## 2 Related Works  
Several previous research works address the management of wireless MPTCP connections using an SDN framework. The works propose the usage of SDN to manage MPTCP mainly focusing on routing, controlling the path, and path resilience. For instance, the WRR MPTCP scheduler is used for multipath routing in [20]. A dynamic path control in MPTCP using SDN is proposed by the authors of [21]. In [22], the authors offer a resolution to the bandwidth utilization problem in wireless network sets (WNS) by observing and dynamically controlling the network access by implementing an SDN-based flow management system. The authors of [23] investigate the use of an SDN to manage heterogeneous home networks. They analyze OpenFlow-enabled link switching under normal conditions and link failure situations. [PERSON] et al., in [24], suggest employing SDN to create MPTCP subflows to reduce the difference in mean delay between them. Other authors consider managing MPTCP connections via SDN in other system models with a similar focus. For instance, the authors of [25; 26; 27] utilize the SDN-MPTCP framework in naval battlefields, LEO satellites, and V2I communication, respectively. Several research works address the reduction of MPTCP energy consumption by devising a new scheduling scheme. An energy-aware MPTCP (eMPTCP) model is proposed by [28] and tested on an Android platform to increase energy efficiency, but the bandwidth changes in different scenarios adversely affect the performance gain in eMPTCP. In [29], the authors propose an MPTCP scheduler to save energy by switching to the most efficient network path. They use an MDP with energy models and application tracing to generate schedules. [PERSON] et al., in [30], create an MPTCP scheduling algorithm for downlink traffic that minimizes energy consumption by distributing loads across multiple interfaces and adjusting channel usage with flow control. Moreover, the authors in [31] address an MPTCP-based content distribution scheme (eMTCP) that is energy-aware by shifting the traffic to the interface with low energy consumption. [PERSON] et al. [11] propose an energy-saving scheduling system named ES-MPTCP that prioritizes subflows to reduce energy consumption while ensuring network throughput. In [12], the authors propose an energy-efficient multipath scheduler for IoT monitoring systems, which considers both network throughput and energy consumption. In [32], the authors address scheduling in MPTCP using a stochastic optimization approach to maximize the average throughput, reduce congestion, and achieve energy efficiency. They compare the proposed solution using a simulation with the base version of MPTCP and eMPTCP without targeting specific congestion control algorithms. [PERSON] et al. [33; 34] propose energy-efficient MPTCP schemes specifically for quality-guaranteed video transmission over heterogeneous wireless networks. They design MPTCP schedulers that consider both the energy consumption of mobile devices and the quality of video transmission by leveraging wireless channel diversity and video frame priority. A few researchers discuss minimizing MPTCP energy consumption by proposing congestion control schemes different from the Linux kernel implementation ones. For example, the authors of [14] suggest a receiver energy-efficient congestion control method based on MPTCP to allow mobile devices powered by batteries to receive more data than MPTCP while using the same amount of energy. In [13], [PERSON] et al. propose an energy-aware congestion control mechanism for MPTCP. The proposed algorithm aims to reduce energy consumption while maintaining network performance by shifting traffic to low-delay, lower-energy-consumption paths. Their algorithm's performance is compared with that of LIA. Other authors target MPTCP energy consumption analysis and modeling. For instance, the authors of [35] analyze the energy consumption of MPTCP versus standard TCP on mobile devices.