Satellite Internet Communication: A Race with Contemporary Optical Fiber Network with the Help of SPT Algorithm

Preet, Shiv

doi:10.1149/10701.0033ecst

Cited by 3 publications

(1 citation statement)

References 27 publications

(15 reference statements)

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“…Lossless compression is the compression technique where the quality of the original message remains intact in the compressed format. There is no deterioration in the quality of the data [22]. The decompression process generates the same number of bits in the data le before the compression [23].…”

Section: Introductionmentioning

confidence: 99%

A Squeeze Pack and Transfer Algorithm-based Efficient Framework for Optimized Network Data Transfer in IoT Applications

Preet

Sharma

Sahni

et al. 2023

Preprint

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The wireless network is the driving force behind the new world's economy, and its invasion has spread far beyond Earth in an interplanetary network using satellites. Wireless networks' productivity must be urgently improved because they are prone to signal attenuation, slower transfer speeds, complete signal unavailability due to weather, and overcrowding of connected users. Due to the towers' remote position, excessive latency is also an issue, as is the enormous magnitude of data transfer that comes with the big data revolution. The antiquated TCP protocol, which is ineffective for low consumption and limited storage IoT items as data buffer is insignificant in such devices, is another problem for IoT applications. A novel SPT (Squeeze Pack and Transfer) algorithm has been proposed to increase mobile network productivity and reduce storage by more than 90% for data files. Binary patterns, rather than conventional textual symbols compress data, resulting in a higher compression ratio and faster compression speed. The suggested algorithm will significantly improve network performance while also facilitating efficient data transfer for Internet of Things devices with limited storage. Many researchers confront issues such as low compression ratios and restricted support for multiple data formats from generic compression. All of these concerns are addressed by the proposed method.

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Section: Introductionmentioning

confidence: 99%