## 2 Incorporating OSI Layers in WSN Clustering
They evaluated these algorithms based on metrics like average power consumption, network lifespan, dead node rate, and coverage time. AR-SC adjusts sensor range for optimal coverage, OCCH uses heuristics for enhanced connected coverage, GCWGC balances coverage and communication weights through a greedy approach, and OTTC overlaps target areas while maintaining connectivity. The study found that achieving uniform performance across all metrics is challenging, and the choice of algorithm should be tailored to the specific application needs. Key factors such as maximum longevity and convergence speed must be considered. The research provides valuable insights for IWSN designers to select practical hedging approaches that meet performance metrics in various industrial applications. [PERSON] et al. highlighted that while no single algorithm excels in all aspects, each has distinct advantages that can be leveraged depending on the application, ensuring optimal performance, reliability, and energy efficiency in diverse industrial environments. A novel Cross-Layer MAC (CL-MAC) protocol [28] has been developed for WSNs by [PERSON] et al. to manage multi-stream, multi-packet, and multi-hop traffic patterns effectively. CL-MAC utilizes a stream configuration packet structure that leverages routing data for efficient multi-hop data transport. By evaluating neighboring flow configuration requests and buffer packets, CL-MAC makes informed scheduling decisions based on the network's current state. This adaptability ensures efficient data transmission even under high traffic loads. Simulations using ns2 demonstrated that CL-MAC enhances delivery rates, reduces end-to-end delays, and lowers average power consumption per transmitted packet. These improvements highlight CL-MAC's potential for superior energy efficiency and data delivery reliability. The cross-layer design allows for coordinated optimization between protocol layers, addressing critical WSN challenges like diverse traffic patterns and energy efficiency. CL-MAC's capability to handle multiple streams and packets concurrently, along with its adaptability, makes it a robust solution for various WSN applications. Additionally, the reduction in end-to-end delay ensures timely data delivery, which is crucial for real-time monitoring and rapid response, while lower power consumption extends the network lifespan. [PERSON] et al. [29] proposed an innovative MAC protocol to enhance energy efficiency in WSNs using a leader-follower communication technique. This protocol eliminates intra-area collisions and minimizes inter-area collisions through two distinct MAC protocol stacks. A sleep schedule with a duty cycle mechanism alternates nodes between active and sleep states, conserving idle power and extending network lifespan. The leader node handles most communication tasks, while follower nodes remain in low-power sleep states until needed, reducing energy consumption and organizing network communication more efficiently. The dual MAC stacks manage intra-area and inter-area communications, ensuring collision-free data transmissions and reducing collisions between different network areas. Simulation results showed significant improvements in energy efficiency, reduced collision rates, and lower power consumption compared with commonly used MAC protocols in WSNs. These enhancements lead to a longer network lifespan and more reliable data transmission. The protocol adapts to real-time network conditions, making it suitable for various WSN applications. The leader-follower technique reduces overall energy expenditure and improves network efficiency. [PERSON] et al. [30] proposed CREC (Cross-layer, Reliable, and Efficient Communication protocol), which integrates multiple functions within a unified framework to enhance WSN communication. CREC features dispersed congestion management, robust geographic routing, and medium access contention networking, optimizing energy efficiency and ensuring reliable data transmission.