Research Topics

Research Topics 

Cloud Computing Topics

Choosing a PhD topic in Cloud Computing, no doubt is cumbersome since it is a multidisciplinary academic field. A PhD researcher is expected to analyse, describe, and suggest supplements, virtualized resources, and delivery models in Information Technology. There are many research areas within Cloud Computing which involve both qualitative and quantitative research to bring forth charting innovative techniques. Following are the areas and PhD topics in Cloud Computing requiring potential research:

An Idea on Developing Secure Resource Utilization and Load Balancing in PAAS based Cloud Computing Techniques.

Improving Cloud data security through Hybrid Verification Technique based on Biometrics and Encryption system

Privacy Preservation in Cloud Computing for user data through trust based mechanism.

An innovative IOT and Cloud Computing based health monitoring system with the aid of machine learning approach.

User Profiling System Design for Cloud Computing Security using Hybrid Cuckoo Search Algorithm.

Resource Scheduling Strategy in Cloud Computing with the aid of clustering and optimization algorithm

Cloud Computing Data based prediction of fault in power generators using mining algorithm and Artificial intelligence.

Improving cloud computing datacenter energy efficiency and security with the aid of optimization approach.

An efficient Network-Aware Virtual Machine Placement model in Cloud Computing using hybrid optimization techniques.

Optimization based QoS-Aware Task Scheduling in Cloud Computing.

Computer Science Topics

The research topic selection is academically challenging for the student who is not an expert in the concerned discipline and recently embarked on the PhD journey. The dilemma students most often face is to understand how to make a topic reasonable: whether it should touch upon multiple research areas or should only be focusing on simple ideas and theories. We help hundreds of such students through our topic selection services under which our experts collaborate with them to synthesize and refine the information into a concise and unique research topic. Below are provided with the PhD topics in Computer Science formulated and suggested by our experts to demonstrate the quality of our work we deliver to our clients:

An efficient technique for risk assessment in component based software architecture using Clustering and classification.

Hybrid optimization-Fuzzy k means clustering based Software Reliability Prediction

Software Fault Detection based Reliability Growth Modelling Using Enhanced BAT optimization algorithm.

Software reliability growth model prediction using Hybrid Dolphin Swarm Optimization approach

Maintainability prediction of open source software using Adaptive genetic neural network.

Machine learning approaches for software reliability prediction with the aid of optimized clustering algorithm.

Premature Recital Analysis of Cloud Computing Services with profit optimization for Scientific Computing.

Sightseeing Interrogation Optimization Methods in Interpersonal Databases

Optimization of Computer Network for Resourceful Enhancement using artificial intelligence

Demonstration and Optimization for large scale data established on Hadoop

Data Mining Topics

The purpose of researcher pursuing PhD in Data Mining is mainly to manipulate a large amount of data in the database determining the various variables to contribute to the solutions of gap in other researches, their problems, and solutions. To find a good research topic and problem is as important as it is to find a good solution through extensive research. Choosing a topic is the work that a researcher should do or learn to do. As our experts always advise, a novice researcher’s first step should be to first look into the various research topics, researches, and experiments to formulate your own. Following are some PhD topics in Data Mining which can help you take this step a little ahead:

A stride towards customer review extraction using frequent pattern mining algorithms and soft computing techniques.

Medical data analysis with the aid of association rule mining and artificial intelligence.

Intrusion detection and classification with the aid of data mining algorithm and Modified neural network.

An efficient technique to improve the customer management using Pattern mining algorithm.

Customer review based e-commerce product rating using frequent pattern mining algorithm and sentiment analysis.

Opinion mining based detection of fake recommendation in e commerce with the aid of machine learning approach.

Prediction of user behaviour / emotions based on web usage mining with the aid of artificial intelligence.

Web usage data classification for web personalization using clustering and machine learning techniques.

An efficient technique for Disease prediction from medical data using data mining algorithm and ANN classifier.

An efficient web page recommendation system using optimized frequent pattern mining and Neural classifier.

Big Data Topics

Students of PhD in Big Data experiment using various technologies to develop algorithms and models by which the big data sets can be managed with sophistication. PhD in Big Data is a multidisciplinary research program which enables the students to perform little but essential tasks of statistician, analyst, and an engineer etc. It is evident that it is not an easy task to get pace up with a multidisciplinary research and the struggle begins from the topic selection. But the academic field and previous researches are likely to lead to a redefinition of the research topic. Having an eagle eye on Big Data and its applications can help you better identify your research topic and an influential research in the discipline. This is why, we have derived a few PhD topics in Big Data below:

MFCM-OMA based big data clustering in E – commerce

A stride towards Privacy preservation in E commerce with the aid of ElGamal Cryptosystem.

Collaborative filtering based recommendation for predicting the E-commerce service using clustering algorithm.

Behavioural Analysis of a Fuzzy Rule Based Classification System for Big Data Classification with Data Mapping and bagging approach in a MapReduce Scheme

Incorporating Apriori Algorithm with MapReduce approach to Remove Classification problems

Analysis on MapReduce Framework in Imbalanced Classification Systems using Fuzzy Based AdaBoost Algorithm

Designing an Effective Approach for Mining Big Data from Heterogeneous Data Streams Using Fuzzy Frequent Pattern Method

Optimizing Fault Detection for Big Data Analytics through Evolutionary Computation.

An efficient approach for detection of failure in big data analytics using clustering and classification technique

An efficient technique for improving classification problem using clustering approach.

Network Security Topics

PhD in Network Security is booming in research academia, many students are getting enrolled in PhDs for getting equipped with the research and technical skills to gather, analyse, and discover the new findings regarding security threats. Every research project becomes good when a well-defined topic is decided and worked upon. When a student looks forward to initiate the research process, first thing comes in mind is to develop a relevant and appropriate topic keeping the purpose and requirement of the research in mind. No doubt, many novice researchers find it extremely difficult to formulate such a topic in network security because this is still emerging field in Information Security. But only a few suggestions of specific and well-defined research topics can ease this task. For this purpose, our research specialists have exemplified the selective PhD topics in Network Security:

A Comparative Approach on Enhancing Lifetime of Wireless Sensor Networks using Improved Genetic Algorithm and Cuckoo Search Algorithm

Analysis on Improving the lifetime of Wireless Sensor networks By Framing the Connectivity Between the Sensors.

An efficient technique for securing network using ElGamal cryptosystem and classification algorithms.

A novel hybrid routing algorithm for secure data transfer in mobile ad-hoc network (MANET)

Intrusion detection in Wireless sensor network using routing and classification algorithm.

Optimized Symmetric key based security improvement in wireless sensor networks.

An efficient routing technique based diagnosis of faults in sensor nodes using optimization technique.

Improving security in data packet transmission through wireless network using optimized routing protocol.

A Secured and Efficient Resource sharing in Psycho Evolutionary Computing

Analysis on Creating an Efficient and Secured Transmission in Bio inspired systems

Image Processing Topics

A PhD in Image Processing is an in-depth research project on an academic topic which is focused and yet highly specialised. It should be noted that useful and informative researches are supposed to re-visit the problems posed and investigated by other researchers. Thence, your first plan is to identify area of interest within the field of latest PhD research topics in Image processing, choose a realistic topic or research problem, draw a well-defined plan, and compose a research work which can be used by others to build their research upon. To help you narrow down your quest for the topic selection for such an effective research, provided below are the PhD topics in Image Processing:

Optimal Eco state network (O-ESN) based image restoration technique to improve Image quality

Breast cancer Detection from mammogram images with the aid of image restoration technique using HNN.

FODM-MNN (Fractional-Order Differentiation Model) based nodule detection from Low-Dose CT lung image.

Image Decomposition for Low-Dose CT Image Processing with the aid of Feature extraction and Machine learning algorithm.

An approach on Identification of Circuit breaks Using Morphological Characteristics Based Segmentation.

Efficient technique for weather forecasting based on satellite images with the aid of machine learning techniques.

Environmental change prediction with the aid of extensive segmentation and machine learning approach from satellite images.

Medical image classification for disease prediction with the aid of Machine learning approach.

Hybrid optimization techniques to improve feature selection in image classification techniques.

Embedded Systems Topics

PhD in Embedded systems and technology combines the study of computer hardware and software within a device that is designed to perform a particular and constant function. Embedded systems are found in the functioning devices in electronics such as mobile phones, automobiles, and digital cameras, etc. PhD candidates in electronics and embedded technology combine and explore theoretical knowledge with laboratory work regarding the selection, adaption and development of hardware and software components. Once you become a doctorate in Embedded System, you are offered to pursue career as software developer, embedded system engineer, software engineer, embedded systems designer et al. or can become an academic researcher in the discipline. To become a doctorate, you must do a valid research in the concerned discipline and demonstrate your research skills through an influential thesis.

PhD topics in Embedded Systems:

IOT based alert system for public transportation regarding passenger requirement and availability

Real time task division in Processor based embedded system using sensor and machine learning.

An efficient Energy Prediction model for Solar-Energy-Powered Embedded Systems using Artificial Intelligence.

An approach on implementing GPS based embedded approach for Monitoring Endangered Species.

Real time embedded based system for monitoring the traffic condition for accident control.

An efficient soil moisture monitoring system for improvement in agriculture using real time embedded systems.

Analysis on Prediction of Deficiency in Plant with Incorporation of embedded sensor system and artificial intelligence.

Improving Node Security in Mobile ad-hoc network (MANET) by employing sensor nodes on clustered node centres.

An efficient embedded IOT based system to predict the traffic conditions for passenger route selection.

An innovative technique for waste management using GPS monitoring and data classification.

Electronics and Communication Engineering Topics

PhD topics in Electronics and Communication Engineering exemplify what type of topic is good for what type of research:

An efficient technique for Received-Signal-Strength Threshold Optimization based on filtering and optimization technique.

Enhanced Neural Network Classifier for pattern recognition of speech signal based on discrete wavelet transforms.

An efficient technique for recognition of Hyper Nasality from Speech Signal using Wavelet transform and ANN.

A novel technique for noise cancellation in speech signals with the aid of hybrid optimization algorithms.

Bayesian interface based Modulation Classification for MIMO-OFDM Signals using enhanced neural network.

Effective analysis on Power and Memory Optimization Techniques for Embedded Systems

Optimization of Performance Analysis and De Noising Techniques for Ultrasound images using Anisotropic Diffusion Filter.

Effectual research on Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques.

Optimization of resource and bandwidth allocation in Wireless Networks Performance analysis using Artificial Intelligence.

Minimization of Monotonous Examination and Design Contemplation of Cassegrain for Satellite Communication.