Project management for cloud computing development

This article deals with the impact of employing cloud computing architectures in the field of software systems development. We analyze the individual influence of the cloud computing model characteristics on the project development process.

Project management for cloud computing development

This article deals with the impact of employing cloud computing architectures in the field of software systems development. We analyze the individual influence of the cloud computing model characteristics on the project development process

A review on Cloud Computing Architectures and Applications

In current time the IT based services demands , services deployment cost , scalability issues and many more constraints have paved the way for focusing on cloud computing. Cloud computing is the structure of a central server resources distributed on the platform scalable environment to provide "on demand" computing resources. In this research in detail the various structures of cloud computing are reviewed. The applications of these architectures are discussed for different areas of life. Also the different working domains of cloud computing architectures are summarized . The purpose of this research is to provide understanding to the students , professionals, developers and researchers about cloud computing

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications

Revolutionizing Healthcare Image Analysis in Pandemic-Based Fog-Cloud Computing Architectures

The emergence of pandemics has significantly emphasized the need for effective solutions in healthcare data analysis. One particular challenge in this domain is the manual examination of medical images, such as X-rays and CT scans. This process is time-consuming and involves the logistical complexities of transferring these images to centralized cloud computing servers. Additionally, the speed and accuracy of image analysis are vital for efficient healthcare image management. This research paper introduces an innovative healthcare architecture that tackles the challenges of analysis efficiency and accuracy by harnessing the capabilities of Artificial Intelligence (AI). Specifically, the proposed architecture utilizes fog computing and presents a modified Convolutional Neural Network (CNN) designed specifically for image analysis. Different architectures of CNN layers are thoroughly explored and evaluated to optimize overall performance. To demonstrate the effectiveness of the proposed approach, a dataset of X-ray images is utilized for analysis and evaluation. Comparative assessments are conducted against recent models such as VGG16, VGG19, MobileNet, and related research papers. Notably, the proposed approach achieves an exceptional accuracy rate of 99.88% in classifying normal cases, accompanied by a validation rate of 96.5%, precision and recall rates of 100%, and an F1 score of 100%. These results highlight the immense potential of fog computing and modified CNNs in revolutionizing healthcare image analysis and diagnosis, not only during pandemics but also in the future. By leveraging these technologies, healthcare professionals can enhance the efficiency and accuracy of medical image analysis, leading to improved patient care and outcomes

Information standards to support application and enterprise interoperability for the smart grid

Copyright @ 2012 IEEE.Current changes in the European electricity industry are driven by regulatory directives to reduce greenhouse gas emissions, at the same time as replacing aged infrastructure and maintaining energy security. There is a wide acceptance of the requirement for smarter grids to support such changes and accommodate variable injections from renewable energy sources. However the design templates are still emerging to manage the level of information required to meet challenges such as balancing, planning and market dynamics under this new paradigm. While secure and scalable cloud computing architectures may contribute to supporting the informatics challenges of the smart grid, this paper focuses on the essential need for business alignment with standardised information models such as the IEC Common Information Model (CIM), to leverage data value and control system interoperability. In this paper we present details of use cases being considered by National Grid, the GB transmission system operator for information interoperability in pan-network system management and planning.This study is financially supported by the National Grid, UK

Next Generation Cloud Computing Architectures: Performance and Pricing

Cloud providers need to optimize the container deployments to efficiently utilize their network, compute and storage resources. In addition, they require an attractive pricing strategy for the compute services like containers, virtual machines, and serverless computing in order to attract users, maximize their profits and achieve a desired utilization of their resources. This thesis aims to tackle the twofold challenge of achieving high performance in container deployments and identifying the pricing for compute services. For performance, the thesis presents a transport-adaptive network architecture (D-TAIL) improving tail latencies. Existing transport protocols such as Homa, pFabric [1, 2] utilize Shortest Remaining Processing Time (SRPT) scheduling policy which is known to have starvation issues for long flows as SRPT prioritizes short flows. D-TAIL addresses this limitation by taking age of the flow in consideration while deciding the priority. D-TAIL shows a maximum reduction of 72%, 29.66% and 28.39% in 99th-percentile FCT for transport protocols like DCTCP, pFabric and Homa respectively. In addition, the thesis also presents a container deployment design utilizing peer-to-peer network and virtual file system with content-addressable storage to address the problem of cold starts in existing container deployment systems. The proposed deployment design increases compute availability, reduces storage requirement and prevents network bottlenecks. For pricing, the thesis studies the tradeoffs between serverless computing (SC) and traditional cloud computing (virtual machine, VM) using realistic cost models, queueing theoretic performance models, and a game theoretic formulation. For customers, we identify their workload distribution between SC and VM to minimize their cost while maintaining a particular performance constraint. For cloud provider, we identify the SC and VM prices to maximize its profit. The main result is the identification and characterization of three optimal operational regimes for both customers and the provider, that leverage either SC or VM only, or both, in a hybrid configuration

Privacy and confidentiality issues in cloud computing architectures

Cloud computing is a computing paradigm in which organizations can store their data remotely in the cloud (Internet) and access applications, services and infrastructure on-demand from a shared pool of computing resources. It is clear that cloud technologies have proven a major commercial success over recent years (since the appearance of products and cloud offerings like Amazon EC2 and Microsoft Azure). According to Gardner, Cloud Computing will play a large part in the ICT (Information and Communication Technologies) domain over the next 10 years or more, since it provides cost-savings to enterprises thanks to virtualization technologies, opening gates for new business opportunities as well. However, Cloud Computing has to face several challenges and issues. Storing and processing data out of the boundaries of your company raises security and privacy concerns by itself. Nowadays information is the commodity of XXI century, and certain information can mean power and market advantage. As pointed out by Andreas Weiss, Director of the EuroCloud, in an interview we held with him, data is one of the most important and valuable resource any company has. Therefore, security mechanisms to protect this data are necessary to make the right choices and decisions for the company without worrying about data safety. In the paradigm of Cloud Computing we will have to trust a Cloud Service Provider (CSP), creating an extra dependency to a third party which some customers, depending on the value of their data, will inevitably feel uncomfortable. Outsourcing business data in a place not owned by oneself can scare organizations from using the benefits of Cloud Computing in an optimal way

Using the NIST reference model for refining logical architectures

The emergence of the Internet as a ubiquitous means of communication fostered the growth of new business and service models based on Cloud Computing. Information and Communication Technology companies use reference models to define their Cloud Computing strategies. NIST Cloud Computing Reference Architecture is one of these reference models that assist in the design of business, services, and architecture models. This paper aims to present the use of NIST reference architecture in the design of Cloud Computing architectures by employing a method that enables the application of the reference architecture to the refinement of logical architectures. © 2014 Springer International Publishing