International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 46 - Number 6 |
Year of Publication: 2012 |
Authors: Ankit Arora, Sachin Bagga, Rajbir Singh Cheema |
10.5120/6913-9311 |
Ankit Arora, Sachin Bagga, Rajbir Singh Cheema . Distributed Cluster Processing to Evaluate Interlaced Run-Length Compression Schemes. International Journal of Computer Applications. 46, 6 ( May 2012), 26-33. DOI=10.5120/6913-9311
Parallel computation, a greater advancement in computational hardware as well as new achievement in current scientific computing such as image processing involves huge exhaustive computation and data processing leading towards parallel architectures. Parallel hardware organization basically a suitable interconnection among computational hardware, where current trends now involves clustered organization of distributed hardware to achieve parallel effects. Cluster environment consisting multi-computer network nodes provides flexible architecture towards high complex data parallelism as well as control parallelism operations. Further detail consists interlaced graphics mechanism with run-length encoding to achieve high compression benefits. Run-length compression speedup benefits have already described in the research IJCA-2011 cluster based performance evaluation of run-length image compression, which is now updated to cover interlaced lossy compression schemes. In general interlacing provides a lossy compression formulation but acceptable in real-life scenarios. Finally, the interlaced methodology and cluster based analysis results will be discussed.