Summary
The literature on the challenges of and potential solutions to architecting cloud-based systems is rapidly growing but is scattered. It is important to systematically analyze and synthesize the existing research on architecting cloud-based software systems in order to build a cohesive body of knowledge of the reported challenges and solutions. We have systematically identified and reviewed 133 papers that report architecture-related challenges and solutions for cloud-based software systems. This paper reports the methodological details, findings, and implications of a systematic review that has enabled us to identify 44 unique categories of challenges and associated solutions for architecting cloud-based software systems. We assert that the identified challenges and solutions classified into the categories form a body of knowledge that can be leveraged for designing or evaluating software architectures for cloud-based systems. Our key conclusions are that a large number of primary studies focus on middleware services aimed at achieving scalability, performance, response time, and efficient resource optimization. Architecting cloud-based systems presents unique challenges as the systems to be designed range from pervasive embedded systems and enterprise applications to smart devices with Internet of Things. We also conclude that there is a huge potential of research on architecting cloud-based systems in areas related to green computing, energy efficient systems, mobile cloud computing, and Internet of Things. Copyright © 2016 John Wiley & Sons, Ltd.

Architecting cloud‐enabled systems: a systematic survey of challenges and solutions

Implementation of a real-time network traffic monitoring service with network functions virtualization

In recent years, virtualization is one of the key technologies of next-generation data centers. However, the problem of virtualization technology is that each instance needs to run a client operating system and a lot of applications. Therefore, it might generate a heavy load and affect the system efficiency and performance. In this work, the performance evaluation of three environments (bare-metal, Docker containers, and virtual machines) is investigated to understand the differences between the characteristics of each environment. Also, we addressed whether container-based virtualization can solve the problems of traditional virtualization. In addition, we combined Docker with OpenStack to implement a container management platform. Finally, we took Hadoop deployment as an example to verify whether Docker can solve the deployment problem and save time.

Implementation and evaluation of a container management platform on Docker: Hadoop deployment as an example

According to analysis by Gartner, Inc., cloud computing is one of the top 10 strategic technology for most organizations in 2015. Gartner defines a strategic technology as one with the potential for significant impact on the organization in the next three years. Even though virtualization can reduce the cost of hardware equipment, but it still faces with two problems: energy consumption and the waste of the idle resources. To solve these two problems, we propose two algorithms, i.e., Dynamic resource allocation and energy saving. In order to implement these two algorithms with live migration of virtual machines, we first build an infrastructure platform based on cloud software Open Stack. Next, dynamic resource allocation and energy saving algorithms are designed and implemented. Finally, we use the Power Distribution Unit (PDU) to monitor system status and record power consumption, the real time status monitoring data verify that the proposed algorithms are efficient in energy saving and idle resource planning.

Implementation of a Cloud Energy Saving System with Virtual Machine Dynamic Resource Allocation Method Based on OpenStack

Management and construction to the teaching laboratory can have a significant influence on not only the operation of the lab, but also the motivation and expectation of students, thus resulting in a reduction of their academic progress. To address the problem, a cloud-based virtual computer laboratory is proposed in this paper. It aims to release the burden of the lab's operation management and help to rapidly construct such a virtual lab. In this end, the physical servers are virtualized as a pool with virtual computers by employing OpenStack, and the management services to the class are provided for teachers and students. To further facilitate the construction of such a virtual lab, a configuration scheme of the physical resources for the virtual computer pool is presented, which is compatible with the specific scale of the lab. Also an application example for the lab in a college is detailed, which verified the availability of the solution.

Constructing a virtual computer laboratory based on OpenStack

A generic cloud platform for engineering optimization based on OpenStack

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Xicheng Wang

Author Tools

Chat about Author

Papers

A generic cloud platform for engineering optimization based on OpenStack