DocumentCode :
1602508
Title :
A Self-Optimized Storage for Distributed Data as a Service
Author :
Al Nuaimi, Klaithem ; Mohamed, Nader ; Al Nuaimi, Mariam ; Al-Jaroodi, Jameela
Author_Institution :
UAE Univ., Al Ain, United Arab Emirates
fYear :
2015
Firstpage :
84
Lastpage :
89
Abstract :
In this paper we propose an automated partial replication storage technique for the cloud, which we call ssCloud. We associate this technique with a dual direction load balancing technique using the cloud servers. We show that by having dual direction load balancing and an automated partial replication of the storage we enhance the download speed from the cloud and reduce the cost of storing multiple replicas on multiple cloud nodes. This is done by having two cloud interfaces, one for the download requests from the clients (load balancing module) and another for uploading and splitting files into blocks and saving them on the different cloud servers (FileController). We also compare our approach to other similar approaches and describe the benefits of using ssCloud.
Keywords :
cloud computing; distributed processing; resource allocation; storage management; FileController; cloud interfaces; cloud servers; cost reduction; distributed data-as-a-service; dual direction load balancing technique; file splitting; file uploading; partial replication storage technique; self-optimized storage; ssCloud; Distributed databases; Google; Load management; Optimization; Security; Servers; Cloud Computing; Data Centers; Data as a Service; QoS; load balancing; network; partial replication; storage optimization; throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), 2015 IEEE 24th International Conference on
Conference_Location :
Larnaca
Type :
conf
DOI :
10.1109/WETICE.2015.23
Filename :
7194335
Link To Document :
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