Improving Accessing Efficiency of Cloud Storage Using De-Duplication and Feedback Schemes

File distribution and storage in a cloud storage environment is usually handled by storage device providers or physical storage devices rented from third parties. Files can be integrated into useful resources that users are then able to access via centralized management and virtualization. Nevertheless, when the number of files continues to increase, the condition of every storage node cannot be guaranteed by the manager. High volumes of files will result in wasted hardware resources, increased control complexity of the data center, and a less efficient cloud storage system. Therefore, in order to reduce workloads due to duplicate files, we propose the index name servers (INS) to manage not only file storage, data de-duplication, optimized node selection, and server load balancing, but also file compression, chunk matching, real-time feedback control, IP information, and busy level index monitoring. To manage and optimize the storage nodes based on the client-side transmission status by our proposed INS, all nodes must elicit optimal performance and offer suitable resources to clients. In this way, not only can the performance of the storage system be improved, but the files can also be reasonably distributed, decreasing the workload of the storage nodes.

[1]  Dezhi Han,et al.  Research on Self-Adaptive Distributed Storage System , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[2]  Victor C. M. Leung,et al.  On multipath balancing and expanding for wireless multimedia sensor networks , 2012, Int. J. Ad Hoc Ubiquitous Comput..

[3]  Xin Sun,et al.  An Efficient Replica Location Method in Hierarchical P2P Networks , 2009, 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science.

[4]  Xiongfeng Zhu,et al.  A Load Balancing Strategy Based on the Combination of Static and Dynamic , 2010, 2010 2nd International Workshop on Database Technology and Applications.

[5]  Junping Wang,et al.  Research on load balance of Service Capability Interaction Management , 2010, 2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology (IC-BNMT).

[6]  Hongyuan Wang,et al.  A Cloud Storage Architecture Model for Data-Intensive Applications , 2011, 2011 International Conference on Computer and Management (CAMAN).

[7]  J. B. Connell,et al.  A Huffman-Shannon-Fano code , 1973 .

[8]  Wei-Tsong Lee,et al.  Dynamic load balancing mechanism based on cloud storage , 2012, 2012 Computing, Communications and Applications Conference.

[9]  Tin Yu Wu,et al.  Cloud-based image processing system with priority-based data distribution mechanism , 2012, Comput. Commun..

[10]  Nick McKeown,et al.  Optimal load-balancing , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[11]  Tin Yu Wu,et al.  Cloud storage performance enhancement by real-time feedback control and de-duplication , 2012, Wireless Telecommunications Symposium 2012.

[12]  Matei Ripeanu,et al.  Towards automating the configuration of a distributed storage system , 2010, 2010 11th IEEE/ACM International Conference on Grid Computing.

[13]  Liang Zhou,et al.  Multimedia traffic security architecture for the internet of things , 2011, IEEE Network.

[14]  Changsheng Xie,et al.  Avoiding performance fluctuation in cloud storage , 2010, 2010 International Conference on High Performance Computing.

[15]  Hongyan Shi,et al.  Dynamic Load Balancing Algorithm Based on FCFS , 2009, 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC).

[16]  Chin-Feng Lai,et al.  A personalized mobile IPTV system with seamless video reconstruction algorithm in cloud networks , 2011, Int. J. Commun. Syst..

[17]  Bing Bai,et al.  Redball: Throttling Shrew Attack in Cloud Data Center Networks , 2012 .

[18]  He Huang,et al.  P&P: A Combined Push-Pull Model for Resource Monitoring in Cloud Computing Environment , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[19]  Han-Chieh Chao,et al.  Transaction-Pattern-Based Anomaly Detection Algorithm for IP Multimedia Subsystem , 2011, IEEE Transactions on Information Forensics and Security.

[20]  M. Imase,et al.  On dynamic resource management mechanism using control theoretic approach for wide-area grid computing , 2005, Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005..

[21]  Parris K. Egbert,et al.  Learning-Based Fusion for Data Deduplication , 2008, 2008 Seventh International Conference on Machine Learning and Applications.

[22]  Guillaume Pierre,et al.  A survey of DHT security techniques , 2011, CSUR.

[23]  Yang Ji,et al.  A novel load balancing scheme for DHT-based server farm , 2010, 2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology (IC-BNMT).