Projects Related to Cloud Computing

Projects Related to Cloud Computing along with potential solution are provided by us, if are looking for professional touch in your work then you can contact ns3-code.com.

This page shares thesis ideas and topics related to Cloud Computing for experts looking to deepen their knowledge. We also offer tailored guidance for scholars.

 20 Significant Research Problems in Cloud Computing with Potential Solutions

In the domain of cloud computing, a wide range of research problems exist, which should be resolved through advanced solutions. Including possible solutions, we list out 20 significant research problems that have to be addressed in an appropriate manner:

  1. Security and Privacy Issues
  • Problem: Ineffective encryption approaches, illicit access, and data violations.
  • Potential Solution: It is approachable to use AI-based threat identification, blockchain-related security, zero-trust security models, and homomorphic encryption.
  1. Energy Efficiency in Cloud Data Centers
  • Problem: Operational expenses are raised through extensive usage of power in data centers.
  • Potential Solution: Focus on utilizing AI-related workload scheduling, renewable energy sources, server consolidation, and dynamic voltage frequency scaling (DVFS).
  1. Resource Allocation and Management
  • Problem: High costs could be resulted in the case of ineffective resource usage.
  • Potential Solution: To address this issue, we aim to create multi-objective optimization methods, auto-scaling algorithms, and AI-related resource scheduling.
  1. Load Balancing in Cloud Computing
  • Problem: Functionality and accessibility is impacted by unbalanced workload distribution.
  • Potential Solution: Plan to apply dynamic load balancing algorithms related to software-defined networking (SDN).
  1. Multi-Cloud Interoperability
  • Problem: Among various cloud providers, standardization is inadequate for communication.
  • Potential Solution: It is beneficial to create containerized microservices, cloud brokerage services, and open-source APIs.
  1. Latency Reduction in Edge Computing
  • Problem: In processing IoT-created data, higher latency is resulted.
  • Potential Solution: For actual-time processing, we intend to apply distributed caching, 5G networks, and edge AI.
  1. Cloud Data Storage and Management
  • Problem: Extensive costs, ineffective backup approaches, and data redundancy.
  • Potential Solution: Concentrate on employing blockchain-related distributed storage, erasure coding, and deduplication.
  1. Virtual Machine (VM) Migration Overhead
  • Problem: Cloud functionality is impacted by greater migration latency.
  • Potential Solution: With machine learning-related predictive algorithms, carry out real-time migration.
  1. Disaster Recovery in Cloud Computing
  • Problem: Data loss issue is presented through inconsistent backup techniques.
  • Potential Solution: Focus on applying blockchain for data security, multi-cloud backup, and AI-related disaster recovery policies.
  1. Cloud Network Security
  • Problem: Phishing, man-in-the-middle (MITM) assaults, and DDoS assaults.
  • Potential Solution: Plan to implement quantum cryptography, SDN-related network monitoring, and AI-related intrusion detection systems (IDS).
  1. Performance Optimization for Cloud Applications
  • Problem: Cloud-related applications are implemented in an ineffective manner.
  • Potential Solution: It is advantageous to utilize actual-time performance tracking, function-as-a-service (FaaS), and serverless computing.
  1. Real-Time Processing in Cloud-Based IoT
  • Problem: Processing of extensive IoT-based data leads to latency.
  • Potential Solution: To solve this problem, we focus on applying AI-related anomaly detection and edge-fog-cloud hybrid computing.
  1. Cloud Computing for Big Data Analytics
  • Problem: Greater computational power is needed for processing and storing huge datasets.
  • Potential Solution: Make use of AI-based distributed computing, Hadoop, and Apache Spark.
  1. Quantum Computing in Cloud
  • Problem: For improved processing, consider the quantum computing incorporation with cloud.
  • Potential Solution: Using hybrid quantum-classical algorithms, the quantum cloud frameworks have to be created.
  1. Blockchain for Cloud Security
  • Problem: Focus on the significant issues such as access control and data morality.
  • Potential Solution: It is approachable to employ decentralized authentication and blockchain-related access control.
  1. Green Cloud Computing
  • Problem: From extensive cloud data centers, consider the carbon discharges.
  • Potential Solution: Concentrate on utilizing AI-based energy optimization, energy-aware scheduling, and renewable energy.
  1. Software-Defined Cloud Computing (SD-Cloud)
  • Problem: Adaptability is needed in conventional cloud networking.
  • Potential Solution: To address this issue, we plan to apply network function virtualization (NFV) and software-defined networking (SDN).
  1. Hybrid Cloud Security
  • Problem: Security risks are increased through the combination of private and public cloud.
  • Potential Solution: Consider employing AI-related compliance monitoring and zero-trust security architecture.
  1. Cost Optimization in Cloud Services
  • Problem: For cloud service providers, greater operational expenses are resulted.
  • Potential Solution: Plan to utilize cloud cost prediction, serverless architecture, and spot instances.
  1. Artificial Intelligence in Cloud Security
  • Problem: Specifically for advanced cyber hazards, the conventional security models are inadequate.
  • Potential Solution: It is beneficial to employ self-learning security frameworks, threat intelligence, and AI-related anomaly detection.

How to install CloudSim using eclipse?

CloudSim is an efficient, cloud computing-based simulation framework that can be installed with Eclipse by following several guidelines. In order to carry out this mission, we offer a complete procedural instruction explicitly:

Step 1: Install Eclipse IDE

  1. Download Eclipse: Focus on downloading the current version of Eclipse IDE from the Eclipse download page.
  2. Install Eclipse: Appropriate to our operating system, the installation guidelines have to be followed.

Step 2: Install Java Development Kit (JDK)

  1. Download JDK: The JDK has to be downloaded by visiting the AdoptOpenJDK or Oracle JDK download page.
  2. Install JDK: Relevant to our operating system, we should adhere to the installation guidelines.
  3. Set up Eclipse to utilize JDK:
  • The Eclipse must be opened.
  • Click on Window -> Preferences.
  • Go to Java -> Installed JREs.
  • Choose Standard VM after clicking Add. Then, select Next.
  • Search for the JDK installation directory by clicking Directory. After that, select Finish.
  • The recently appended JDK should be chosen. Then, select Apply and Close.

Step 3: Download and Extract CloudSim

  1. Download CloudSim: Download the current version of CloudSim from the CloudSim GitHub repository.
  2. Extract CloudSim: To the preferred directory, the downloaded ZIP file must be extracted.

Step 4: Develop a New Project in Eclipse

  1. Develop a New Java Project:
  • The Eclipse has to be opened.
  • Navigate to File -> New -> Java Project.
  • For our project, offer a specific name (for instance: CloudSimExample). Then, select Finish.

Step 5: Include CloudSim Libraries to Our Project

  1. Append External JARs:
  • In the Project Explorer window, we have to right-click on our project.
  • Choose Properties.
  • Click on Java Build Path -> Libraries -> Add External JARs.
  • The directory should be accessed, in which the CloudSim is extracted. Choose all JAR files by opening the jars folder.
  • Select Open. After that, choose Apply and Close.

Step 6: Build a New Java Class for CloudSim Instance

  1. Build a New Class:
  • In our project, the src folder has to be right-clicked.
  • Choose New -> Class.
  • For our class, a particular name must be offered (for instance: CloudSimExample). Then, select Finish.

Step 7: Write CloudSim Sample Code

  1. Sample Code: Within our recently developed class, we should copy and paste the below specified example code. Using one cloudlet, one VM, one host, and one data center, this code configures a simple CloudSim simulation.

import org.cloudbus.cloudsim.allocationpolicies.VmAllocationPolicySimple;

import org.cloudbus.cloudsim.brokers.DatacenterBrokerSimple;

import org.cloudbus.cloudsim.cloudlets.Cloudlet;

import org.cloudbus.cloudsim.cloudlets.CloudletSimple;

import org.cloudbus.cloudsim.core.CloudSim;

import org.cloudbus.cloudsim.datacenters.Datacenter;

import org.cloudbus.cloudsim.datacenters.DatacenterSimple;

import org.cloudbus.cloudsim.hosts.Host;

import org.cloudbus.cloudsim.hosts.HostSimple;

import org.cloudbus.cloudsim.resources.Pe;

import org.cloudbus.cloudsim.resources.PeSimple;

import org.cloudbus.cloudsim.vms.Vm;

import org.cloudbus.cloudsim.vms.VmSimple;

import org.cloudsimplus.builders.tables.CloudletsTableBuilder;

import java.util.ArrayList;

import java.util.List;

public class CloudSimExample {

public static void main(String[] args) {

// Initialize the CloudSim library

CloudSim simulation = new CloudSim();

// Create a data center

Datacenter datacenter = createDatacenter(simulation);

// Create a broker

DatacenterBrokerSimple broker = new DatacenterBrokerSimple(simulation);

// Create a VM

Vm vm = new VmSimple(1000, 2); // 1000 MIPS, 2 PEs

vm.setRam(2048).setBw(1000).setSize(10000); // 2 GB RAM, 1 GB BW, 10 GB Storage

// Create a cloudlet

Cloudlet cloudlet = new CloudletSimple(10000, 2); // 10,000 MI, 2 PEs

cloudlet.setFileSize(300).setOutputSize(300); // 300 KB File and Output Size

// Submit VM and Cloudlet to broker

broker.submitVm(vm);

broker.submitCloudlet(cloudlet);

// Start the simulation

simulation.start();

// Print results

new CloudletsTableBuilder(broker.getCloudletFinishedList()).build();

}

private static Datacenter createDatacenter(CloudSim simulation) {

// Create a list of processing elements (PEs)

List<Pe> peList = new ArrayList<>();

peList.add(new PeSimple(1000)); // 1000 MIPS per PE

// Create a host

Host host = new HostSimple(2048, 10000, 1000000, peList); // RAM, BW, Storage

host.setVmScheduler(new org.cloudbus.cloudsim.schedulers.vm.VmSchedulerTimeShared());

// Create a list of hosts

List<Host> hostList = new ArrayList<>();

hostList.add(host);

// Create and return a data center

return new DatacenterSimple(simulation, hostList, new VmAllocationPolicySimple());

}

}

Step 8: Execute the CloudSim Instance

  1. Execute the Project:
  • In the Project Explorer window, we need to right-click on the CloudSimExample class.
  • Then, choose Run As -> Java Application.
  • By demonstrating the aspects of the simulated cloudlet execution, the Eclipse Console will exhibit the outcome.

Relevant to cloud computing, several research problems are specified by us, encompassing possible solutions. For assisting you to install CloudSim with Eclipse, we provided an in-depth instruction in a clear manner, along with a sample code.

Thesis Related to Cloud Computing

Thesis Related Ideas on Cloud Computing which we have worked are listed here, we have gained online trust for more than 2000+ scholars. If you are looking for a precise and clear work then ns3-code.com will serve you the best. 

  1. CA-DAG: Communication-Aware Directed Acyclic Graphs for Modeling Cloud Computing Applications
  2. Load balancing in cloud computing using particle swarm optimization on Xen Server
  3. Enhanced cloud computing security and integrity verification via novel encryption techniques
  4. Dynamic load balancing methods for resource optimization in cloud computing environment
  5. A formal specification approach of Privacy-aware Attribute Based Access Control (Pa-ABAC) model for cloud computing
  6. A Network Virtualization Approach in Many-core Processor Based Cloud Computing Environment
  7. A Critical Review of Cloud Computing Environment for Big Data Analytics
  8. Approximating resource provisioning cost in cloud Computing using reduced scenario set obtained from Fast Forward Selection algorithm
  9. Delay-Optimal Task Offloading for UAV-Enabled Edge-Cloud Computing Systems
  10. Affordable and Energy-Efficient Cloud Computing Clusters: The Bolzano Raspberry Pi Cloud Cluster Experiment
  11. Multimedia Processing Pricing Strategy in GPU-Accelerated Cloud Computing
  12. Towards Solving a Mixture of Issues Using Artificial Intelligence and Cloud Computing
  13. Virtual machine-based task scheduling algorithm in a cloud computing environment
  14. Secure Data Sharing in Cloud Computing Using Revocable-Storage Identity-Based Encryption
  15. A comber approach to protect cloud computing against XML DDoS and HTTP DDoS attack
  16. Use of body knowledge and cloud computing tools to develop software projects based in innovation
  17. Novel Resource Allocation Model and Algorithms for Cloud Computing
  18. An overview on cloud computing platform spark for Human Genome mining
  19. Review on mitigation of distributed Denial of Service (DDoS) attacks in cloud computing
  20. Mobile Cloud Computing by In-vehicle Servers Based on Delay Tolerant Network Protocol

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