Multipath Transmission Control Protocol (MPTCP) has emerged as a promising solution to leverage the capabilities of modern heterogeneous networks by enabling simultaneous data transmission across multiple paths. However, efficiently managing congestion control in MPTCP remains a critical challenge due to the need for fairness, stability, and optimal resource utilization. This paper provides a comprehensive analysis of state-of-the-art MPTCP congestion control algorithms with modified BALIA, focusing on their design principles, performance trade-offs, and applicability in diverse network environments. Specifically, we examine Linked Increases Algorithm (LIA), which balances throughput optimization and fairness with single-path TCP, Opportunistic Linked Increases Algorithm (OLIA), which enhances stability and responsiveness, and Balanced Linked Adaptation Algorithm (BALIA), which aims to achieve a better trade-off between throughput, fairness, and convergence. Through extensive simulations and real-world experiments, we evaluate the performance of these algorithms in terms of throughput, end-to-end delay, loss ratio, and resilience to network dynamics. This finding will help in designing a smart communication system.