Enterprise risk forecasting in human resource management in cloud computing using cascaded block visual modelling, artificial hummingbird guided graph attention networks

In order to provide users timely and reliable services, resources and facilities in cloud data centers are often more than actual needs, which leads to low resource utilization and high operating costs. However, controling the quantity of resources and facilities may cause low throughput. Therefore, many researches are devoted to increasing resource utilization, improving jobs throughput and reducing operating costs through effective cloud resource management. The cloud resource management in cloud data center can be regarded as a multi-resource demand job allocation problem. This paper proposed an allocation algorithm of jobs based on deep reinforcement learning. The algorithm allocates waiting jobs to clusters respectively, so as to optimize throughput and improve resource utilization. The algorithm is implemented in cloud data center simulation model CloudSim. The experimental results show that the method based on Deep Reinforcement Learning is better than traditional method in multi-resource job allocation problem.

Cloud management faces with great challenges, due to the diversity of Cloud resources and ever-changing management requirements. For constructing a management system to satisfy a specific management requirement, a redevelopment solution based on existing management systems is usually more practicable than developing the system from scratch. However, the difficulty and workload of redevelopment are also very high. As the architecture-based runtime model is causally connected with the corresponding running system automatically, constructing an integrated Cloud management system based on the architecture-based runtime models of Cloud resources can benefit from the model-specific natures, and thus reduce the development workload. In this paper, we present an architecture-based approach to managing diverse Cloud resources. First, manageability of Cloud resources is abstracted as runtime models, which could automatically and immediately propagate any observable runtime changes of target resources to corresponding architecture models, and vice versa. Second, a customized model is constructed according to the personalized management requirement and the synchronization between the customized model and Cloud resource runtime models is ensured through model transformation. Thus, all the management tasks could be carried out through executing programs on the customized model. The experiment on a real-world cloud demonstrates the feasibility, effectiveness and benefits of the new approach to integrated management of Cloud resources

Abstract: Online resource management in cloud computing must respond to rapidly changing demand and system conditions, often exceeding the adaptability of static or periodically recomputed optimisation plans. This study formulates cloud resource management as a Markov decision process (MDP) and investigates deep reinforcement learning (DRL) as an approximate dynamic programming (ADP) approach for deriving adaptive control policies. The system state encompasses workload, capacity utilisation, and performance indicators, while actions govern virtual machine placement, scaling, and server power-state transitions. Reward functions combine energy and operating costs with penalties associated with service-level agreement violations. DRL algorithms, including deep Q-networks, advantage actor–critic, and proximal policy optimization, are implemented in PyTorch and trained through interaction with a CloudSim-based simulation environment calibrated to realistic load and power profiles. The learned policies are evaluated against deterministic and scenario-based stochastic optimisation baselines using metrics such as average cost, energy consumption, SLA violations, and robustness to non-stationary demand. Results show that DRL policies can approach or surpass the performance of stochastic optimisation solutions in highly dynamic scenarios, while maintaining feasible control actions. The study demonstrates how DRL can be positioned within an OR/ADP framework and highlights conditions under which learning-based methods offer significant advantages for online cloud control. Keywords: deep reinforcement learning, approximate dynamic programming, cloud computing, Markov decision processes, online resource management, energy-aware control, PyTorch, simulation

This study addresses the critical need for effective resource management through software container migration in cloud data centers. It emphasizes its role in avoiding resource shortages and reducing energy consumption in cloud environments. This study introduces a novel multi-objective integer linear programming (ILP) approach for software container replacements, complemented by a specialized algorithm designed to migrate software containers between over- and underutilized hosts to enhance efficiency compared to traditional optimization methods. The simulation results demonstrate the algorithm's effectiveness, validating its potential for optimizing energy usage and resource allocation in cloud environments. Statistical analyses confirm the proposed model's and algorithm's superiority over benchmark approaches, highlighting their potential for enhancing resource management in cloud computing systems.

The trend of adopting Internet of Things (IoT) in healthcare, smart cities, Industry 4.0, and so on is increasing by means of cloud computing, which provides on-demand storage and computation facilities over the Internet. To meet specific requirements of IoT applications, the cloud has also shifted its service offering platform to its next-generation models, such as fog, mist, and dew computing. As a result, the cloud and IoT have become part and parcel of smart applications that play significant roles in improving the quality of human life. In addition to the inherent advantages of advanced cloud models, to improve the performance of IoT applications further, it is essential to understand how the resources in the cloud and cloud-influenced platforms are managed to support various phases in the end-to-end IoT deployment. Considering this importance, in this article, we provide a brief description, a systematic review, and possible research directions on every aspect of resource management tasks, such as workload modeling, resource provisioning, workload scheduling, resource allocation, load balancing, energy management, and resource heterogeneity in such advanced platforms, from a cloud perspective. The primary objective of this article is to help early researchers gain insight into the underlying concepts of resource management tasks in the cloud for IoT applications.

A novel bio-inspired approach for VM load balancing and efficient resource management in cloud

Optimal resource management in cloud computing

Turbulent times and crises force many human resource (HR) managers to adapt human resource practices (HRP) to a rapidly changing reality. The modification of HRP in a very stressful environment poses enormous challenges for HR managers. This study looks at the mechanisms through which HRP was adapted to unexpected changes to attain resilience during worldwide crises. Based on qualitative data collected from 72 Israeli HR managers, the findings reveal that HR managers’ social capital (SC) serves as a mechanism for adapting HRP to attain resilience. HR managers employed personal, intra-organizational, and extra-organizational levels of SC that lead to compatible types of resilience: employee, organizational, and interface resilience. Although personal and intra-organizational SC were used frequently, the HR managers used extra-organizational SC to cope with the upheavals caused by the crises to a lesser extent, and, therefore, less interface resilience was attained through HRP. The findings contribute to the literature by suggesting that HR manager SC serves as a mechanism fueling the adaptation of HRP during crises and leads to resilience. It also extends the resilience literature by suggesting that the adaptation of HRP through HR manager SC influences different types of organizational resilience.

The integration of Artificial Intelligence (AI) and digital connectivity can revolutionize material and human resources management in secondary schools. The study focused on human and material resources management in education in Nigeria and its impact on students’ academic performance in secondary schools, in Ebonyi State, Nigeria. Subjects for the study were two hundred (200) students and hundred (100) teachers randomly selected from five secondary schools in Afikpo, Ohozara, and Ezza South Local Government Areas of Ebonyi State. Questionnaire was used to collect relevant data for the study. Pearson Product Moment Correlation was used to analyses the formulated hypotheses. The findings of the study revealed that there was significant positive relationship between human resources management and students’ academic performance (r = 0.814; p < 0.05). Also, significant relationship exists between material resources management and students’ academic performance (r = 0.629; p < 0.05). The implication is that effective material resource management may bring about improvement in student’s academic performance. While it was recommended that effective practice of both human and material resources is to be well implemented for effective performance of students at any level of educational system in Nigeria.

Purpose — This paper explores the field of ethical conflicts of human resource (HR) managers in Slovenian organizations: unfair payments, extreme differences in rewards, not respecting employees’ rights, discrimination; using over excessive disciplinary power, not paying social contributions, and engaging in manipulations, among others. The main attention is paid to the implementation of employees’ rights and the factors that affect the process of the implementation of employees’ rights.Design/methodology/approach — We applied an ABC (antecedents — behavior — consequences) analysis of ethical organizational behavior. The survey encompasses 73 HR managers of Slovenian companies.Findings — HR managers perceive their role in an organization as being caught in a specific position in relation to senior management and employees. The study shows that in organizations where the “soft” and “combined” model of human resource management (HRM) is developed, the implementation of employees’ rights is more strongly realized.Research limitations — The sample size is one of the chapter’s limitations. The other is the use of quantitative statistical approach without applying other methods. In the future it should be accompanied with qualitative techniques by which dishonesty would be more directly linked to the violation of employees’ rights.Practical implications — Professional education can (1) form a solid system of professional values that can help to prioritize expectations and demands in the work place and (2) equip HR managers with competencies to solve ethical issues and to engage in ethical behavior.Social implications/value — The results show that first of all, HR managers are responsible in their role (responsibility of the role in developing the model of HRM which facilitates the implementation of employees’ rights) and only secondly, comes the responsibility of HR managers in an active sense of responsibility (responsibility as a virtue).

Human resource (HR) managers’ commitment to their occupation (HR) leads to the proper delivery and implementation of HR practices and, therefore, is deemed as a critical factor for the success of HR practices. Based on sociocognitive, human capital, and signaling theories, this study examines: (a) HR managers’ own and their chief HR officer's (CHRO) HR‐specific human capital as antecedents of their commitment to HR, and (b) the mediating mechanism through which the CHRO’s HR‐specific human capital positively influences HR managers’ commitment to HR. Based on 146 HR managers from 146 organizations in South Korea, the findings of the current study suggest that HR managers with higher levels of HR‐specific human capital and those working with CHROs with higher levels of HR‐specific human capital tend to have higher levels of commitment to HR. In addition, CHROs with higher levels of HR‐specific human capital positively influence HR managers’ commitment to HR by signaling to them that HR and its function are valued and cared about by their organizations. Theoretical and practical implications of this study are discussed along with study limitations and further research directions. © 2015 Wiley Periodicals, Inc.

The work culture revolution has become one of the most profound phenomena in the development of human resource management (HR) in the modern era. One of the biggest impacts of this change is the emergence of remote work flexibility and global collaboration, which is further changing the dynamics of the workplace. The purpose of this study is to analyze the impact of the work culture revolution on human resource management (HR) in the era of remote work flexibility and global collaboration. This study uses a descriptive qualitative approach to analyze the work culture revolution in human resource management (HR) in the era of remote work flexibility and global collaboration. The results of this study show that the work culture revolution that includes remote work flexibility and global collaboration has brought significant changes in human resource (HR) management. Work flexibility has been shown to improve employees' well-being and job satisfaction, giving them more control over the balance of their personal and professional lives. However, the main challenge that arises is how companies can manage the performance of employees who work remotely, especially in terms of performance measurement, productivity monitoring, and ensuring effective communication within teams spread across multiple locations and time zones. Large companies, which are more accustomed to adopting advanced technology, are more successful in addressing these challenges compared to smaller companies, which still rely on a physical presence-based approach. Data from this study reinforces those findings in terms of performance management systems, 78% of large companies have switched to results-based systems, while 55% of small companies still rely on physical presence to monitor employee performance. In addition, platforms such as Zoom (78%) and Microsoft Teams (65%) dominate the use for remote collaboration, indicating that technology plays an important role in facilitating communication across locations and time zones. On the other hand, companies that pay more attention to the mental well-being of employees, by providing online counseling services and wellness programs, tend to have higher engagement rates. This can be seen from 60% of companies that provide mental health support to their employees.

Purpose– To explore whether the ages of human resources (HR) managers has an impact on their perceptions of the qualities/characteristics of older and younger workers (i.e., manager attitudes) and on the implementation of age management initiatives to the benefit of older workers (i.e., manager behaviors). The paper aims to discuss this issue.Design/methodology/approach– Based on theories concerning the origins of stereotypes and the concept of “in-group bias”, three hypotheses were tested on a sample of HR managers from 516 Italian companies extracted from the Gfk Eurisko database by using factor analyses and bivariate and multivariate tools.Findings– The age of an HR manager seems to influence his/her attitudes towards older and younger workers, because HR managers judge workers of a similar age to them more positively. In contrast, the age of an HR manager does not seem to play a particular role in the implementation of age management initiatives. In the companies considered, however, there is a tendency to adopt early retirement schemes when the HR managers concerned are younger, while in general there is a tendency to implement age management initiatives and show a greater appreciation of older workers in larger companies.Practical implications– The implementation of age management initiatives to the benefit of older workers may improve HR managers ' perceptions of those workers ' positive qualities. Furthermore, specific training may help HR managers recognize that both younger and older workers have useful albeit different strengths.Originality/value– This study provides new empirical evidence from the Italian context on the largely under-investigated issue of the role played by age in shaping HR managers ' attitudes towards older workers, and age management policies in particular.

The objective of this study is to argue transition from human resource management (HRM) to strategic human resource management (SHRM). In addition, this study also discusses the theory of SHRM. The research methodology of this study is based on arguments from SHRM literature. The significant of paper is a discussion of SHRM theory. Key terms are personnel, employee, and capital in management of human resources by firms. Practitioners call human resources as personnel in personnel management (PM); and call human resources as an employee in HRM. Practitioners do not clarify the term yet for human resources in SHRM. This paper suggests “capital” term for human resources in SHRM. Secondly, return on investment (ROI) of HRM might be positive organizational attitude and behaviours. HRM makes investment to employees, and ROI of HRM is important to SHRM because positive attitude and behaviours increase individual performance of employees. Thirdly, there is a triangular relation in SHRM theory. This is named as trigonometry of SHRM. There are dependent variables, independent variables, and moderators in this triangular. Finally, SHRM can be described with employee performance and firm performance relationship. In this relation, HRM practices lead to increased individual performance, and individual performance increases performance of business departments such as logistics, supply, finance, marketing, production etc. and performance of business departments has an impact on firm performance. In this SHRM model, HRM has an impact on firm performance through individual performance and business departments. All are described is SHRM theory in this study. For HRM case, HRM has two purposes in firm management. Those purposes are performance and recruitment. HRM aims to increase individual performance of employees. If HRM aims to increase firm performance through individual performance, it is description of SHRM. HRM has an impact on individual performance via HRM practices. HRM practices are keys to increase individual performance. Because employees implement business processes in firm management. Those processes are such as production, marketing, stock, supply, logistics, finance and others. Individual performance of employees increases performance of those business processes in firm management. Therefore, it is important to increase individual performance through HRM practices. This is a HRM theory in this study. Moreover, HRM does recruitment of employees for functioning these business processes. Because all needs human resources to effectively implement processes in firms.

ABSTRACTThis study has used a longitudinal, quantitative design to explore the expected increase in the reference to human resource management (HRM) strategic planning roles in Australian organisations between 1993 and 2004. The research also examined which of the organisational characteristics of ownership, sector and size best predicts strategic planning roles for HR managers in 2003-04. Data was collected from the content analysis of 315 job advertisements for senior Human Resources (HR) managers published in national newspapers and on the Internet. Results established a longitudinal increase in references to strategic HR roles and established that internationally-owned, larger, and public sector organisations placed greater emphasis on promoting strategic roles for HR managers. The strongest predictor of a strategic planning role however was the sector in which the organisation was placed. Specifically, in the public sector HR managers at the most senior level were given the same strategic role as counterparts in the private sector but HR managers at the next level down were significantly less likely than HR managers at the same level in the private sector to be given strategic roles. These findings have implications for the training and development opportunities for HR managers working in the public sector.