Abstract
File downloads make up a large percentage of the Internet traffic to satisfy various clients using distributed environments for their Cloud, Grid and Internet applications. In particular, the Cloud has become a popular data storage provider and users (individuals and corporates) are relying heavily on it to keep their data. Furthermore, most cloud data servers replicate their data storage infrastructures and servers at various sites to meet the overall high demands of their clients and increase availability. However, most of them do not use that replication to enhance the download performance per client. To make use of this redundancy and to enhance the download speed, we introduce a fast and efficient concurrent technique for downloading large files from replicated Cloud data servers and traditional FTP servers as well. The technique, DDFTP utilizes the availability of replicated files on distributed servers to enhance file download times through concurrent downloads of file blocks from opposite directions in the files. DDFTP does not require coordination between the servers and relies on the in-order and reliability features of TCP to provide fast file downloads. In addition, DDFTP offers efficient load balancing among multiple heterogeneous data servers with minimal overhead. As a result, we can maximize network utilization while maintaining efficient load balancing on dynamic environments where resources, current loads and operational properties vary dynamically. We implemented and evaluated DDFTP and experimentally demonstrated considerable performance gains for file downloads compared to other concurrent/parallel file/data download models.
Original language | English |
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Pages (from-to) | 1116-1130 |
Number of pages | 15 |
Journal | Journal of Network and Computer Applications |
Volume | 36 |
Issue number | 4 |
DOIs | |
Publication status | Published - Jul 2013 |
Keywords
- Cloud computing
- Distributed FTP
- Heterogeneous systems
- Load balancing
- Replicated data servers
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications