The increasing growth of the Internet will lead to significant and fascinating technology in computer science. Guidance for PhD thesis in computers facilitates a productive path for scholars and researchers. The quality of a PhD thesis reclines in its distinctiveness. A PhD thesis is a constituent of great significance for the corresponding academic field, such as computer science. Some of the essential steps to write a PhD thesis are listed below that serve as an aid for PhD research scholars in writing the correct PhD thesis:
Step1: Fixation of PhD Thesis Title
Title fixation for PhD thesis should be unique, followed by all the essential names of the research study. The titles must be more inclusive and acceptable to reflect the major contribution of the PhD thesis in the field of computer science.
Step 2: Writing the Abstract
Abstract framing is a high-class overall executive summary of the PhD thesis. The content of the abstract includes the core idea, problem motivation, research objectives, proposed research methods, achievements, and limitations. The end of the abstract offers a short description of the rest of the thesis organization.
Step3: List of Contents
Forming a list of contents helps provide direct accessibility for the necessitated page by proclaiming all the headings and sub-headings pointed in the PhD thesis research study, along with the list of tables, figures, and abbreviations used in the thesis.
The most important step is the introduction to the research work of a PhD thesis. This introduction chapter contains the content to understand the responsibility of estimating all the perspectives of the research objectives. The introduction chapter establishes the background, purpose of the research, context and developmental process of the research work as a clear overview.
The introduction chapter also covers the gap analysis to determine the differentiation between the present and desired performance of the proposed research work. The research objective provides the problem statement and the solution that the current research work achieves. The research objective should be specific, quantifiable, attainable, practical, and time-based. Objective lists the major focus of the research work and is divided into the number of research objectives as the outline to proceed with the work. While writing the content of this chapter, the researcher needs to include the fundamental information of the research work and the significance of the research contribution.
Step 5: Related Works
Related work and literature review is the next step to be added in the PhD thesis to impart the survey and critical review of prior related works. This chapter contains the coherent and consistent narrative of the previously published papers related and surveys to the same aspect of the present research work are preserved in the logical flow. Related work of the PhD demonstrates the literature search and critical analysis of the relevant literature characterizing earlier work in the field. While writing this chapter, the latest reference papers are analyzed, and their drawbacks are identified.
This chapter points out the research gap in knowledge, methods, and solutions for the problem that the thesis conflicts. During the updation of related works, highly cited publications, pertinent books, peer-reviewed journal articles, and official website information are utilized from a more consistent resource such as Google Scholar. Few top research journals such as IEEE, ACM, Elsevier, Springer, Science Direct, Wiley, Taylor & Francis, Thomson Reuters, and Inderscience Publishers should be referred for surveys and related works. For this purpose, this chapter must include practical knowledge, theoretical realizations, and contemplation.
Step 6: Research Methodology
Formulating the methodology of the research work covers the measures to achieve objectives for evaluating the reliability and validation of the research work. Research methodology provides depth explanation of the research work with its design, tool, and technologies used. Approaches such as qualitative, quantitative, descriptive, and experimental are utilized to represent the methodology. Research methodology also expresses the mathematical formulation of the research work.
Step 7: Performance Evaluation and Result Discussions
The next chapter is about the results and analyses of the research work. This chapter must concisely introduce the tools used and actual observations; statistical derivations should be analyzed in statements, tables, and graphs, for superior understanding. This section also discusses the graphical representation of obtained current work results with the defense of prior work results and comparative analysis.
Step 8: Conclusion
The conclusion is included in the very last part of the PhD thesis that summarizes all the complete research work by referring back to the main methodology of the thesis for the comprehensive descriptions; the conclusion segment does not comprise detailed descriptions of the issues or the solutions.
Step 9: Future Research Scope
Future directions of the research are enclosed at last, which is critical for future means of evolving research in the subjective fields and summing up the findings by referring back to the problems encountered in the research work.
Step 10: Referencing
In this step, the researcher must cite all the reference sources such as publications, books, journals, articles, and websites exploited in the research using a specific citation format.
Internet of Things (IoT):
The Internet of Things (IoT) has enabled many smart applications by connecting millions of physical objects to the Internet and facilitating communication between machine-to-human and machine-to-machine. IoT has gained significant attention as an active area of research and development.
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Vehicular Ad-hoc Networks:
VANET is a wireless multi-hop network consisting of self-organizing vehicles as mobile nodes. A main constraint of VANET is frequent topology changes due to the high node mobility. With the increasing number of vehicles equipped with computing technologies and smart devices, inter-vehicle communication has become a promising field of research in wireless communication. VANETs provide a wide range of applications from entertainment to safety, such as dynamic route prediction with less traffic, blind crossing, lane changing assistance, parking payment, and real-time traffic condition monitoring. Another important application for VANETs is the provision of Internet connectivity to vehicular nodes.
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In the real world, machine learning has been increasingly adopted in a variety of fields such as the natural language processing, data mining, virtual assistants, robotics, pattern recognition, traffic prediction, computer games, transportation, healthcare, security systems, recommendation, social media services, and so on. To address the research challenges in modeling the machine learning algorithms, machine learning algorithms have been designed with an increased focus on handling the data inadequacy, class imbalance, and overfitting.
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Digital forensics is an imperative part of handling the criminal investigation in the digital world and retrieving the electronic data to investigate a criminal further. The distinct and dynamic characteristics of digital evidence impede the systematic admissibility of electronic data in a court of law. Hence, the design of digital forensic models relies on the current legislation and privacy laws.
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Cyber security aims to protect cyberspace involving the data, networks, computers, and programs with the objective of the available, integral, and confidential data against the attacks. Nowadays, adopting data science in the design of cyber security mechanisms massively changes the research directions in significantly discovering the insights from the data. The study of the possible cyber attacks in cyberspace, available security mechanisms, and research challenges greatly provides the guidelines for cyber security researchers to develop contextually sound solutions.
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Artificial Intelligence simulates the intelligent behaviors of humans via computers for learning and decision-making. In the real world, the disciplines such as computer science, biology, logic, philosophy, and physiology are increasingly integrated with AI technology. AI plays an indispensable role in the applications of natural language processing, speech recognition, image processing, intelligent robots, and automation systems with remarkable results.
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Blockchain technology guarantees reliable, safe, and trusty benefits for the logistic, business, and government systems. The implementation process and cost of blockchain technology impede its adoption in all industries. The study of blockchain technology paves the way to developing the enhancement in the blockchain concepts while adopting the different systems.
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With the demand for optimization everywhere, the metaheuristic computing becomes essential in intelligently selecting the optimal solution from a large set of available options. The fields of transportation, engineering, business, and social sciences have increasingly adopted metaheuristic computing to reach the result convergence optimally. The adoption of problem-focused strategy is crucial for the combinatorial optimization process among the different metaheuristic algorithms.
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Mobile Ad Hoc Networks:
Rapid evolution of wireless communication needs a self-creating, self-organizing, and self-administering wireless network called MANET. Inherent characteristics of MANET, flexibility, dynamic topology, lack of infrastructure, ease of deployment, self-configuration, and low-cost applications make MANET an essential part of future pervasive wireless environments. Integration of MANET with other networks and fixed infrastructures will be essential to the evolution of future fourth-generation communication networks. Despite the advantages of MANET, many challenging technical issues remain unsolved. The wireless mobile ad hoc nature of MANETs brings new security and scalability challenges to the protocol design.
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Wireless Sensor Networks:
The real-time applications of medicine, military surveillance, and environmental monitoring have become popular with the potential advantages of the Wireless Sensor Networks (WSN). The design of WSN needs to be focused on the essential requirement of the power consumption in the dense deployment of a large set of sensor nodes. The researchers have provided a detailed study to analyze the state-of-the-art research and its challenges in the WSN.
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Software Defined Networks:
With the widespread adoption of the digital society anywhere, Software Defined Networking (SDN) dynamically supports the pre-defined policies based on network configuration, faults, and load-based reconfiguration changes. The vertical integration of the control and data planes breaks promises the network programming with the influence of the changes in the infrastructure. The research challenges in the SDN penetrates the development of novel research direction with ever-evolving technologies.
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Cloud computing technology leverages the technologies towards the development of the individual, business, or industry access with its competitive and operational advantages. The integration of cloud computing technology with the emerging technologies of the Internet of Things (IoT), big data analytics, virtual reality, information modeling, and augmented reality have become the future application areas of cloud computing. From the study of the research thesis, the researchers quickly explore the previous models, solutions, and challenges in cloud computing technology and provide feasible research solutions.
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Fog computing technology greatly assists the business developments such as smart cities and smart campuses by integrating the Internet of Things (IoT) technology over secure information sharing locally or in distributed nature. The unification of the fog computing frameworks ensures the low-cost services to the time-sensitive applications with the developments in resource management, task handling, and fault or delay tolerance. Examining the research challenges in the thesis provides the guidelines for fog computing researchers to design the research objective.
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Edge computing handles the critical situations that arise in the time-sensitive Internet of Things (IoT) applications like smart city, smart electricity, and smart transportation with a very short response time. With the integration of the storage, computing, and network resources at the edge of the environment, the edge computing technology enables the quick development and deployment of the edge applications in both the academia and industry systems from the study of the research challenges and opportunities in the edge computing research area.
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Over the past decades, Cloud security has been an ongoing and challenging research area due to the emerging security attributes of various threats, attack models, risks, and vulnerabilities in the cloud. The investigation of the cloud security attributes with the identification of the security demands, such as the integrity, confidentiality, transparency, and availability, greatly assists in increasing the success rate of the cloud computing technology.
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Mobile Cloud Computing:
The advancements in mobile cloud computing have been heavily inspired by the unique characteristics of mobile computing and the processing of mobile cloud applications. From the analysis of the mobile cloud computing architecture and its research challenges, the imperative research solutions on the computation offloading, task scheduling, resource allocation, load balancing, optimization, and resource management are to be introduced with the correlation of the advancements in the mobile devices and design of the mobile cloud applications.
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Data mining methods have proved their significance in database access applications in social networks, web search engines, and academic and industry-based services. To handle the disparate data sources, heterogeneous data formats, business challenges, research, and scientific fields, the developments in the data mining research have become a vital process over the tremendous improvements in the technologies and complexities in the different fields.
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In the real world, most organizational data are in the form of big data, relying on big data analytics to improve business outcomes. The data-driven analysis from uncovering the hidden relationships in large-scale structured, unstructured, and semi-structured data ensures the potential benefits to the business organizations in terms of understanding customer preferences, effective marketing, operational efficiency, and increased revenue opportunities.
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Mobile computing allows the users to connect with all the sources at all times via the Internet for commercial and business applications. With the increased access of mobile devices, mobile computing often deals with the text, numerical data, audio, image, and video formats at any time during information access and communication with others. The battery life is a primary concern in mobile computing research and is to be resolved and enriched by analyzing existing mobile computing solutions with the combination of advanced technologies.
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With the rapid growth of information available in social networks, individuals and business organizations often suffer from understanding a massive amount of digital information over the Web. Social network analysis targets extracting potential information and finding the relevant information within a reasonable time from the abundance of the data. For instance, the social connectivity of the users with the e-commerce applications assists in providing personalized recommendations based on the users interests.
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Web Technology enables Internet users to communicate between different types of devices by integrating different tools and techniques. Web-based systems and environments have significantly impacted the continuously evolving web data over the Internet. To cope with the advancements in the web technology, the research developments have focused on processing, storing, transmitting, and communicating the web content to influence the effectiveness and productivity of the organization.
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