Detection of DDoS Attack in Cloud Computing and its Prevention: A Systematic Review
Awareness of Cloud Computing among the Prospective Teachers in the Modern World
Enhancing Replica Management in a Cloud Environment using Data Mining Based Dynamic Replication Algorithm
Elasticity in the Cloud Related to Database Autonomies and Scalability
Cloud Computing Rising in the Field of Big Data and Artificial Intelligence
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
Genetic Algorithm Using MapReduce - A Critical Review
Encroachment of Cloud Education for the Present Educational Institutions
A Survey on Energy Aware Job Scheduling Algorithms in Cloud Environment
Clustering based Cost Optimized Resource Scheduling Technique in Cloud Computing
Cloud computing is one of the latest and greatest environments for delivering Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS) in digital communications infrastructure. Cloud computing helps the user remotely access the required service as needed through the Internet. But this technological advancement, due to its remote availability in the cloud, leads to new attacks. One of the biggest threats to cloud infrastructure is Distributed Denial of Service (DDoS) flooding attacks. DDoS flooding attacks are clearly trying to exploit the availability of services for a legitimate user. An attacker gains access to a large number of computers (i.e., botnets) by exploiting the vulnerabilities, and then uses the botnets to initiate an organized attack with a large number of targets. This paper analyses the latest methods for detecting and preventing Distributed Denial of Service (DDoS) attacks. It also provided methods and technologies for preventing, detecting, and responding to DDoS flood attacks.
Cloud computing plays a vital role in education, politics, religion, transportation, relationships, medical check-ups, and so on. In education, online courses are carried out with the help of cloud computing. In cloud computing, expert conversations and classes delivered through any electronic device are protected on the server. The user can collect any information from the server through any search engine. There are so many platforms for downloading information for users. Electronic devices are very popular in this digital world. Some companies or individuals are introducing many applications for mobile phones and computers. One of the most useful options is search engines. It is very common to collect existing information on a server and it is a good communicator between users and cloud computing systems. Prospective teachers are the future teachers who will shape future citizens. The aim of the paper is to raise awareness of cloud computing among prospective teachers. This paper used a survey method to determine cloud computing awareness among prospective teachers and includes 61 samples from the College of Education. It uses the Cloud Computing Awareness Checklist tool to collect data for the present study. Hypotheses related to family type, locality, father's profession, father's education, and parents' income were found to have no significant differences. Thus, the result showed that prospective teachers have little knowledge of cloud computing. The researcher concluded that background variables are not significant. The essential things are the funds provided and the desire to learn. This will develop awareness and finally, the educator and prospective teachers raise awareness among prospective teachers and students, respectively. Educators encourage future teachers to collect more information about cloud computing on its own or with the help of an external facilitator.
Cloud computing has recently gained a lot of popularity and attention from the research community. One of the many on-demand services that large-scale applications provide to cloud customers is storage, which accumulates more generated data and subsequently leads to the need for storage. Despite the fact that users can use the cloud to store and provide the type of storage that desire, it still takes a significant amount of time to store and retrieve data due to the large accumulation of data. Due to the need to improve data availability, response time, reliability, and migration costs, the current storage engine needs to be replicated across multiple sites. When copies are properly distributed, data replication speeds up execution. The biggest challenges in data replication are choosing which data to replicate, where to put it, how to manage replication, and how many replicas it needs. Therefore, various studies have been carried out on some data mining-based data replication systems to evaluate replication issues and manage cloud storage. In most cases, data replication in a data mining environment is done using data mining along with a replication algorithm and a data grid policy. In addition, this paper addresses replica management issues and proposes affordable data replication in the cloud that satisfies all Quality of Service (QoS) requirements.
Cloud computing has been a very popular paradigm for implementing online applications. Scalability, elasticity, cost of use, and large-scale economies are the main reasons for the effective and widespread acceptance of cloud computing. In this paper, we outline our work to inject the aforementioned "cloud capabilities" into a database system designed to support various applications deployed in the cloud: designing scalable databases using autonomies database and elasticity that enables lightweight resiliency using low-cost live database migrations and an intelligent and autonomous controller designed for system management without human intervention.
Cloud Computing is a strong, large-scale and complex Computing technology. It lessens the need to maintain an expensive, specialized computer hardware area, as well as expensive software and software. Cloud computing has shown a significant increase in data quality or the production of large amounts of data. Big data processing is a difficult and time-consuming operation that necessitates the use of a large computer system in order to ensure performance. Knowledge creation and analysis are two intertwined activities and this paper investigates the rise of Big Data and Artificial Intelligence (AI) in Cloud Computing research. As data storage and mining methods advance, the preservation of expanding data quantities is characterized by a change in the core of structured results. This shift is reflected in the evolution of structured results. However, one major barrier is that this rate of growth surpasses the ability of data gathering systems and cloud infrastructure platforms to be upgraded. Workloads are really heavy and it is possible that certain cloud computing disputes will be created, which will include the description, characteristics, and categorization of huge data. In addition, analysis problems based on data integrity, heterogeneity and protection.