RESOURCE MANAGEMENT

Cloud computing has become key to modern digital infrastructure, yet traditional reactive auto-scaling systems struggle to balance performance requirements with cost efficiency. This study addresses the limitations of existing cloud resource management approaches by developing the Predictive and Cost-Optimized Auto-Scaling Framework (PCOAF), a conceptual model that integrates machine learning-based workload forecasting with multi- objective optimization. Through systematic application of Design Science Research Methodology, the research analyzed current auto-scaling systems, identified critical deficiencies including reactive latency, prediction inaccuracy, and cost inefficiency, and designed a three-layered architecture comprising monitoring, prediction and decision, and optimization and execution modules. The framework employs archetype-aware prediction to classify workloads into four behavioral patterns; SPIKE, PERIODIC, RAMP, and STATIONARY enabling tailored scaling strategies for each type. Theoretical validation demonstrates that PCOAF achieves 99.8% workload classification accuracy, reduces mean absolute percentage error to 15%, and projects cost reductions of 22% while decreasing service-level objective violations by 61.4% compared to baseline reactive systems. The study establishes PCOAF's feasibility across five design criteria: relevance, consistency, feasibility, scalability, and economic viability. By addressing identified gaps in both international research and Nigeria's emerging cloud ecosystem, this framework contributes a theoretically grounded and practically applicable solution for intelligent, cost-aware cloud resource management in resource-constrained environments.

This research work titled “Resource Management in the Theatre: Recruitment, Retention and Talent Management (A Focus on UNIBEN Theatre)” examines how human resource practices affect the effectiveness and sustainability of theatre production in the University of Benin Theatre Arts Department. The study was carried out to identify the strategies used in recruiting, retaining, and managing talents among theatre practitioners and students, as well as the challenges encountered in the process. The study adopted a survey research design, and data were collected through the use of structured questionnaires administered to 60 respondents consisting of academic staff, technical staff, and students of the department. Both purposive and simple random sampling techniques were used in selecting participants. The data collected were analyzed using simple percentages and presented in tables and charts. Findings revealed that while the UNIBEN Theatre has a fair recruitment process and a supportive learning environment, there are still notable gaps in employee motivation, career development opportunities, and recognition of talent. The study further showed that proper management of human resources plays a vital role in maintaining artistic quality, creativity, and productivity in theatre production. Based on the findings, the study recommends that the department should strengthen its recruitment policies, introduce regular staff and student development programs, and implement effective retention strategies that promote job satisfaction and professional growth.