A Comprehensive Review of Security Issues in Cloud Computing
An Extended Min-Min Scheduling Algorithm in Cloud Computing
Data Quality Evaluation Framework for Big Data
An Architectural Framework for Ant Lion Optimization-based Feature Selection Technique for Cloud Intrusion Detection System using Bayesian Classifier
Be Mindful of the Move: A Swot Analysis of Cloud Computing Towards the Democratization of Technology
GridSim Installation and Implementation Process
A Survey on Energy Aware Job Scheduling Algorithms in Cloud Environment
Genetic Algorithm Using MapReduce - A Critical Review
Clustering based Cost Optimized Resource Scheduling Technique in Cloud Computing
Encroachment of Cloud Education for the Present Educational Institutions
Cloud computing is a prominent and evolving distributed computing paradigm that provides users with on-demand services through a network of diverse autonomous systems with flexible computational structures. Within this context, the significance of task scheduling becomes evident, serving as a vital component in elevating cloud computing's overall performance. Streamlining cost-effective execution and optimizing resource utilization is a key objective, given the NP-hard nature of the task scheduling problem. This intricacy has prompted researchers to investigate metaheuristic algorithms inspired by nature. Although numerous metaheuristic techniques have been explored to address task allocation challenges, ample opportunities remain for the development of optimal strategies. In this paper, a state-of-the-art task assignment model is presented, centered around OptiAssign-Particle Swarm Optimization (PSO), with a strong emphasis on the crucial role played by efficient dependency handling and multi-level task scheduling. The primary aim of this model is to optimize the utilization of virtual machine capacities while simultaneously minimizing execution time, makespan, wait time, and overall execution costs within various distributed computing systems. The novel algorithm showcases outstanding performance compared to traditional approaches in task scheduling, highlighting the importance of skillful dependency management and the implementation of multi-level task scheduling strategies. The conclusive results of the study further affirm the effectiveness of the model in addressing the inherent
DevKraft is a cutting-edge cloud platform designed for collaborative coding experiences, leveraging AWS infrastructure. It offers specialized pages tailored for various activities, DevKraft for hackathons, DevKode for coding challenges, and QuizDeck for quizzes. DevKraft boasts streamlined deployment processes and utilizes a robust DevOps stack, including Jenkins, Docker, Prometheus, Grafana, and Kubernetes. Developed with TypeScript and Node.js, this platform ensures seamless integration and deployment of projects, setting a new standard for collaborative coding platforms in the cloud environment.
This system is proposed to address the challenges healthcare professionals face in monitoring patients who require intravenous infusion. This treatment method is commonly used for patients with dehydration, malnutrition, or those unable to take oral medications. The system enables remote monitoring of a patient's health and reduces the workload of healthcare professionals. The process begins with a doctor prescribing the necessary dose of drip bottles, which are then configured by the nurse accordingly. Once set for automatic operation, the system diligently calculates and monitors the fluid level and infusion rate using a load cell sensor. Additionally, the patient's vital signs, including heart rate, body temperature, and oxygen levels, are continuously monitored and stored in a database using cloud computing technology, enabling robust data analysis. The system provides real-time feedback on infusion parameters via an LCD screen. In the event of a patient's health deteriorating below a threshold level, a message is sent to the doctor, accompanied by a buzzer sounding and a red LED flashing at the patient's bedside. A supervisor continuously monitors the patient's health report, promptly informing the physician of any rapid changes and facilitating immediate treatment. This comprehensive system enhances patient care, streamlines medical monitoring processes, and enables swift responses to emergent health situations.
