Cloud Computing Projects for Final Year

Cloud computing enables the parallel process for performing high-speed massive data computation. Then, it provides large-capacity storage with an availability open-source software and datasets.  In addition, it improves the comprehensive learning skills for next generation cloud crowdsourcing.

This page mainly focuses on novel Cloud Computing Projects for Final Year Students with Cloud oriented research areas!!!

Based on this, we have figured out some important features that manipulate the cloud research directions. In specific, these features analyze the similarity and dissimilarity of present computing with conventional computing.

What are the Characteristics of Cloud Computing?

• Measured Service – Automated analysis of resource utilization through metering capability. (For instance: processing, storage, user accounts, bandwidth, etc.)
• Rapid Elasticity Services – Adaption of sudden changes in resource provisioning i.e., scaling up of system
• Resource Pooling – Dynamic allocation of resources based on client requests. Here, the resources are collectively pooled in server (multi-tenant model)
• On Demand Self Service – Data users can give and take the desired servicesin the absence of human involvement
• Broad Network Access – Wide range of network accessibility by standard approaches

We have experts from all regions of world who are well-versed to spot out the current research trends in Cloud Computing. In order to give accurate visions about the recent research areas, we frequently update our knowledge from Cloud fundamentals to latest advancements.

Research Ideas in Cloud Computing

• Cloud based Access Control Model
• Cloud Workload Balancing Strategies
• Cryptography Techniques in Cloud Computing
• Efficient Outsourced Data Integrity Auditing
• Secrecy Preserving Data Services and Storage
• Cloud Task Virtualization, Allocation and Optimization
• Secure Cloud based Key and Access Control Management
• Resource Scheduling and Allocation
• Task Scheduling in Mobile Cloud
• Load Balancing and Task Scheduling
• Fault Tolerance and Storage Schemes
• Service Level Agreement and Analyze Quality Metrics
  • Budget
  • Cost
  • Resource utilization
  • Response Time

Furthermore, we have sufficient skill in handling various kinds of cloud virtualization. It may vary based on the software/application requirements. For your reference, we given some commonly used cloud virtualization.

• Application Virtualization: Through different methods, the application can be executed from remote place. The approach may fall under any of these followings,
  • Desktop Virtualization
  • Application Streaming
  • Virtual Machine (VM) / Virtual Desktop Infrastructure (VDI) packages
  • For instance: Microsoft Soft Grid
• Server Virtualization:
  • Supports multi-operating system and applications. Also, it is provisioned with Hardware Abstraction Layer (HAL) in every OS.
• Host Virtualization:
  • Here, the OS is executed as the Guest to function on host / VM interface
• Storage Virtualization:
  • In this, the user data is stored under the control of virtual storage system but the connected servers do not have idea of data
• Network Virtualization:
  • Supports cost-effective virtual network to easilyknow the logical connection of application without physical network.
  • For instance: VLAN
• Full Virtualization:
  • Establish communication among VM hypervisors without guest OS alteration

As we all already known that Cloud Computing is comprised with chain of services for accessing distributed resources through web. Here, we have listed some significant issues that categorized by the end–user, service provider and infrastructure.

Research Issues in Cloud Computing

• Infrastructure
  • Network Service and Hardware
  • Cloud Data Storage
  • Other Hardware
• End-User
  • Information Visibility
  • Cloud Governance Impact
  • Data Security and Privacy
  • Cloud based Web Browser Security
  • Reliable Authentication and Integrity
  • Identity and Accesses Management
• Service Provider
  • Data Communication
  • Trust based Third-Party Software
  • Possible Security Attacks
  • Subsidiary Processes and Services
  • Privacy based Access Control
  • Identity and User Authentication
  • Performance and Workload Unpredictability

Primarily, cloud enables the big data processing, manipulation, analysis and storage. And, there are numerous Cloud Service Providers (CSPs) available. In that, some may offer the services for their commercial purpose. For example,

• Google Compute Engine
• Elastic Compute Cloud (EC2)
• Microsoft Azure (MS)
• Amazon Web Services (AWS)

In general, CSP deals with 3 major kinds of service models and they are Platform as a Service (PaaS), Software as a Service (SaaS) and Infrastructure as a Service (IaaS). For instance, in the case of robotic applications, the cloud needs some extraordinary services or infrastructures to support both data sharing and transition.

Over past few times, Robot as a Service (RaaS) is launched to bring smooth collaboration of embedded devices and robotics. Ultimately, cloud robotics becomes a fast-growing research area. The architecture of this system is classified into following modules,

• Cloud Infrastructure – Multi-Servers (Proxy / Performance), Huge Databases and so on
• Bottom Facility –UAV, UGV, Automatic Tools and more

In addition, we have listed recent research trends in cloud computing that are gathered from the current research journal papers, magazines and more.

Research Areas in Cloud Computing

• Cloud Aware 5G/6G Networks
• Cloud Deep Learning Solutions
• Software Engineering Services
• Cloud assisted Fog Computing
• SLA-Driven Cloud AutoScaling and QoS
• Integration of Cloud with Future IoT
• Cloud based Quantum Computing
• Bitcoin and Cryptocurrency Mining
• Kubernetes and Containers Technology in Cloud
• Artificial Intelligence Infrastructure
• Decentralized Cloud Security using Blockchain
• Big Data Storage and Analytics in Cloud
• Software Defined Architecture in Cloud Environs
• Cloud based Serverless Computing and Security
• Impact of Data Science in Cloud Applications

Important things to remember while selecting Cloud Computing Projects for Final Year students are listed below,

• Do Thorough Survey
• Collect information about various problems that current not solved
• Identify the your interested research idea
• Construct linked supportive system (internships, related experts contact)
• Select the scope of your handpicked idea

To the end, this support system helps the scholars to have sufficient knowledge in developing their project. Also, we have given that how we deliver our service for Cloud Computing project development.

Project Support Services for you

• Domain and topics title list
• Base papers set and other materials
• Teamviewer support and the phone support
• Software installation and execution support
• Source codes and project video
• Assignment writing and seminar program design
• Set of UML diagrams drawing
• Help for the following
  • Power point preparation
  • Review submission
  • Project report writing
  • Project implementation

How do you Simulate Cloud Environment?

Next, we can see about how we are going to simulate the cloud system. Also, we concentrate on scalability factor which signifies the fast performance of tool in the time of increased requests.

Importance of cloud simulators

All the cloud models have varying unique features which are specially intended to achieve objectives.  It may be fast elasticity, geographic location, greater access time, etc. Particularly, it plays major role in simplifying complicates systems. Further, the newly developing approaches also depend on these features. For instance: the recent scholars are working with load balancing, cost modeling, security and power saving models. The first step to develop the project is to pick the suitable cloud simulator based on system needs. For you information, we have listed some broadly used tool with their supportive programming languages.

• DCSim – Java
• iFogSim – Java
• EdgeCloudSim – Java
• iCanCloud – C++/Ned
• myIFogSim – Java
• CloudSim – Java
• CloudAnalyst – Java
• CloudNet – Java
• GreenCloud – C++/TCL (Support network level operations)

Next, we can discuss about the critical performance parameters that popularly used in industrial cloud services. Since, metrics are important to measure the overall performance of the system.

What are the key components of performance metrics in cloud operations?

• System / Service Availability
• Security
• Delay
• Scalability
• Volume
• Reply Time
• Bandwidth
• Trustworthiness

Further, if you want to know more creative ideas to your Cloud Computing Projects for Final Year then approach us. We are ready to provide our helping hand to fulfill your requirements.