An AWGN Channel Data Transmission Proposal Using Discrete Events for Cloud and Big Data Environments Using Metaheuristic Fundamentals

Cloud computing consists of providing computing services and re-sources, including servers, storage, databases, networking, software, analytics, and intelligence, over the Internet (“the cloud”) to deliver faster innovation, flexible capabilities, and economies of scale. Big Data refers to a large amount of data, coming from controlled or uncontrolled sources, in accordance with structured or unstructured data, its potential comes from this volume where through its analysis it allows extracting insights from analyzes of this information. Metaheuristics have proven to be a powerful tool for roughly solving optimization problems, applied to find answers to problems about which there is little information. This research aims to propose modeling to improve the transmission of content in wireless communication systems, employing the pre-coding process of bits based on the application of a discrete event in signals before the modulation process, using DQPSK modulation in an AWGN channel. The results show improvement achieving 74.61% in memory utilization and 131.29% at runtime with respect to information compression.