# Evaluating MPTCP Congestion Control Algorithms: Implications for Streaming in Open Internet
### Related Works
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Title** & **Authors** & **Year** & **Key Findings** & **Algorithms** \\ \hline An Analysis of MPTCP Congestion Control [37] & [PERSON]. [PERSON], [PERSON] & 2022 & Highlighted performance limitations of MPTCP coupled congestion control algorithms in disjoint paths. & MPTCP Coupled Congestion Control \\ \hline Technical Comparison between MPTCP and TCP in Heterogeneous Networks [38] & [PERSON]. [PERSON] & 2022 & Demonstrated the superiority of MPTCP over single-path TCP in heterogeneous networks, with LIA and BLIA emphasized. & LIA, BALIA \\ \hline Discrete-Time Sliding-Mode Controllers for MPTCP Networks [39] & [PERSON], [PERSON] & 2021 & Provides a discrete-time model of data exchange in MPTCP networks and introduces new flow control algorithms based on the concept of discrete sliding modes. & Discrete sliding-mode control \\ \hline Performance Evaluation of MPTCP on Simultaneous Use of 5G and 4G Networks [40] & [PERSON], [PERSON], [PERSON] & 2022 & Revealed that the BELAST scheduler with the BELAST scheduling can produce the BELAST scheduling and lowest delay in 5G and 4G networks. & BALIA \\ \hline An Intelligent TCP Congestion Control Method Based on Deep Q Network [41] & [PERSON], [PERSON], [PERSON] & 2021 & Introduced TCP-DQN, an intelligent TCP congestion control method based on DQN, showing a significant throughput boost. & TCP-DQN \\ \hline D-OLIA: A Hybrid MPTCP Congestion Control Algorithm with Network Delay Estimation [42] & [PERSON], [PERSON], [PERSON], [PERSON] & 2021 & Proposed D-OLIA, a hybrid MPTCP-CCA that enhances OLIA’s performance by integrating network delay awareness. & D-OLIA \\ \hline Learning to Harness Bandwidth With Multipath Congestion Control and Scheduling [43] & [PERSON]. [PERSON], [PERSON] & 2021 & Introduced a Deep Q-Learning-based framework for joint congestion control and packet scheduling for MPTCP. & DQL-MPTCP \\ \hline Adaptive Decrease Window for BALIA (ADW-BALIA): Congestion Control Algorithm for Throughput Improvement in Nonshared Bottlenecks [44] & [PERSON], [PERSON], [PERSON], [PERSON] & 2021 & Proposed an adaptive decrease window for BALIA to improve throughput in scenarios with nonshared bottlenecks. & ADW-BALIA \\ \hline A Price to Pay for Increased Throughput in MPTCP Transmission of Videos Streams [45] & [PERSON], [PERSON] & 2020 & Investigated the impact of TCP CC algorithms on video stream characteristics. & Various TCP CC algorithms \\ \hline Influence of Congestion Control Algorithms on Head-of-Line Blocking in MPTCP-based Communication [46] & [PERSON], [PERSON] & 2019 & Examined the influence of TCP CC algorithms on HoL blocking in MPTCP networks. & Various TCP CC algorithms \\ \hline Synchronizing Scheduler for MPTCP Transmission of Streaming Content [47] & [PERSON], [PERSON] & 2022 & Proposed a new scheduler for MPTCP targeting the aspects related to protocol delay. & N/A \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Overview of recent research publications on MPTCP congestion control and related topics. an intelligent method that showcased noticeable improvements in throughput. A similar line follows the design of D-OLIA proposed by [PERSON], [PERSON], [PERSON], and [PERSON] in [42]. As a hybrid MPTCP CC algorithm, D-OLIA elevates the OLIA's performance by weaving in the network delay awareness, thus offering a service-tailored approach to CC design. Further steps in this direction were made by [PERSON] and [PERSON] while introducing a Deep Q-Learning-based framework for joint CC and packet scheduling in MPTCP, named DQL-MPTCP [43]. Their work underscores the potential of advanced machine learning techniques in optimizing MPTCP's performance. Yet, another scenario-specific solution was explored by [PERSON], [PERSON], [PERSON], and [PERSON] in [44]. By incorporating an adaptive decrease window mechanism into MPTCP CC, termed ADW-BALIA, a throughput improvement in nonshared bottleneck networks was obtained.