## 2 Related Works  
This section reviews studies focused on mobility, energy, security, and weighted techniques in MANETs. To begin with, MPR nodes broadcast TC messages to establish communication between sources and destinations. Thus, optimizing MPR selection is crucial for improving network performance. Notably, the OLSR protocol and MPR selection can be enhanced by incorporating additional criteria into the MPR mechanism [21; 22]. Mobility, energy, and trust metrics play a significant role in routing protocol performance in dynamic environments. Several studies have analyzed these factors and quantified their impact using multiple metrics. Moreover, the importance of effective data routing in IoT environments and MANET-WSN convergence has been highlighted [23]. Deploying MANET nodes in such scenarios reduces latency and overcomes WSN limitations like low data rates and limited battery capacity. While MANET nodes have energy constraints, they offer higher bandwidth and lower latency, making them advantageous for critical data transmission. In addition, the hybrid multipath energy and QoS-aware OLSR protocol (MEQSA-OLSRv2) [24] addresses challenges such as limited energy, mobility, and congestion in MANET-WSN scenarios by using a multicriteria node rank metric (MCNR). It optimizes link quality and selects MPR sets based on energy and QoS, significantly outperforming existing schemes in high-traffic and mobility situations. However, reachability and stability are further challenged by node mobility. To address this, a topology-based protocol [25] was developed to enhance VANET performance. Simulations confirmed that the choice of protocol depends on network size and desired metrics. Similarly, other studies have improved MPR selection and routing efficiency by addressing issues like redundant HELLO and TC messages and delayed routing updates [26; 27; 28]. Furthermore, several advanced algorithms, such as the continuous Hopfield network (CHN) [29] and 3D position-based modified OLSR [30], have demonstrated improvements in packet delivery ratio (PDR), throughput, and routing overhead. In parallel, clustering techniques like ACRP and EECRPSID have been employed to optimize clustering and eliminate redundant data [31; 32]. For instance, the ANFC-QGSOR protocol [33] combines clustering and optimization to improve performance in VANETs. On the other hand, energy-aware algorithms, such as those proposed in [34; 35], focus on balancing network load and extending network lifetime. Additionally, security enhancements, such as novel MPR selection algorithms to avoid malicious nodes [36], have improved throughput and reduced packet loss. Similarly, studies on V2X security [37] and hybrid secure cluster-based algorithms [38] have demonstrated better performance in simulations. In terms of weighted clustering, several studies have proposed weighted techniques for enhanced performance. For example, weighted clustering techniques [39; 40] and multi-objective OLSR optimization [41] have further improved network performance by reducing packet loss and delay. Additionally, a study combining residual energy and reachability for optimal MPR selection [42] showed improved network lifetime. Finally, a new multicriteria-weighted MPR (MCWMPR) scheme has been integrated into the OLSR protocol to enhance MPR selection based on multiple metrics [43], demonstrating a significant improvement over traditional approaches. The proposed method aims to address the gaps identified in previous studies by introducing an adaptive, multicriteria MPR selection algorithm that integrates mobility, energy,and trust metrics. Unlike existing methods that focus on single criteria, this approach combines these key factors to improve the stability and reliability of MPR selection in highly dynamic environments. Furthermore, by reducing the frequency of MPR re-affiliations and minimizing network overhead, our method tackles the limitations associated with frequent topology changes and energy constraints.