scholarly journals A dependable storage service system in cloud environment

2014 ◽  
Vol 8 (4) ◽  
pp. 574-588 ◽  
Author(s):  
Chin-Chen Chang ◽  
Chin-Yu Sun ◽  
Ting-Fang Cheng
Keyword(s):  
Service System ◽  
Cloud Environment ◽  
Storage Service

scholarly journals Building an Object Cloud Storage Service System using OpenStack Swift

2014 ◽  
Vol 102 (10) ◽  
pp. 39-42
Author(s):  
Sridevi Bonthu ◽  
Y S S R Murthy ◽  
M. Srilakshmi
Keyword(s):  
Cloud Storage ◽  
Service System ◽  
Cloud Storage Service ◽  
Storage Service

scholarly journals Research on key technologies of NBD storage service system based on load classification

AIP Advances ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 125124
Author(s):  
Qinlu He ◽  
Zhimin Yu ◽  
Genqing Bian ◽  
Weiqi Zhang ◽  
Kexin Liu ◽  
...  
Keyword(s):  
Service System ◽  
Storage Service ◽  
Key Technologies

scholarly journals Building a Cloud Storage Service System

2011 ◽  
Vol 10 ◽  
pp. 691-696 ◽  
Author(s):  
Chengzhang Peng ◽  
Zejun Jiang
Keyword(s):  
Cloud Storage ◽  
Service System ◽  
Cloud Storage Service ◽  
Storage Service

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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