Improving link stability under topological changes arise due to link/node failures under uniform speeds and random trajectories of mobile nodes, is a significant problem that must be addressed to improve routing performance in mobile adhoc networks (MANETs). Under random characteristics of wireless channels, there must be a unified model based on proactive strategies to improve link stability under topological changes for stable and robust communications among neighboring nodes. This thesis addresses the problem of link stability under topological changes by presenting proactive strategies for faster failure detection, robustly maintaining link stability, effective link stability estimation, and efficient traffic estimation. First, a novel faster failure detection (FFD) strategy is proposed for link re-connectivity under link/node failures using a Hello messaging scheme. FFD is modeled through a Continuous Time Markov Chain (CTMC) based approach to proactively detect link/node failures under topological changes in MANETs. The FFD strategy minimizes delay incurred as a result of link re-connectivity, optimizes adjacency establishments among neighboring nodes, and enables energy efficiency to improve network connectivity. Second, a novel dynamic link connectivity (DLC) strategy for maintaining link stability among neighboring nodes. DLC is modeled through CTMC by taking into account continuous time analysis of dynamic link connectivity and stationary probability distribution between neighboring node pairs. The DLC strategy examines stability of network nodes and calculates probabilities of connection and disconnection states on the basis of transition rate estimation between these states. The DLC strategy robustly maintains link connectivity for future communications among neighboring nodes inside a cluster. Third, novel link connectivity metrics (LCM) and path distribution analysis (PDA) strategies are presented for effective link stability estimation in MANETs. LCM and PDA are modeled using CTMC under random movement of network nodes and topology trigxxii gered path duration statistics as a function of effective link stability estimation. The LCM and PDA strategies collectively enhance robustness and stability of a network by making it less prone to connectivity failures for future communications among network nodes. Finally, the fourth contribution is a novel efficient traffic estimation (ETE) strategy using Hello messaging among neighboring nodes inside a cluster. ETE is modeled through periodic exchange of transmitted Hello messages under local link connectivity between neighboring node pairs, which follows a CTMC model. The ETE strategy estimates optimum Hello messages traffic through local link connectivity. Simulation and analytical results demonstrate that the proposed strategies improve link stability under topological changes and can be deployed as effective tools for maximizing routing performance in MANETs.