the IR spectra of liquids, the presence of quantum dots in liquids with a wide spectrum of excitation from UV to IR radiation.

Quantifying cumulative changes in water quality caused by small floodgates in Taihu Lake Basin — A case in Wuxi

Small floodgates in the river network area own some characteristics: considerable quantity, wide range and short adjustment time, and intercepts the one-dimensional constant flow of rivers, which induce a great impact on riverine water quality. In this study, a typical urban floodgate-controlled reach was selected, and analyzed through the monthly data of four pollutant indicators TN, TP, CODMn and NH3-N at six sampling sites S1–S6 in 2016–2018. The principal component analysis and correlation analysis showed that TP was a representative indicator and there was a positive correlation between various pollutants. The difference test and linear regression showed that the concentration of pollutants at different sampling points varied greatly, and the pollutant concentrations in the longitudinal direction of the river showed a cubic-linear regression. The cluster system and CCME WQI showed that the water quality in the urban floodgate-controlled reach is “marginal” state, and TN and NH3-N are severely exceeding the standard. The “cumulative changes” of the floodgate on the pollutant input to the environment appeared spatial heterogeneity.

Multimicrogrid collaborative economic scheduling method based on the FISCO BCOS blockchain

AbstractWith the advancement of carbon peaking and carbon neutrality goals, microgrid clusters have attracted widespread attention due to their high stability and energy efficiency. This article proposes a scheduling architecture for microgrid clusters that integrates blockchain smart contracts, consensus mechanisms, and encryption technologies to address the issues of data trust, privacy protection, and security reliability in microgrid clusters. An economic adjustment model for microgrid clusters is constructed that combines economic and environmental objectives. Finally, based on the RPBFT (Rotating Proof of Believability) algorithm and group architecture of FISCO BCOS blockchain technology, an economic scheduling method for microgrid clusters is designed. The authors built a microgrid cluster model on the FISCO BCOS blockchain platform and conducted experiments on the effectiveness, economy, fault tolerance, and scalability of economic scheduling methods. The experimental results showed that the economic scheduling method proposed in this paper can effectively reduce the risk of nodes tampering with data in a microgrid cluster system, ensure the privacy of submicrogrids, and support the deployment of large‐scale microgrid clusters, the realization of multiparty collaborative autonomy and the stable, low‐carbon, economic operation of microgrid clusters.

An Alternate GPU-Accelerated Algorithm for Very Large Sparse LU Factorization

The LU factorization of very large sparse matrices requires a significant amount of computing resources, including memory and broadband communication. A hybrid MPI + OpenMP + CUDA algorithm named SuperLU3D can efficiently compute the LU factorization with GPU acceleration. However, this algorithm faces difficulties when dealing with very large sparse matrices with limited GPU resources. Factorizing very large matrices involves a vast amount of nonblocking communication between processes, often leading to a break in SuperLU3D calculation due to the overflow of cluster communication buffers. In this paper, we present an improved GPU-accelerated algorithm named SuperLU3D_Alternate for the LU factorization of very large sparse matrices with fewer GPU resources. The basic idea is “divide and conquer”, which means dividing a very large matrix into multiple submatrices, performing LU factorization on each submatrix, and then assembling the factorized results of all submatrices into two complete matrices L and U. In detail, according to the number of available GPUs, a very large matrix is first divided into multiple submatrices using the elimination tree. Then, the LU factorization of each submatrix is alternately computed with limited GPU resources, and its intermediate LU factors from GPUs are saved to the host memory or hard disk. Finally, after finishing the LU factorization of all submatrices, these factorized submatrices are assembled into a complete lower triangular matrix L and a complete upper triangular matrix U, respectively. The SuperLU3D_Alternate algorithm is suitable for hybrid CPU/GPU cluster systems, especially for a subset of nodes without GPUs. To accommodate different hardware resources in various clusters, we designed the algorithm to run in the following three cases: sufficient memory for GPU nodes, insufficient memory for GPU nodes, and insufficient memory for the entire cluster. The results from LU factorization test on different matrices in various cases show that the larger the matrix is, the more efficient this algorithm is under the same GPU memory consumption. In our numerical experiments, SuperLU3D_Alternate achieves speeds of up to 8× that of SuperLU3D (CPU only) and 2.5× that of SuperLU3D (CPU + GPU) on the hybrid cluster with six Tesla V100S GPUs. Furthermore, when the matrix is too big to be handled by SuperLU3D, SuperLU3D_Alternate can still utilize the cluster’s host memory or hard disk to solve it. By reducing the amount of data exchange to prevent exceeding the buffer’s limit of the cluster MPI nonblocking communication, our algorithm enhances the stability of the program.

Clinical feasibility of radiofrequency ablation using novel adjustable separable electrodes with a multipurpose needle for treating small hepatocellular carcinomas: a prospective single center study

Background The novel separable clustered electrode system with two adjustable active tips (ICAEs) and a fine multipurpose needle (MPN) for in situ temperature monitoring and adjuvant agent injection was developed and validated in an animal study. The purpose of this study was to evaluate the technical efficacy and complication of the novel electrode system for patients who have small HCC. Methods In this prospective, single-center clinical trial, ten participants with 14 small (≤ 2 cm, BCLC 0-A) HCCs referred for RFA were enrolled. A novel electrode system consisting of two ICAEs and one MPN with a thermometer and side holes was used for RFA. The RF energy was delivered using a multichannel RF system combining bipolar and switching monopolar modes. Technical success, efficacy, and complications were evaluated on immediate and one-month follow-up CT. Results Technical success was achieved in 92.9% (13/14) of tumors. One participant withdrew consent after RFA, and technical efficacy was achieved in 91.7% (11/12) of tumors. None showed thermal injury to nontarget organs. All patients were discharged the day after RFA without major complications. The active electrode lengths were adjusted in 60% (6/10) of patients during the procedure to tailor the ablation zone (83.3%, n = 5) or treat two tumors with different sizes (16.7%, n = 1). MPN was capable of continuous temperature monitoring during all ablations (100%, 14/14). Conclusions RFA using a novel electrode system showed acceptable technical efficacy and safety in patients with small HCCs. Further comparative studies are needed for the investigation of the system’s potential benefits compared to conventional electrodes.

THE MECHANISM OF DIGITAL TRANSFORMATION OF AGRICULTURE

<em>The article is devoted to the study of the construction of the mechanism of digital transformation of agriculture when building a management system for agro-industrial clusters. The new realities of socioeconomic relations at the international level and the level of individual states require involvement in digitalization trends. That makes it necessary to study the mechanism of digital transformation of the branches of the national economy, including agriculture. The use of new IT technologies contributes to the formation of competitive advantages and directions for the development of the industry. On the other hand, it acts as an incentive to activate and increase the efficiency of the management system by stimulating the introduction of achievements and trends in modern science and technology, which is especially important in the digitalization and digital transformation of agriculture. Accumulation, systematization, and generalization of traditional-historical and modern IT technologies and management system techniques is an element of integration and activation of network, cluster, and other innovative mechanisms in the modernization of the management system in the agro-industrial complex. The development of the agriculture digital transformation will allow to specify of the tools and methods of updating and building integrated management systems of system-forming innovative agro-clusters will allow to generalize of the theoretical and methodological foundations, and develop recommendations for the formation of a management model of system-forming innovative agro-clusters using the concept of "triple helix" and modern digital technologies in the field of agro-industrial complex of Russia.</em>

Three-stage fuzzy-metaheuristic algorithm for smart cities: Scheduling mobile charging and automatic rule tuning in WRSNs

Recent breakthroughs in wireless power transfer technology have been promising for empowering and enabling seamless operation of wireless sensors and developing sustainable systems such as wireless rechargeable sensor networks (WRSNs). Relying on this technology and focusing on WRSNs, this paper proposes an adaptive charging scheduling algorithm called the three-stage fuzzy metaheuristic algorithm (TSFM) by using the whale optimization algorithm (WOA) and a multiobjective function designed to meet the application requirements of WRSNs in smart cities. The TSFM algorithm benefits from the WOA for the automated configuration and optimization of the fuzzy rule-base table in a three-stage fuzzy inference system for clustering, routing, and scheduling mobile charging simultaneously. Unlike the other methods, the TSFM algorithm determines the ratio of effect of fuzzy input parameters of every stage based on application and environment in addition to considering effective parameters for every stage, especially for charging scheduling (e.g., the energy of a charge-request node, the distance between a charge-request node and a mobile charging (MC), the density of a charge-request node, the average energy consumption rate of a charge-request node, and the time elapsed after a charge request). Furthermore, for the proper distribution of energy in a network, better responsiveness, and optimal use of a charging robot, two energy thresholds are defined in the TSFM algorithm, namely as the charging request issue threshold and the charging operation completion threshold. The TSFM algorithm is adaptable to applications, environments, and requirements of WRSNs not only by using the features of nodes (as the fuzzy input parameters) but also by considering the application-specific features, environments, and infrastructure (e.g., network size, number of nodes, base station (BS) positions, and designer’s goals) within the process of optimizing tunable parameters. The TSFM algorithm was evaluated and compared with some common methods such as FCFS, NJNP, and ESS in terms of functional metrics such as energy utility, charging latency, survival rate, death rate of nodes, system stability, number of packets received by BS, number of request nodes, number of alive nodes, average residual energy, adaptability analysis, and statistical validation in two scenarios and six applications. According to the simulation results, the proposed TSFM algorithm improved the performance criteria and outperformed the other methods by far in terms of application. For instance, the TSFM algorithm improved the minimum system stability rate by 167%, 0.73%, and 123% compared with FCFS, NJNP, and ESS methods, respectively.

Islanding Detection in Grid-Connected Urban Community Multi-Microgrid Clusters Using Decision-Tree-Based Fuzzy Logic Controller for Improved Transient Response

The development of renewable-energy-based microgrids is being considered as a potential solution to lessen the unrelenting burden on the centralized utility grid. Furthermore, recent studies reveal that integrated multi-microgrid cluster systems developed in urban communities maximize the effectiveness of microgrids and greatly decrease the utility grid dependence. However, due to the uncertain nature of renewable energy sources and frequent load variations, these systems face issues with unintentional islanding operations. This can create severe damage to the microgrid’s performance in its stable operating condition and lead to undesired transient responses. Hence, islanding must be identified rapidly to take preventive measures to address the issue. This requires the development of a suitable anti-islanding technique that is faster in terms of accuracy and timely detection. With this intention, this paper proposes a decision-tree-based fuzzy logic (DT-FL) controller for the rapid identification of islands in an urban community multi-microgrid cluster. The DT-FL controller’s operation includes two steps. First, the decision tree extracts the electrical parameters at the point of common coupling of the multi-microgrid system. Second, these extracted parameters are utilized for the online tuning of the fuzzy logic controller, for the fast detection of islanding. The multi-microgrid cluster under study, along with the proposed islanding technique, is implemented in the MATLAB-2021a software. The efficacy of the proposed DT-FL controller is validated by comparing its performance with that of the conventional fuzzy logic controller under different test scenarios. From the results, it is observed that the proposed DT-FL controller shows superior performance in terms of the islanding detection time as well as the transient response of the system when compared with the conventional controller.

An integrated ultra-high vacuum cluster for atomic-scale deposition, interface regulation, and characterization of spintronic multilayers

The study of interface spin effects in spintronic multilayer films requires distinguishing the effects generated by different interfaces. However, testing in atmospheric conditions requires a capping layer to protect the films, which introduces new interfaces and limits the study of interface spin-dependent effects. To address this challenge, we have developed an integrated ultra-high vacuum cluster system that includes magnetron sputtering equipment, ion irradiation equipment, and time-resolved magneto-optical Kerr effect (TR-MOKE) equipment. Our sputtering system integrates 12 cathodes in a single chamber, allowing the co-sputtering of four targets. The ultimate vacuum can reach 1 × 10−10 mbar, and the deposition resolution of 0.1 nm can be achieved. Ion irradiation equipment can ionize to produce He+, and by screening and accelerating the implantation of He+ into multilayer films, ion scanning is realized, and up to 30 keV energy can be applied to the films. The TR-MOKE equipment can detect ultra-fast magnetic dynamics processes in vacuum conditions, and its external magnetic field can be rotated 360°. Our vacuum cluster system connects the three subsystems, allowing in situ film deposition, regulation, and characterization. By accurately detecting the effects of different layers, the system can distinguish the interface effects of multilayers. Experimental results demonstrate that the three subsystems can work independently or coordinate to observe the interface effects of multilayers.