Graph homomorphism have been utilized as a highly powerful mathematical tool to map the complex topologies of networks to simpler ones and still be able to retain adjacency relations. This article focuses on the use of graph homomorphism, in network coding, to increase the efficiency of data transmission, resilience and scale. The research paper proposes homomorphic mappings that are algebraic transformation that facilitate the best encoding and decoding of network nodes. The proposed methodology is founded on the synergize of graph-theoretic concepts and algebraic representation toward the realization of a better throughput, lower redundancy and higher fault tolerance. Comparative analysis has shown that the throughput has increased by up to 18.6 and the decrease in the traditional routing schemes by up to 22.3 in the number of packets lost. The novelty is to plot the structural graphs in a cohesive way with the strategies of coding to allocate the data effectively. The architecture can be used in distributed systems, wireless networks, and IoT networks and provides a secure and scalable communication service.