RAPID: A Fast Data Update Protocol in Erasure Coded Storage Systems for Big Data

Author(s):  
G. J. Akash ◽  
Ojus Thomas Lee ◽  
S. D. Madhu Kumar ◽  
Priya Chandran ◽  
Alfredo Cuzzocrea
Keyword(s):  
Big Data ◽  
2015 ◽  
Vol 50 ◽  
pp. 264-269
Author(s):  
Thirumalaisamy Ragunathan ◽  
Sudheer Kumar Battula ◽  
Rathnamma Gopisetty ◽  
B. RangaSwamy ◽  
N. Geethanjali

Author(s):  
Kenji Nakashima ◽  
Joichiro Kon ◽  
Saneyasu Yamaguchi ◽  
Gil Jae Lee ◽  
Jose Fortes
Keyword(s):  
Big Data ◽  

Author(s):  
Mohsen Karimzadeh Kiskani ◽  
Hamid R. Sadjadpour ◽  
Mohammad Reza Rahimi ◽  
Fred Etemadieh

Author(s):  
Sebastian Dippl ◽  
Michael C. Jaeger ◽  
Achim Luhn ◽  
Alexandra Shulman-Peleg ◽  
Gil Vernik

While it is common to use storage in a cloud-based manner, the question of true interoperability is rarely fully addressed. This question becomes even more relevant since the steadily growing amount of data that needs to be stored will supersede the capacity of a single system in terms of resources, availability, and network throughput quite soon. The logical conclusion is that a network of systems needs to be created that is able to cope with the requirements of big data applications and data deluge scenarios. This chapter shows how federation and interoperability will fit into a cloud storage scenario. The authors take a look at the challenges that federation imposes on autonomous, heterogeneous, and distributed cloud systems, and present approaches that help deal with the special requirements introduced by the VISION Cloud use cases from healthcare, media, telecommunications, and enterprise domains. Finally, the authors give an overview on how VISION Cloud addresses these requirements in its research scenarios and architecture.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 118696-118706
Author(s):  
Yupeng Hu ◽  
Qian Li ◽  
Wei Xie ◽  
Zhenyu Ye

Author(s):  
Chao Yin ◽  
Jianzong Wang ◽  
Changsheng Xie ◽  
Jiguang Wan ◽  
Changlin Long ◽  
...  

2018 ◽  
Vol 44 ◽  
pp. 00202 ◽  
Author(s):  
Monika Żygadło ◽  
Jerzy Kotowski ◽  
Jacek Oko

Because of growing amount of the data(known as „big data”) needed to be store and process there is a rapid growth of usage electricity and emission. In this paper we present the IT solution of this problem: green computing, solutions to storage and manage the energy and IT support needed to manage and control those systems. The article presents the main idea and already implemented solutions.


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