## 5 Energy Optimization Approach Based on MAC/Routing Cross-Layer (EOAMRCL)
### Clusters Formation Phase (Network Layer)
In contrast, GWO enables it to dynamically adjust and optimize clustering and routing strategies, leading to more efficient energy management and enhanced node longevity. ### Strengths and Weaknesses of EOAMRCL

The strengths of EOAMRCL lie in its innovative integration of GWO and a cross-layer design, which collectively enhance the protocol's energy efficiency and overall network performance. By leveraging GWO, EOAMRCL effectively balances exploration and exploitation phases, ensuring optimal cluster head selection. This results in a more efficient use of energy resources, as the most suitable nodes are chosen to manage communication within the network. Additionally, the cross-layer design of EOAMRCL improves energy efficiency by coordinating operations between the MAC and network layers. This coordination allows for a dynamic duty-cycle schedule, reducing unnecessary energy consumption by managing node activity more effectively. The protocol's superior performance is demonstrated in its ability to extend network lifetime, maintain higher levels of residual energy, and achieve greater data throughput compared to other existing protocols. However, the increased implementation complexity is a notable weakness of EOAMRCL. Integrating GWO and cross-layer interactions requires more sophisticated management and coordination, which can be challenging to implement and maintain. The computational overhead associated with optimizing CH selection and routing paths is also higher, potentially limiting the protocol's applicability in resource-constrained environments. Additionally, while EOAMRCL shows excellent performance in static network scenarios, it may face challenges in highly dynamic environments where network topology and node energy levels change frequently. Adapting the protocol to such conditions could require further refinement and additional mechanisms to ensure scalability and adaptability. ## 7 Conclusions

This paper introduces a novel multi-layer protocol for energy-efficient management in WSNs, emphasizing the interaction between the MAC and network layers to minimize unnecessary energy consumption. We developed a robust objective function to identify the optimal cluster group and the best CHs during the formation phase while our routing pro tocol selects the most energy-efficient route for data delivery based on transmission power. Our new data transmission strategy for both intra-cluster and inter-cluster communication effectively addresses excessive energy consumption in the routing process. Each node schedules active and sleep modes using allotted NAV time slots, allowing the MAC layer to generate a duty-cycle schedule through cross-layer routing information. Additionally, the integration of a modified CSMA/CA mechanism with sleep/activate mode enhances the protocol's energy efficiency by managing node activity more effectively. Simulation results demonstrate that EOAMRCL outperforms EEUC, CGA-GWO, and DWEHC protocols in terms of overall network remaining energy, number of dead nodes, total data received at the BS, and network lifetime. The superior performance is due to the efficient multi-layer approach, which overcomes the limitations of single-layer protocols. The innovative EOAMRCL protocol significantly enhances the energy efficiency and longevity of WSNs by leveraging cross-layer interactions. By integrating the MAC and network layers, our protocol ensures more precise and effective energy management, leading to a notable reduction in energy wastage. This multi-layer synergy is crucial for maintaining the balance between energy consumption and network performance, particularly in complex WSN environments. The use of NAV time slots for scheduling active and sleep modes further optimizes energy usage, enabling nodes to conserve energy without compromising data transmission reliability. Our extensive simulation results highlight EOAMRCL's ability to maintain higher residual energy levels, fewer dead nodes, and greater data throughput at the base station compared with the other protocols.