A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center

As cloud computing usage grows,cloud data centers play an increasingly important role.To maximize resource utilization,ensure service quality,and enhance system performance,it is crucial to allocate tasks and manage performance effectively.The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers.The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies,categories,and gaps.A literature review was conducted,which included the analysis of 463 task allocations and 480 performance management papers.The review revealed three task allocation research topics and seven performance management methods.Task allocation research areas are resource allocation,load-Balancing,and scheduling.Performance management includes monitoring and control,power and energy management,resource utilization optimization,quality of service management,fault management,virtual machine management,and network management.The study proposes new techniques to enhance cloud computing work allocation and performance management.Short-comings in each approach can guide future research.The research’s findings on cloud data center task allocation and performance management can assist academics,practitioners,and cloud service providers in optimizing their systems for dependability,cost-effectiveness,and scalability.Innovative methodologies can steer future research to fill gaps in the literature.

Optimization Management of Industrial Organizations Based on Performance Indicators

This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.

Research and Analysis on the Application of Strategic Performance Management in Enterprises

In today’s competitive business environment,strategic performance management(SPM)is crucial for continuous growth and innovation.Therefore,it is important to realize the advantages of SPM in enterprise applications.This paper analyzes the theoretical basis,implementation framework,and application effects of SPM in enterprises by examining actual cases from different industries.It reveals the core elements of an effective performance management system,including clear goal setting,reasonable performance indicators,and periodic performance evaluations.Additionally,the paper examines the impact of China’s specific economic policy environment on the implementation of SPM and proposes strategies to optimize performance management practices,ultimately promoting the achievement of strategic goals.This paper provides specific and personalized practical guidance for enterprises.

Construction Method for Performance Management Curriculum Content System Based on Knowledge Graph

Performance Management is the core course of human resource management major,but its knowledge points lack multi-dimensional correlations.There are problems such as scattered content and unclear system,and it is urgent to reconstruct the content system of the course.Knowledge graph technology can integrate massive and scattered information into an organic structure through semantic correlation and reasoning.The application of knowledge graph to education and teaching can promote scientific and personalized teaching evaluation and better realize individualized teaching.This paper systematically combs the knowledge points of Performance Management course and forms a comprehensive knowledge graph.The knowledge point is associated with specific questions to form the problem map of the course,and then the knowledge point is further associated with the ability target to form the ability map of the course.Then,the knowledge point is associated with teaching materials,question bank and expansion resources to form a systematic teaching database,thereby giving the method of building the content system of Performance Management course based on the knowledge map.This research can be further extended to other core management courses to realize the deep integration of knowledge graph and teaching.

Analysis of the management and therapeutic performance of diabetes mellitus employing special target

Diabetes mellitus (DM) is a chronic metabolic condition characterized predominantlyby hyperglycemia. The most common causes contributing to the pathophysiologyof diabetes are insufficient insulin secretion, resistance to insulin’stissue-acting effects, or a combination of both. Over the last 30 years, the globalprevalence of diabetes increased from 4% to 6.4%. If no better treatment or cure isfound, this amount might climb to 430 million in the coming years. The major fact-ors of the disease’s deterioration include age, obesity, and a sedentary lifestyle.Finding new therapies to manage diabetes safely and effectively without jeopardizingpatient compliance has always been essential. Among the medicationsavailable to manage DM on this journey are glucagon-like peptide-1 agonists,thiazolidinediones, sulphonyl urease, glinides, biguanides, and insulin-targetingreceptors discovered more than 10 years ago. Despite the extensive preliminarystudies, a few clinical observations suggest this process is still in its early stages.The present review focuses on targets that contribute to insulin regulation andmay be employed as targets in treating diabetes since they may be more efficientand secure than current and traditional treatments.

Traffic Incident Management Performance Measures: Ranking Agencies on Roadway Clearance Time

This study develops a procedure to rank agencies based on their incident responses using roadway clearance times for crashes. This analysis is not intended to grade agencies but to assist in identifying agencies requiring more training or resources for incident management. Previous NCHRP reports discussed usage of different factors including incident severity, roadway characteristics, number of lanes involved and time of incident separately for estimating the performance. However, it does not tell us how to incorporate all the factors at the same time. Thus, this study aims to account for multiple factors to ensure fair comparisons. This study used 149,174 crashes from Iowa that occurred from 2018 to 2021. A Tobit regression model was used to find the effect of different variables on roadway clearance time. Variables that cannot be controlled directly by agencies such as crash severity, roadway type, weather conditions, lighting conditions, etc., were included in the analysis as it helps to reduce bias in the ranking procedure. Then clearance time of each crash is normalized into a base condition using the regression coefficients. The normalization makes the process more efficient as the effect of uncontrollable factors has already been mitigated. Finally, the agencies were ranked by their average normalized roadway clearance time. This ranking process allows agencies to track their performance of previous crashes, can be used in identifying low performing agencies that could use additional resources and training, and can be used to identify high performing agencies to recognize for their efforts and performance.

Optimal Machine Learning Enabled Performance Monitoring for Learning Management Systems

Learning Management System(LMS)is an application software that is used in automation,delivery,administration,tracking,and reporting of courses and programs in educational sector.The LMS which exploits machine learning(ML)has the ability of accessing user data and exploit it for improving the learning experience.The recently developed artificial intelligence(AI)and ML models helps to accomplish effective performance monitoring for LMS.Among the different processes involved in ML based LMS,feature selection and classification processesfind beneficial.In this motivation,this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring(GSO-MFWELM)technique for LMS.The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS.The pro-posed GSO-MFWELM technique involves GSO-based feature selection techni-que to select the optimal features.Besides,Weighted Extreme Learning Machine(WELM)model is applied for classification process whereas the parameters involved in WELM model are optimallyfine-tuned with the help of May-fly Optimization(MFO)algorithm.The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance.The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects.The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.

Assessing Financial Management Practices and Accounting Mechanisms in Agricultural Cooperatives:A Case Study From Nepal

The study focuses on assessing the financial management practices and accounting mechanisms in agricultural cooperatives in Tulsipur Sub-Metropolitan,Dang District,Nepal with a focus on understanding their implications for financial performance and organizational effectiveness.The sample size of total cooperatives(n=46)was divided into Savings and Credit Cooperatives(n=18)and Multipurpose Cooperatives(n=28),respectively,with a total number of respondents(n=138)categorized into managing directors,employees,and general members.Using a mixed-methods approach that combines quantitative analysis of financial data with qualitative insights gathered through interviews and surveys,the study emphasizes the importance of modern financial practices,improved reporting mechanisms,and relevant staff training for long-term sustainability.Recommendations include the integration of criteria and evaluation tools to assess cooperative performance,with Hamro Pahunch Multipurpose Cooperative identified as a high performer.Emphasizing the need for robust financial management strategies to navigate the complexity of the agricultural sector,manage risks,and achieve sustainable development,the study notes frequent preparation of financial management reports on a monthly and annual basis,and predominantly annual accounting management.Most cooperatives are using computerized models to present financial positions,but face challenges such as lack of marketing infrastructure,cooperative skills,and technical support.Ultimately,the study advocates for educating policy makers,cooperative leaders,practitioners and stakeholders on the role of effective financial management and accounting in enhancing the resilience,expansion and socio-economic impact of agricultural cooperatives,thereby fostering their long-term prosperity and viability as drivers of rural development and empowerment.

ENERGY STATE APPROACH TO THE INTEGRATED FLIGHT PERFORMANCE MANAGEMENT OF COMMERCIAL AIRCRAFT

The integrated aircraft flight performance management techniques are discussed in this paper based on the point-mass energy state approximation principle. The flight performance optimization algorithms, developed with energy state approximation approach, are first introduced, the functionally integrated flight path/speed control system, so called total energy control system (TECS), is then discussed, and the guidance technique and algorithms, which relate the performance optimization results directly with the TECS, are analyzed and developed. Digital simulation results for a specific transport aircraft model demonstrate the satisfactory performances of the resulted flight performance management system.

Management Practices:Shaping Employee Satisfaction and Commitment in Large German Companies

The rapid evolution of the political,economic,and social landscape has generated increased interest in understanding the contextual application of management styles and behaviours toward employees.In this context,organizations must comprehend and assess employee satisfaction to enhance productivity and realize their strategic and economic goals.Therefore,this study aims to investigate the prevailing and significant management behaviours toward employees in large German companies and their impact on employee satisfaction and job commitment.To achieve the research objective,the study will employ a qualitative method to explore management behaviours toward employees.Data were collected through interviews with randomly selected managers from different companies and departments.The study aims to uncover discrepancies or variations in employee expectations regarding management behaviour.The findings will provide a better understanding of the most prevalent and significant management behaviours toward employees in large German companies and their impact on employee satisfaction and job commitment.The results will be valuable to management in adopting suitable leadership styles and improving employee satisfaction,leading to increased productivity and organizational performance.The research will contribute to the existing body of knowledge in the field of management and human resource management by providing insights into the impact of management behaviours on employees.It will also offer recommendations to management on how to enhance employee satisfaction and job commitment,leading to improved organizational performance.In conclusion,this study will investigate the prevailing management behaviours toward employees in large German companies and their impact on employee satisfaction and job commitment.

Contractor-Related Factors and Performance of Bridge Construction Projects Implemented by Kenya National Highways Authority (KeNHA) Kenya

The performance of bridge projects in Kenya is poor in terms of completion by schedule, cost, and quality (scope). Yet, there is less evidence of empirical research on what factors contribute to this outcome. This study aimed to bridge this gap by examining the effects of contractor-related factors on the performance of bridge construction projects in Kenya through a case study of the Bridge projects Implemented by the Kenya National Highway Agency (KeNHA). The theory of constraints (TOC) was adopted as its theoretical framework. Descriptive research was used, and the target population was 18 bridge construction projects, which were the units of analysis from 2012 to 2022. In each of these projects, 18 respondents, namely clients, consultants, contractors, engineers, environment and social guards, project managers, stakeholders, subcontractors, technical advisors, and inspectors, were included in a target population of 144 respondents. A census was conducted and a structured questionnaire was administered from which a response rate of 68% was achieved. The information was analyzed using descriptive, correlation, and multiple linear regression analysis. The contractor-related factors considered in the study were staff and management factors. The findings indicated that staff and management factors had a positive and significant outcome on performance of bridge construction projects. The study recommends continuous training and a safe learning environment for staff to improve their skills and performance in future projects. The study also recommends that a special category for bridge contractors be created in Kenya’s National Construction Authority rankings to ensure that only qualified contractors implement the Bridge projects.

Research on Improvement Strategies of Psychological Training and Stage Expressiveness in Percussion Performance

With the continuous development of music education,percussion,as an important form of performance,has led to growing attention to the psychological training of its performers.This study aims to explore how psychological factors in percussion performance impact stage expressiveness and to propose corresponding psychological training strategies.By analyzing relevant domestic and international literature,we found that psychological training not only enhances performers’confidence and alleviates performance anxiety but also contributes to an overall improvement in performance quality.This study shows that methods such as emotional management and cognitive restructuring exhibit promising application potential in practice.Therefore,exploring a systematic psychological training program is significant for improving the stage expressiveness of percussion performers.

Implications COVID-19 on Performance and Energy Management in the Production Electricity

The COVID-19 pandemic has directly impacted the electric power industry;the energy sector has experienced huge losses in electricity production.These losses have also affected the reliability of communication and employees’performance,hence destabilizing the electric power system.This article aims at achieving two objectives.First,analyzing the impact of the COVID-19 pandemic on the communication of performance(human error and human factors)and energy management in electricity production.Second,to develop a conceptual framework model to alleviate effects of the pandemic on the power sector and then improve energy management and human performance.This paper involves investigating the influence of the COVID19 pandemic on the global production of electricity in the first quarters of 2019 and 2020.A conceptual model was developed based on a case study.Additionally,to ensure reliability,a variable,namely COVID-19,was used as a moderator to examine the effects of the independent and dependent variables.The results show that scores for the internet of things(IoT)with awareness and communication(A&C)and workplace environment management were high with Cronbach’s alpha value of 0.87 for the IoT and 0.89 for A&C.These numbers are important indicators of factors that could affect performance and energy management and should not be overlooked by the top management.The results also indicate that the pandemic has had a direct effect on the electricity production sector,and the conceptual framework model revealed that COVID-19,as a moderator,has a direct effect on the variables that significantly affect the improvement of both energy management and employee performance.The case study’s results confirm the poor performance in power plant maintenance and operation,in which human error would increase especially in Iraqi power plants that have not yet adopted any internationally recognized standards for energy management.This paper contributes to the literature studying COVID-19’s impact on the electricity sector in two ways:first,by developing a model to assist the electricity production sector mitigating effects of the COVID-19 pandemic,and second,by providing a detailed investigation into the pandemic’s impact on the electricity sector’s global production.The findings are hoped to assist researchers and research centers in understanding the general and specific framework to manage the pandemic’s effects on electricity production.

Contractor Monitoring and Performance of Road Infrastructure Projects in Uganda: A Management Model

An understanding of the influence of contractor monitoring on performance of road infrastructural projects in Uganda provided an impetus for this study. The objectives of the study were to: assess the relationship between contractors monitoring and performance of national road infrastructure projects and the relationship between contractor monitoring components and performance of national road infrastructure projects in Uganda. Purposive sampling was employed in selecting the procurement professionals, engineers and simple random sampling was adopted in selecting private consultants, members of parliament and respondents from the civil society organizations. Data for this study were collected using a closed ended questionnaire and interviews. Some of the major finding from this study include: weak procurement rules which lead to awarding road projects to incompetent contractors;contractor monitoring being handled by unqualified, incompetent and inexperienced professionals;lack of contractors and contract supervisors appraisal system;delay of contractors payments which affects timelines in services delivery;lack of a strong internal project monitoring and evaluation mechanism at the Uganda National Roads Agency (UNRA). The research therefore recommends the establishment of an Independent Public Infrastructure Development and Monitoring Unit by government and adoption of systems that appraise both contractors and contract supervisors with clear disciplinary actions for unsatisfactory performance by the UNRA.

Dynamic performance management system

An integrated, efficient and effective performance management system, ＂dynamic performance management system＂, is presented, which covers the entire performance management process including measures design, analysis, and dynamic update. The analysis of performance measures using causal loop diagrams, qualitative inference and analytic network process is mainly discussed. A real world case study is carried out throughout the paper to explain how the framework works. A software tool for DPMS, Performance Analyzer, is also introduced.

Assessing Air Traffic Management Performance Interdependencies through Bayesian Networks： Preliminary Applications and Results

The performance model proposed by this study represents an innovative approach to deal with performance assessment in ATM （air traffic management）. It is based on Bayesian networks methodology, which presents several advantages but also some drawbacks as highlighted along the paper. We illustrate the main steps required for building the model and present a number of interesting results. The contribution of the paper is two-fold： （1） It presents a new methodological approach to deal with a problem which is of strategic importance for ANSPs （air navigation service providers）; （2） It provides insights on the interdependencies between factors influencing performance. Both results are considered particularly important nowadays, due to the SES （Single European Sky） performance scheme and its related target setting process.

Sponge:An Oversubscription Strategy Supporting Performance Interference Management in Cloud

Resource oversubscription optimizes the utilization of the computing resources. Many well-known virtual machine monitors(VMMs)such as Xen and KVM,adopt this approach to help maximize the yield of the cloud datacenters That is,with proper resource oversubscription strategies,more virtual machines(VMs) can be supported by limited resources. However performance interference among VMs hosting in the same physical machines(PMs) exists in cloud environment,and probably aggravated by resource oversubscription strategies,which aims to put more VMs into the same PM. In this paper,we present a resource oversubscription strategy called Sponge targeting cloud platforms Sponge mitigates the issue of performance interference among the oversubscribed co-hosting VMs. Sponge also provides a VM association strategy for each PM to handle with its besteffort. We performed our evaluation on a virtua datacenter simulated by Xen. Our evaluation results show that Sponge improves the resources utilization and manages to make each VM mee its performance requirement even hosting with other VMs in the same PM.

Research and Implementation of Architecture for Distributed Service Performance Management

An architecture for online discovery quantitative models system of service performance management is proposed. The system is capable of constructing the quantitative models without prior knowledge of the managed elements. The model can be updated continuously in response to the changes made in provider configurations and the evolution of business demands. Due to the existence of strong correlation between the distributed service metrics and response times, linear and hyper-linear quantitative models are constructed, which respectively, use stepwise multiple linear regression algorithm. The simulation results show the effectiveness of a quantitative model constructing system and model constructing algorithms.

Management Performance Evaluation Model of Korean Construction Firms

Corporate management performance evaluation currently focuses on financial aspects;however, it is necessary to identify and manage elements that contribute to increased economic values in the long run. When it comes to construction firms, most previous research did not cover weighting and estimation approaches for non-financial elements that ultimately influence financial status. In this research, the objective is to develop a management performance evaluation model for Korean construction firms. The model includes financial factors and non-financial factors. This research investigated actual data from Korean construction firmsandclassifiedtheir characteristics. This study is performed in two steps. First, this study derives KPIs for performance measurement techniques and weights the KPIs. And then, it applies the performance data of construction firms to the technique. The findings of this study show that Korean construction firms consider customers to be the foremost priority, converse to previous research which argued that the internal business process was the top priority. The performance measurement results can be fed back into strategies and plans to shed light on issues, reflect on management plans for subsequent years and modify mid to long-term strategies. Therefore, the developed model can help decision-makers effectively revise their management plans.

Improving construction performance through supply chain management

A typical model of construction supply chain (CSC) is presented firstly. Then the characteristics and problems of CSC are identified. The authors also describe the progress towards adoption of supply chain management (SCM) in the construction industry. Traditional construction management approaches (CMAs) are compared with new SCM-based CMAs. The authors suggest that integrated SCM based on cooperating competition is crucial to improve construction performance. Based on relevant results from related research, a framework for integrated construction supply chain management (CSCM) is developed to guide the effective implementation of SCM in construction.