Requirement of Cloud Analytics and Distributed Cloud Computing: An Initial Overview

Abstract

A better and more streamlined user experience is the result of the research demonstrating how cloud analytics tools and software are particularly effective for processing vast data sets, producing insights in easily digestible formats on demand, and improving the user interface. Cloud computing is a large-scale information technology solution that can customize and deliver a new kind of environment based on information technology to everyday users, in particular to IT and computing systems users. Cloud computing was developed by Amazon Web Services (AWS) and Microsoft Azure. The use of cloud computing comes with a multitude of features and aspects, including internet backup. It comes with just-in-time delivery of standardized storage process, management, and infrastructure, as a measurable service, on a 'Pay-as-you-go' type, and is therefore widely accessible in various organizations and institutions. Cloud computing and its load balancing are essential features that must be taken care of to maintain a healthy Information Management system. In a condensed form, this paper discusses a significant number of topics that are connected to the given subject.

Enterprise SaaS Workloads on New-Generation Infrastructure-as-Code (IaC) on Multi-Cloud Platforms

“…A multi-cloud strategy would go a long way to handle these edge cases effectively. Still, the complexity of setting up the environment for multi-cloud is a significant pain point and barrier to adoption (Achar, 2015). Some cloud providers have already implemented their infrastructure deployment services that automate the creation and management of cloud resources, such as Google Cloud Deployment Manager, AWS CloudFormation (Achar, 2020c), AWS OpsWorks, and Stacks (Mantoux, 1983).…”

An Optimized Routing OLSR Protocol with Low Control Overhead for UAV Ad Hoc Networks

“…Since additional content was added to the original HELLO packet, it brought some additional control overhead. In [12], a new MPR selection mechanism is proposed, which uses mobile stability as the MPR node selection criterion, thereby improving the stability of the protocol, but the new selection algorithm cannot guarantee that the selected MPR set is the smallest, Therefore, the number of TC messages sent and forwarded in the network may be increased, resulting in additional control overhead. In response to the problem that the single-hop coverage of the node is small, which leads to an increase in the number of routing hops, Alshbatat proposed an improved mechanism of using directional antenna to expand the communication coverage to reduce the number of hops in literature [13].…”

Heavy Rainfall in Kenya and Its Predictability Using Artificial Neural Networks

“…These climate networks are generally built by connecting spatiotemporal placements that are importantly related with each other accordant to some measure. Hence climate networks already look to be an effective tool for more qualitative El Niño Southern Oscillation prediction, by looking at a warning of the oncoming of El Niño when a predestined network attribute surpasses some critical value [12].…”