GridOPTICS(TM) A Novel Software Framework for Integrating Power Grid Data Storage, Management and Analysis

Author(s):  
Ian Gorton ◽  
Jian Yin ◽  
Bora Akyol ◽  
Selim Ciraci ◽  
Terence Critchlow ◽  
...  
2018 ◽  
Vol 50 (6) ◽  
pp. 1-51 ◽  
Author(s):  
Yaser Mansouri ◽  
Adel Nadjaran Toosi ◽  
Rajkumar Buyya

2021 ◽  
Author(s):  
Qinyi Lei ◽  
Qi Sun ◽  
Linyan Zhao ◽  
Dehua Hong ◽  
Cailiang Hu

Author(s):  
Ryan Hafen ◽  
Tara Gibson ◽  
Kerstin Kleese van Dam ◽  
Terence Critchlow
Keyword(s):  

2013 ◽  
pp. 294-321
Author(s):  
Alexandru Costan

To accommodate the needs of large-scale distributed systems, scalable data storage and management strategies are required, allowing applications to efficiently cope with continuously growing, highly distributed data. This chapter addresses the key issues of data handling in grid environments focusing on storing, accessing, managing and processing data. We start by providing the background for the data storage issue in grid environments. We outline the main challenges addressed by distributed storage systems: high availability which translates into high resilience and consistency, corruption handling regarding arbitrary faults, fault tolerance, asynchrony, fairness, access control and transparency. The core part of the chapter presents how existing solutions cope with these high requirements. The most important research results are organized along several themes: grid data storage, distributed file systems, data transfer and retrieval and data management. Important characteristics such as performance, efficient use of resources, fault tolerance, security, and others are strongly determined by the adopted system architectures and the technologies behind them. For each topic, we shortly present previous work, describe the most recent achievements, highlight their advantages and limitations, and indicate future research trends in distributed data storage and management.


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