An OptiAssign-PSO Based Optimisation for Multi-Objective Multi-Level Multi-Task Scheduling in Cloud Computing Environment
Advanced Analytics for Disease Tracking & Remote Intravenous Injection Monitoring
DevKraft - Fueling Collaboration in Coding Challenges
Comparative Security and Compliance Analysis of Serverless Computing Platforms: AWS Lambda, Azure Functions, and Google Cloud Functions
Blockchain Healthcare Management using Patients
A Comprehensive Review of Security Issues in Cloud Computing
Data Quality Evaluation Framework for Big Data
An Extended Min-Min Scheduling Algorithm in Cloud Computing
Be Mindful of the Move: A Swot Analysis of Cloud Computing Towards the Democratization of Technology
An Architectural Framework for Ant Lion Optimization-based Feature Selection Technique for Cloud Intrusion Detection System using Bayesian Classifier
GridSim Installation and Implementation Process
A Survey on Energy Aware Job Scheduling Algorithms in Cloud Environment
Genetic Algorithm Using MapReduce - A Critical Review
Clustering based Cost Optimized Resource Scheduling Technique in Cloud Computing
Encroachment of Cloud Education for the Present Educational Institutions
With the Web growing rapidly and increase in user-generated content websites such as Facebook and Twitter, there is a need for fast databases that can handle huge amounts of data. For this purpose, new database management systems collectively called NoSQL are being developed. There are many NoSQL database types with different performances, and thus it is important to evaluate performance. To check the performance, three major NoSQL databases called MongoDB, Cassandra, and Couchbase have been considered. For performance analysis, different workloads were designed. The evaluation has been done on the basis of read and update operations. This evaluation enables users to choose the most appropriate NoSQL database according to the particular mechanisms and application needs.
Cloud Computing deals with the varied virtualization resources. The task scheduling plays a crucial role to enhance the performance of cloud computing. The issue with task scheduling is distribution of tasks within the system in a way that will optimize the performance of the overall system, minimize the makespan, waiting time, maximize throughput, and so on. The paper highlights the comparison between FCFS, Priority based and Round Robin scheduling algorithms. The priority based and round robin scheduling algorithm have showcased better results under certain parameters than the FCFS.
Cloud computing infrastructure is widely used for deploying client's data in sharing environment. Clients can store and retrieve their data, whenever client needs to access his data, cloud provides the required data efficiently. However, some of the important data might be easily damaged, where the data holder can't store in the cloud unless and until the data privacy and confidentiality is guaranteed. It is nice to provide confidentially during the query processing time and retrieval time. To provide confidentially and efficiency for the query processing, The authors use RC4 algorithm which provides security to users data. The RC4 algorithm produces a pseudo-random key stream that issued to generate the cipher text (by XORing it with the plaintext). With this stream cipher, it can be used for encryption by combining it with the plaintext using bit-wise exclusive-or; translate is performed in the same way.
Cloud computing provides resource sharing and handling of applications on internet without having local or personal devices. The data integrity is one of the major challenges in cloud computing. The Outsourced Proof of Retrievability (OPoR) system focuses on Cloud Storage Server (CSS) for prevention of routing attacks and malicious operations of servers. In Public verifiability, the security monitoring is taken by Cloud Audit Server (CAS) for reducing overhead on clients. Hence there is a chance that CAS can take miscellaneous operations, so it is needed to strengthen the secure process of both CSS and CAS. This paper strengthens the Proof of Retrievability model (PoR) process and its dynamic data integrity verification on distrusted and outsourced storages on cloud computing. It strengthens the CAS and CSS operations by using third party entities, which generates unique temporary key for each update or modification of the file from user. Generally, this type of OTP key is generated by the server side, hence it is generated by third party Key-Generator entity. The reset attacks of CAS and cloud storage server is secured by a unique temporary key and deleting the local host replica after verifying the uploaded file proof tags, which was send by CAS and CSS, and the cost of memory and process time is reduced using Elliptic curve cryptography. Thus the proposed system, Improving the Proof of Retrievability (IPoR) model will toughen the resistant of retrievability on upload and update of file operations on cloud computing.
Distributed computing frameworks speak to a standout amongst the most complex processing frameworks as of now in presence. Current uses of Cloud include broad utilization of disseminated frameworks with shifting level of network and use. With a late concentrate on huge scale expansion of Cloud processing, personality administration in Cloud based frameworks is a basic issue for the maintainability of any Cloud-based administration. This zone has additionally gotten extensive consideration from the exploration group and also the IT business. Diverse calculations and methodology are utilized by the specialists. Still distributed computing security is in its center stage. A few IT organizations are concentrating on cloud security and cloud information security. This paper gives a thought regarding security dangers and arrangements.