T. Pullaiah

Work place: ECE Department, Jawaharlal Nehru Technological University, Hyderabad-500085, India

E-mail: thanam.tp@gmail.com

Website:

Research Interests:

Biography

T. Pullaiah, Associate Professor of ECE, Department of ECE, Vignan Institute of management and Tech. for women, Hyderabad, TS. B.E (ECE) from SRKR Engineering College Bhimavaram, Andhra University, Andhra Pradesh, completed in 1997. M.Tech (DSCE) from JNTU Anantapur, JNTUA, completed in 2007. Presently Pursuing Ph.D from JNTUH Hyderabad on “Data compression Techniques” Experience: 20 years.

Author Articles
∆DHT-Zip: A Delta-difference Hybrid Tree Coding Scheme for End-to-end Packet Compression Framework in Network-on-Chips

By T. Pullaiah K. Manjunathachari B. L. Malleswari

DOI: https://doi.org/10.5815/ijcnis.2025.02.02, Pub. Date: 8 Apr. 2025

Due to the maximal transistor count, Multi-Processor System-on-Chip (MPSoC) delivers more performance than uniprocessor systems. Network on Chip (NoC) in MPSoC provides scalable connectivity compared to traditional bus-based interconnects. Still, NoC designs significantly impact MPSoC design as it increases power consumption and network latency. A solution to this problem is packet compression which minimizes the data redundancy within NoC packets and reduces the overall power consumption of the whole network by minimizing a data packet size. Latency and overhead of compressor and decompressor require more memory access time, even though the packet compression is good for the improved performance of NoC. So, this problem demands a simple and lightweight compression method like delta compression. Consequently, this research proposes a new delta-difference Hybrid Tree coding (∆DHT-Zip) to de/compress the data packet in the NoC framework. In this compression approach, the Delta encoding, Huffman encoding and DNA tree (deoxyribonucleic acid) coding are hybridized to perform the data packet de/compression approach. Moreover, a time series approach named Run Length Encoding (RLE) is used to compress the metadata obtained from both the encoding and decoding processes. This research produces decreased packet loss and significant power savings by using the proposed ∆DHT-Zip method. The simulation results show that the proposed ∆DHT-Zip algorithm minimizes packet latency and outperforms existing data compression approaches with a mean Compression Ratio (CR) of 1.2%, which is 79.06% greater than the existing Flitzip algorithm. 

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