Serverless computing for IoT data processing – Complete Phd and Masters Thesis

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Table of Contents:

Chapter 1: Introduction
1.1 Background of the Study
1.2 Statement of the Problem
1.3 Objectives of the Study
1.4 Research Questions
1.5 Significance of the Study
1.6 Limitations of the Study
1.7 Scope of the Study

Chapter 2: Literature Review
2.1 Definition of Serverless Computing
2.2 Overview of IoT Data Processing
2.3 Benefits of Serverless Computing for IoT
2.4 Challenges of Serverless Computing for IoT
2.5 Previous Studies on Serverless Computing for IoT Data Processing

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques

Chapter 4: Discussion of Findings
4.1 Analysis of Data Collected
4.2 Comparison of Findings with Previous Studies
4.3 Implications of Findings
4.4 Recommendations for Future Research

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Contributions to the Field
5.4 Recommendations for Practitioners
5.5 Recommendations for Policy Makers

Brief Overview:
Serverless computing is a cloud computing model that allows developers to build and run applications without managing the underlying infrastructure. In the context of IoT data processing, serverless computing offers a cost-effective and scalable solution for handling the massive amount of data generated by IoT devices. This thesis aims to explore the benefits and challenges of using serverless computing for IoT data processing.

The literature review will provide an overview of serverless computing and IoT data processing, highlighting the advantages and limitations of this approach. The research methodology section will outline the methods used to collect and analyze data, including case studies and experiments. The discussion of findings will present the analysis of the collected data, comparing it with previous studies and drawing implications for future research.

In conclusion, this thesis will summarize the findings and their implications for the field, making recommendations for practitioners and policymakers. Overall, this research will contribute to the growing body of knowledge on serverless computing for IoT data processing, providing valuable insights for the development of scalable and efficient IoT systems.

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