## 1 Introduction
### Research Gaps, Our Methodology, and Contributions
In light of this, the major contributions of this paper are delineated as follows:  
* The introduction of a pioneering adaptive and dynamic DFG division methodology based on a hexagonal structure. The division process dynamically adjusts in response to the presence and distribution of SNs within the network vicinity. This approach ensures optimal coverage, balanced node participation, and efficient scalability, aligning the DFGs framework with the growth and distribution patterns of IoT SNs. * The proposal of a high-efficiency DFG mechanism that continuously adapts to varying network densities. The groups dynamically evolve in response to real-time network conditions, optimizing resource utilization and balancing workloads. This adaptive framework enhances the responsiveness of the network while maintaining low latency and robust operational efficiency. * For DFGs, there is an implementation of an innovative method for selecting the optimal PDFH, First Secondary DFH (FSDFH), and Second SDFH (SSDFH) for each DFG utilizing the MPA. This approach incorporates highly effective and complex criteria for DFFF, such as the SNs' distance from the sink node, their RE, and the average distance between DFGMs, ASBO, and PDFH rotation times, effectively preserving SNs' energy and prolonging the network's lifespan. * The implementation of a novel parameter, namely ASBO, where, to the best of our knowledge, we are the first researchers who have introduced and implemented this factor in-depth in the DFFF and RDCF. The exact definition of ASBO is demonstrated in Section 5.2.2. * For relaying, the proposed protocol utilizes innovative RDCF to select a Primary Data Fusion Relay (PDFR), First Secondary DFR (FSDFR), and Second SDFR (SSDFR) based on the candidate PDFR's RE, its distance from the sink node, PDFH, and ASBO in order to select optimal PDFRs, particularly those situated at significant distances from the sink node, thereby conserving PDFHs' energy with demonstrated efficiency. * The optimization and management of resource utilization and data redundancy reduction by applying data fusion techniques for device/link failures and recovery, data redundancy, and building occlusion. In particular, we analyze the issue of data redundancy among relatively close SNs, and in light of this, we provide an efficient data fusion management approach that guarantees a coherent and efficient protocol. Specialist recovery techniques are also employed to address device and link failures, consolidating the protocol and enhancing its overall performance. We also examine the effects of building occlusions at various elevations and appropriate mitigation strategies. * The illustration of the PDFH, FSDFH, and SSDFH selection processes employing MPA within the proposed protocol through a detailed and comprehensible example, enhancing readers' understanding and proficiency in this aspect. * The comprehensive performance evaluation of the proposed protocol through an extensive series of simulations, considering key network performance evaluation metrics including network lifespan, energy consumption, throughput, and average delay. Comprehensive comparisons with existing protocols demonstrate the effectiveness of the proposed protocol without and with multi-hop routing. This paper is organized as follows: Section 2 offers a thorough discussion of previous related works, focusing on the design of energy-efficient routing protocols, especially for the election of PDFH, as well as optimization methods. In Section 3, we provide a comprehensive overview of the MPA and its applications. The system model is demonstrated in Section 4, while Section 5 is dedicated to the proposed protocol, presenting a detailed demonstration of it. Section 6 meticulously displays and analyzes the simulation results. Finally, Section 7 concludes the paper and offers key recommendations.