Efficient Distributed Index Structure and Encrypted Query Processing Scheme for Cloud Computing Environment

2017 ◽  
pp. 499-505
Author(s):  
Yeonwoo Jang ◽  
Hyunjo Lee ◽  
Jae-Woo Chang
Keyword(s):  
Cloud Computing ◽  
Query Processing ◽  
Index Structure ◽  
Computing Environment ◽  
Processing Scheme ◽  
Cloud Computing Environment ◽  
Distributed Index

scholarly journals Data Service Trust Measurement in Cloud Environment

2019 ◽  
Author(s):  
Lin Shi ◽  
Zilong Wang ◽  
Ning Chen ◽  
Jie Chen
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Virtual Machines ◽  
Management Service ◽  
Cloud Environment ◽  
Computing Environment ◽  
Optimization Scheme ◽  
Processing Scheme ◽  
Cloud Computing Environment ◽  
Cloud Data

Abstract Highly trusted issues will be one of the main obstacles to a new era of highly trusted cloud computing. In the cloud computing environment, because sensitive applications and user data are put into the cloud, they run in virtual machines in the data center. Among them, due to the existence of access vulnerability, virtualization vulnerability, web application vulnerability, etc., high trust issues arise from data control, identity authentication, lack of information and other related issues. The introduction of trust mechanisms can be very facilitate the solution of related issues, achieve highly trusted quantification, analysis, and modeling of cloud data centers, meet high trust requirements, and provide users with a highly trusted cloud computing environment. This article mainly studies the trust measure of data services in cloud environment. In this paper, the optimization scheme is verified through experiments, and the traditional big data processing scheme, the original Sahara and the optimization scheme are compared in six cases. Overall, the optimization scheme has a significant performance improvement. Compared with the default configuration of Sahara, the configuration of the new interface has increased the throughput in DFSIO by 120%. Using the design of the unified cache management service, Tachyon can reach 13 in specific situations. In the execution time of Sort workloads, the optimization scheme generally decreased by about 50% compared to the original Sahara, and the memory utilization increased from 80% to 96% in our experiments, but in the cache isolation and other areas need to be improved. The results are basically in line with expectations, which also confirms the rational thinking and value of this article on BDAaS performance research.

User Annotated Resource Allocation in Cloud Computing Environment

2011 ◽  
Vol 4 (3) ◽  
pp. 132-133
Author(s):  
Krishnakumar L Krishnakumar L ◽  
◽  
Jimy Joy
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Computing Environment ◽  
Cloud Computing Environment

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Sign in / Sign up

Export Citation Format

Share Document