You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Holistic Survey of Wireless Multipath Video Streaming 
Chapter Title:  V. SCHEDULING, RESILIENCE, AND PATH SELECTION 
1. Abstract of Cited Paper (BIB001):  Devices capable of connecting to multiple, overlapping networks simultaneously are becoming increasingly common. For example, most laptops are equipped with LAN- and WLAN-interfaces, and smart phones can typically connect to both WLANs and 3G mobile networks. At the same time, streaming high-quality video is becoming increasingly popular. However, due to bandwidth limitations or the unreliable and unpredictable nature of some types of networks, streaming video can be subject to frequent periods of rebuffering and characterised by a low picture quality. In this paper, we present a client-side request scheduler that distributes requests for the video over multiple heterogeneous interfaces simultaneously. Each video is divided into independent segments with constant duration, enabling segments to be requested over separate links, utilizing all the available bandwidth. To increase performance even further, the segments are divided into smaller subsegments, and the sizes are dynamically calculated on the fly, based on the throughput of the different links. This is an improvement over our earlier subsegment approach, which divided segments into fixed size subsegments. Both subsegment approaches were evaluated with on-demand streaming and quasi-live streaming. The new subsegment approach reduces the number of playback interruptions and improves video quality significantly for all cases where the earlier approach struggled. Otherwise, they show similar performance. 
2. Abstract of Cited Paper (BIB002):  Video streaming is gaining popularity among mobile users. The latest mobile devices, such as smart phones and tablets are equipped with multiple wireless network interfaces. How to efficiently and cost-effectively utilize multiple links to improve the video streaming quality needs to be investigated. In order to maintain high video streaming quality while reduce the wireless service cost, in this paper, the optimal video streaming process with multiple links is formulated as a Markov Decision Process (MDP). The reward function is designed to consider the quality of experience (QoE) requirements for video traffic, such as the interruption rate, average playback quality, playback smoothness and wireless service cost. Using dynamic programming, the MDP can be solved to obtain the optimal streaming policy. To evaluate the performance of the proposed multi-link rate adaptation (MLRA) algorithm, we implement a testbed using the Android mobile phone and the open-source X264 video codec. Experimental results demonstrate the feasibility and effectiveness of the proposed MLRA algorithm for mobile video streaming applications, which outperforms the existing state-of-the-art one. 
3. Abstract of Cited Paper (BIB003):  Devices capable of connecting to multiple, overlapping networks simultaneously is becoming increasingly common. For example, most laptops are equipped with LAN- and WLAN-interface, and smart phones can typically connect to both WLANs and 3G mobile networks. At the same time, streaming high-quality video is becoming increasingly popular. However, due to bandwidth limitations or the unreliable and unpredictable nature of some types of networks, streaming video can be subject to frequent periods of rebuffering and characterized by a low picture quality. In this paper, we present a multilink extension to the data retrieval part of the DAVVI adaptive, segmented video streaming system. DAVVI implements the same core functionality as the MPEG DASH standard. It uses HTTP to retrieve data, segments video, provides clients with a description of the content, and allows clients to switch quality during playback. Any DAVVI-data retrieval extensions can also be implemented in a DASH-solution. The multilink-enabled DAVVI client divides video segments into smaller subsegments, which are requested over multiple interfaces simultaneously. The size of each subsegment is dynamic and calculated on the fly, based on the throughput of the different links. This is an improvement over our earlier subsegment approach, which divided segments into fixed size subsegments. The quality of the video is adapted based on the measured, aggregated throughput. Both the static and the dynamic subsegment approaches were evaluated with on-demand streaming and quasi-live streaming. The new subsegment approach reduces the number of playback interruptions and improves video quality significantly for all cases where the earlier approach struggled. Otherwise, they show similar performance. 
4. Abstract of Cited Paper (BIB004):  Modern mobile devices are equipped with multiple network interfaces, including 3G/LTE and WiFi. Bandwidth aggregation over LTE and WiFi links offers an attractive opportunity of supporting bandwidth-intensive services, such as high-quality video streaming, on mobile devices. However, achieving effective bandwidth aggregation in mobile environments raises several challenges related to deployment, link heterogeneity, network fluctuation, and energy consumption. We present GreenBag, an energy-efficient bandwidth aggregation middleware that supports real-time data-streaming services over asymmetric wireless links, requiring no modifications to the existing Internet infrastructure and servers. GreenBag employs several techniques, including medium load balancing, efficient segment management, and energy-aware mode control, to resolve such challenges. We implement a prototype of GreenBag on Android-based mobile devices which hosts, to the best knowledge of the authors, the first LTE-enabled bandwidth aggregation prototype for energy-efficient real-time video streaming. Our experiment results in both emulated and real-world environments show that GreenBag not only achieves good bandwidth aggregation to provide QoS in bandwidth-scarce environments but also efficiently saves energy on mobile devices. Moreover, energy-aware GreenBag can minimize video interruption while consuming 14-25% less energy than the non-energy-aware counterpart in real-world experiments. 
5. Abstract of Cited Paper (BIB005):  Video streaming is gaining popularity among mobile users. The latest mobile devices, such as smart phones and tablets, are equipped with multiple wireless network interfaces. How to efficiently and cost-effectively utilize multiple links to improve video streaming quality needs investigation. In order to maintain high video streaming quality while reducing the wireless service cost, in this paper, the optimal video streaming process with multiple links is formulated as a Markov Decision Process (MDP). The reward function is designed to consider the quality of service (QoS) requirements for video traffic, such as the startup latency, playback fluency, average playback quality, playback smoothness and wireless service cost. To solve the MDP in real time, we propose an adaptive, best-action search algorithm to obtain a sub-optimal solution. To evaluate the performance of the proposed adaptation algorithm, we implemented a testbed using the Android mobile phone and the Scalable Video Coding (SVC) codec. Experiment results demonstrate the feasibility and effectiveness of the proposed adaptation algorithm for mobile video streaming applications, which outperforms the existing state-of-the-art adaptation algorithms. 
6. Abstract of Cited Paper (BIB006):  Smart devices equipped with multiple network interfaces are becoming commonplace. Nevertheless, even though multiple interfaces can be used to connect to the Internet, their capabilities have not been fully utilized yet because the default TCP/IP stack supports only a single interface for communication. This situation is now changing due to the emergence of multipath protocols on different network stack layers. For example, many IP level approaches have been proposed utilizing tunneling mechanisms for hiding multipath transmission from the transport protocols. Several working groups under IEEE and IETF are actively standardizing multipath transmission on the link layer and transport layer. Application level approaches enable multipath transmission capability by establishing multiple transport connections and distributing data over them. Given all these efforts, it is beneficial and timely to summarize the state-of-the-art, compare their pros and cons, and discuss about the future directions. To that end, we present a survey on multipath transmission and make several major contributions: 1) we present a complete taxonomy pertaining to multipath transmission, including link, network, transport, application, and cross layers; 2) we survey the state-of-the-art for each layer, investigate the problems that each layer aims to address, and make comprehensive assessment of the solutions; and 3) based on the comparison, we identify open issues and pinpoint future directions for multipath transmission research. 
7. Abstract of Cited Paper (BIB007):  Transport protocols that can exploit multiple paths, especially MPTCP, do not match the requirements of video streaming: high average transmission delay, too strict reliability, and frequent head-of-line phenomenons resulting in abrupt throughput drops. In this paper, we address this mismatch by introducing a cross-layer scheduler, which leverages information from both application and transport layers to re-order the transmission of data and prioritize the most significant parts of the video. Our objective is to maximize the amount of video data that is received in time at the client. We show that current technologies enable the implementation of this cross-layer scheduler without much overhead. We then demonstrate the validity of our approach by studying the performance of an optimal cross-layer scheduler. The gap between the performance of the traditional scheduler versus the optimal scheduler justifies our motivation to implement a cross-layer scheduler in practice. We propose one implementation with basic cross-layer awareness. To evaluate the performance of our proposal, we aggregate a dataset of real MPTCP sessions and we use video stream encoded with HEVC. Our results show that our cross-layer proposal outperforms the traditional scheduler. Viewers not only benefit from the inherent advantages of using MPTCP (such as a better resilience to path failure) but also get a better QoE compared to the traditional scheduler. 
8. Abstract of Cited Paper (BIB008):  End-users in online video services are sensitive to the overall quality of the video at screen, but also, and more importantly, to other factors, including the latency between the video generation and the playback for live videos. If the improvement of the quality of the perceived video has been well investigated by the multimedia community, the impact of delay, latency, and re-buffering has not received a significant attention. Adaptive streaming technologies, which have been widely adopted in the recent years, contribute to this lack of consideration since vendors usually recommend the introduction of significant extra-latency. In this paper, we address the problem of low-latency live video streaming. We propose an implementation of multi-path video delivery at the applicative level, which exploits the information provided in the latest version of the video delivery standards. We present an implementation of a video player, which takes advantage of multi-path networking to enable video playback using TCP with a latency below 100 ms. By initiating the multi-path delivery from the client side, our mechanism is compatible with current network equipments and does not require any change neither at the server nor in the middleboxes.

Literature Review:
A key characteristic of video data is that, based on the en/decoding technology, packets may have unequal importance (e.g. I-frames vs P-frames). Considering the importance of each packet, different error protection levels can be applied. In addition, packets can be sent over different network paths based on paths quality to meet real-time deadlines, increase reliability, minimize out-of-order packet delivery, circumventing path heterogeneity issues BIB007 , as discussed in Section 4. Therefore, wirelesss multi-path video scheduling strategies need to consider, at least, three main functional aspects; packet selection, packet protection and path selection. We now revisit the works surveyed in Section IV through the new classification presented in Tables V, VI , VII, and VIII based on the following questions: • Which packet should be sent next? • How to protect the packet? • Which is the best path to send the packet? A. Which packet should be sent next? One important scheduling task is selecting the next packet to be sent. Content awareness and video distortion at frame level are key features to select the proper packets. These BIB008 Y features will be discussed in this subsection. Tables V, VI, VII, and VIII present each category related to the protocol layer. Note that, generally, ABR approaches rely on HTTP and separate TCP connections do not consider each one packet for data transmission and proper path for a DASH segment/subsegment need to be determined instead of packet (e.g., BIB003 , BIB006 , BIB009 , BIB001 , BIB002 , BIB004 , BIB005 ). However, when using MPTCP for HTTP-based ABR video, the MPTCP scheduler performs its own transport-level scheduling for the received DASH data stream.