Set of Questions for master’s and Doctoral Thesis Defence: Guaranteed Success

Set of Questions for master’s and Doctoral Thesis Defence: Guaranteed Success

Detail demo for masters and PhD students

Contents

After submitting my thesis to an external examination, I started preparing for the final defence. Although the final defence depends on unknown variables, a series of questions must be prepared. I noticed that the last questions of the defence revolve around this list. I noticed that the final defence questions revolve around this list.

The examiners came after carefully reading your thesis. They already have a set of questions which they prepare while reading your thesis. The second type of question emerges from the presentation. Therefore, the elements included in the slides should be clear to you. Unclear items that you have included in the presentation can create problems for you.

The set of questions and how I prepared for my defence are listed below.

Please, summarize your thesis.

With limited resources, it is pretty challenging to meet dynamic and massive cloud customers’ demands. This study investigated this gap — IaaS revenue maximization by customer satisfaction and efficient resource provision in a limited resources environment.

Can you summarise it in one sentence?

IaaS revenue maximization by customer satisfaction and efficient resource provision in a limited resources environment.

What is the idea that binds your thesis?

IaaS revenue maximization

What motivated and inspired you to carry out this research?

Edge computing, mobile computing, the Internet of Things, AI, and 5G are emerging technologies, and cloud computing is the foundation for these technologies.

What are the most issues and challenges in this field?

Limited resources, performance degradation, cost, and customer dissatisfaction are the hot issues in this field.

Of the above-discussed problems, which one does your thesis cover?

Limited resources and performance-related issues.

Why is the problem you have tackled worth tackling?

Surly performance is the backbone of cloud services and with limited resources and high workload, the performance goes down.

Who is the leading role in your field?

Raj Kumar

Which three papers are the most important in relation to your thesis?

  1. Revenue Maximization with Optimal Capacity Control in Infrastructure as a Service Cloud Markets
  2. Revenue Maximization for Dynamic Expansion of Geo-Distributed Cloud Data Centers
  3. A Survey of Profit Optimization Techniques for Cloud Providers

What published work is closest to yours? How is your work different?

“Avoid penalties through SLA rejection and avoid massive workload SLAs”. However, the rejection of SLA has a very bad impact on the business. The Cloud Federation is a solution to meet this challenge. This partially covers this issue by not disallowing SLAs, however, the issue here is that the vendor is required to hire fixed-registered vendors.

What are the recent developments in your area?

S. Li, J. Huang and B. Cheng, “Resource Pricing and Demand Allocation for Revenue Maximization in IaaS Clouds: A Market-Oriented Approach,” in IEEE Transactions on Network and Service Management, vol. 18, no. 3, pp. 3460–3475, Sept. 2021

How did you come up with your research questions?

While analysing the cost, prices and revenue of the major companies, I came to know that provider revenue is wanted in penalties. If somehow, this wastage is covered, it may increase the provider revenue.

What were the crucial research decisions you made?

When we get something, we almost always lose something else. We will undoubtedly pay a price for high performance in terms of revenue maximisation and customer satisfaction.

Why did you use this research methodology? What did you gain from it?

After reviewing the literature and the market, I discovered this gap, and the proposed solution was the best way to address it.

Photo by Moaid Mefleh from Pexels

What alternatives did you have to this method?

Removing the running clients, not accepting the heavy workload, only accepting the higher revenue SLAs, federated clouds.

What steps did you take to address the ethical implications of your work?

Clouds need powerful labs and online servers. Initially, I talked to Higher Education Commission (HEC), as one of my teachers was using their servers for implementation but later on, I faced some resistance. Therefore, I started searching for some valid simulations and came across CloudSim.

How have you evaluated your work?

Through CloudSim and CloudAnalytic leading cloud simulators, developed by CLOUDS Lab, University of Melbourne.

How do you know that your findings are correct?

I used the CloudSim simulator, which is a popular cloud simulation tool. The simulation results were checked against the relevant articles and found accurate.

What are the strongest/weakest parts of your work?

First, the topic covers the primary topic of today’s technology. It is widely studied and used. Second, I published every part of the thesis, which I think shows the validity of the study. There are some weaknesses in the subject, so it should be presented in 2018. Presenting this work in 2021 feels old fashion. I feel like I’m working on a very old topic.

Who is most likely to be interested in your work?

Both academia and the market. These research papers have received more than 70 citations in academia since their publication, indicating that scholars are interested in this research.

Photo by Arif Syuhada from Pexels

What value does your work have for other researchers?

I’ve covered every aspect of cloud computing revenue maximisation. Cloud computing revenue maximisation is divided into seven categories based on academic literature and market demand, which will aid researchers working on revenue in cloud computing.

What value does your work have for practitioners and markets?

Cloud computing is a hot topic in academia as well as the business world. The business world is moving to the cloud. Because revenue is such an important aspect of any business, this research will be beneficial to market practitioners.

Which aspects of your work do you plan to publish, and where do you plan to publish them?

Every chapter of this thesis has been published.

How long-term are these contributions?

The world is rapidly changing, especially in terms of cloud computing. When I first started working on this project, there were no clear definitions or directions for edge computing; however, edge and cloud are now the most popular topics.

What are your research’s main achievements?

  • Smart workload migration
  • Smart resources scheduling
  • Customer satisfaction
Photo by Feedyourvision from Pexels

What have you learned as a result of completing your PhD?

This journey taught me a lot. I learned to write and read in particular. How should the ideas be developed and linked?

What advice would you give to a research student who is just getting started in this field?

Pursue the Edge and Mobile Computing.

Did you make any recommendations for future research? What would be a good place to start?

The cloud serves as a foundation for emerging technologies like edge computing, mobile computing, and the Internet of Things. As a result, my future work will focus on these areas.

What are the recent developments in your field?

NLP in pricing for customer satisfaction.

What would you have gained by using another approach?

There are a variety of approaches that could be used to address the issues, but this was the best option.

How has your view of your research topic changed?

The world is changing at a breakneck pace. Due to the massive traffic of smart devices and IoT, technology is moving away from centralised processing and toward edge processing. That’s why I’m shifting my focus to edge computing and the Internet of Things.

Summarise your key findings

  1. Hiring external resources to increase the resource’s scalability.
  2. Smart workload migration
  3. Customer satisfaction
  4. Revenue Maximization

Which of these findings is the most interesting to you? Why?

Hiring external resources because of resources limitation is a primary issue with small-scale cloud providers.

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