The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Cloud computing delivers computing resources, including servers, storage, databases, and networking, as on-demand services over the internet, eliminating the need for organizations to own and maintain physical infrastructure. Service models are typically categorized as Infrastructure as a Service, Platform as a Service, and Software as a Service, deployed across public, private, or hybrid environments. Core research areas include resource allocation and load balancing, virtual machine and container scheduling, auto-scaling under variable workloads, cost optimization, and meeting service-level agreements under fluctuating demand. Roughly 94 percent of enterprises now use cloud services in some form according to recent industry surveys, with most running multi-cloud or hybrid strategies that raise distinct challenges in data security and multi-tenant isolation. Newer research directions include serverless computing, edge-cloud continuum architectures, and energy-efficient data center design. Applications span enterprise IT, big data analytics platforms, and the backend infrastructure for mobile and IoT applications. As an open-access cloud computing journal, IJACSA covers cloud architectures, performance evaluation studies, and security frameworks for hybrid environments.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed October 2026
This paper aims to develop an efficient and adaptive load balancing algorithm for cloud computing environments using a novel hybrid meta-heuristic approach. Effective load balancing is necessary for optimum performance a…
Mobile health (mHealth) applications are increasingly relying on artificial intelligence (AI) to provide accurate and real-time decision support for healthcare delivery. However, achieving the optimal balance between pro…
Effective scheduling of tasks is a key concern in cloud computing because it considerably affects system functionality, resource usage, and execution efficiency. The present study proposes an Enhanced Chimp Optimization…
Effective load balancing in cloud computing architectures is crucial towards enhancing resource utilization, response times, and stability in the system. The present study proposes a new strategy with a Particle Swarm Op…
Virtual Machine (VM) migration is one of the most important features of cloud computing for resource utilization optimization, energy minimization, and quality of service enhancement. Existing migration solutions, howeve…
The basis for current digital infrastructure is cloud computing, which allows for scalable, on-demand computational resource access. Data center power consumption, however, has skyrocketed because of demand increases, ra…
This survey aims to analyze resource prediction models in cloud environments to improve resource allocation strategies. It can be difficult for cloud service providers to maintain the required Quality of Service (QoS) re…
This study investigates the factors influencing cloud computing adoption in the public sector, emphasizing the performance of IT personnel. Through qualitative interviews with five IT management professionals in the publ…
Effective resource estimation is essential in cloud computing to minimize operational costs, optimize performance, and enhance user satisfaction. This study proposes a comprehensive framework for virtual machine optimiza…
Integrating edge and cloud computing systems builds up a powerhouse, a framework for realizing real-time data processing and conducting large-scale computation tasks. However, efficient resource allocation and task sched…
