A data placement strategy based on clustering and consistent hashing algorithm in cloud computing

2014 ◽  
Author(s):  
Qiang Li ◽  
Kun Wang ◽  
Suwei Wei ◽  
Xuefeng Han ◽  
Lili Xu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Placement ◽  
Consistent Hashing ◽  
Hashing Algorithm

Data Placement and Query for Cloud Computing Based on MyHeawood Network

2014 ◽  
Vol 543-547 ◽  
pp. 3100-3104
Author(s):  
Xin Huang ◽  
Yu Xing Peng ◽  
Peng Fei You
Keyword(s):  
Cloud Computing ◽  
Interconnection Network ◽  
Cost Effective ◽  
Data Placement ◽  
Cloud Services ◽  
Massive Data ◽  
Massive Datasets ◽  
The Family ◽  
The Cost ◽  
Hashing Algorithm

The massive data in Data centers network will be frequently accessed massive datasets for cloud services, which will lead to some new requirements and becomes an important issue for interconnection topology and data management in cloud computing. According to the cost-effective, the paper proposes a new interconnection network MyHeawood for cloud computing. MyHeawood is constructed by small switches and servers with dual-port NIC according to recursive method. The data placement strategy in MyHeawood is a hashing algorithm based on the family of hash functions. MyHeawood uses three replicas strategy base on master copy, which is allocated in different sub layer to improve the reliability of data.

Research of Load Balancing Based on NOSQL Database

2014 ◽  
Vol 602-605 ◽  
pp. 3371-3374
Author(s):  
Peng Wang ◽  
Yan Qi
Keyword(s):  
Load Balancing ◽  
Distributed Storage ◽  
Storage System ◽  
Sql Server ◽  
Distributed Storage System ◽  
Nosql Database ◽  
Consistent Hashing ◽  
Cache Hit Ratio ◽  
Hashing Algorithm ◽  
Balancing Principle

The NOSQL database to support data and high concurrent read and write,scalability and high availability features in a distributed storage system which has been applied widely. In this paper, through the research of load balancing in distributed storage system,and it proposes the consistent hashing algorithm and the virtual node strategy, in order to improve the load balancing of the system and increase the cache hit ratio. For the load balancing principle of NOSQL and SQL Server, analysis and comparison of the experimental data.The result shows that, with the increase of the number of virtual nodes, the cache hit ratio of NOSQL is higher than the cache hit ratio of SQL Server.

Research of Cloud Storage and Improved Distributed Strategy of Data Storage

2014 ◽  
Vol 496-500 ◽  
pp. 1812-1816 ◽  
Author(s):  
Hong Xia Mao
Keyword(s):  
Load Balancing ◽  
Data Storage ◽  
Cloud Storage ◽  
Storage System ◽  
Utilization Rate ◽  
Consistent Hashing ◽  
Storage Node ◽  
Load Rate ◽  
Hashing Algorithm ◽  
System Prototype

In this paper, an extensible system prototype of cloud storage is designed. Considering the load balance of cloud storage system, an improved data storage strategy based on consistent hashing algorithm is proposed in this paper. The strategy adopts virtual nodes to storage data and real–time monitoring of load rate of each storage node to adjust load balancing of the whole storage system. In the improved strategy, the priority is introduced into the storage system to rapidly improve the utilization rate of the new storage nodes. The strategy can effectively optimize the performance of the whole storage system, and improve the overall effect of the load balancing.

A High-Speed Railway Data Placement Strategy Based on Cloud Computing

2011 ◽  
Vol 135-136 ◽  
pp. 43-49
Author(s):  
Han Ning Wang ◽  
Wei Xiang Xu ◽  
Chao Long Jia
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Data Access ◽  
Interval Mapping ◽  
Data Placement ◽  
Programming Algorithm ◽  
High Speed Railway ◽  
Mapping Algorithm ◽  
Data Intensive ◽  
Study Results

The application of high-speed railway data, which is an important component of China's transportation science data sharing, has embodied the typical characteristics of data-intensive computing. A reasonable and effective data placement strategy is needed to deploy and execute data-intensive applications in the cloud computing environment. Study results of current data placement approaches have been analyzed and compared in this paper. Combining the semi-definite programming algorithm with the dynamic interval mapping algorithm, a hierarchical structure data placement strategy is proposed. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices. And the dynamic interval mapping algorithm could guarantee better self-adaptability of the data storage system. It has been proved both by theoretical analysis and experiment demonstration that a hierarchical data placement strategy could guarantee the self-adaptability, data reliability and high-speed data access for large-scale networks.

scholarly journals Data Placement in Era of Cloud Computing: a Survey, Taxonomy and Open Research Issues

2019 ◽  
Vol 20 (2) ◽  
pp. 377-398 ◽  
Author(s):  
Avinash Kaur ◽  
Pooja Gupta ◽  
Manpreet Singh ◽  
Anand Nayyar
Keyword(s):  
Cloud Computing ◽  
Workflow Management ◽  
Data Placement ◽  
Future Research ◽  
Research Directions ◽  
Research Issues ◽  
Cloud Computing Environment ◽  
Factors Affecting ◽  
Complete Survey ◽  
Future Research Directions

In cloud computing, data placement is a critical operation performed as part of workflow management and aims to find the best physical machine to place the data. It has direct impact on performance, cost and execution time of workflows. Number of data placement algorithms is designed in cloud computing environment that aimed to improve various factors affecting the workflows and their execution including the movement of data among data centers. This paper provides a complete survey and analyses of existing data placement schemes proposed in literature for cloud computing. Further, it classifies data placement schemes based on their assess capabilities and objectives. Further objectives and properties of data placement schemes are compared. Finally future research directions are provided with concluding remarks.

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