A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Mobile video streaming has become one of the most popular applications in the trend of smartphone booming and the prevalence of 3G/4G networks, i.e., HSPA, HSPA+, and LTE. However, the prohibitively high power consumption by 3G/4G radios in smartphones reduces battery life significantly and thus severely hurts user experience. To tackle this challenge, we designed GreenTube, a system that optimizes power consumption for mobile video streaming by judiciously scheduling downloading activities to minimize unnecessary active periods of 3G/4G radio. GreenTube achieves this by dynamically managing the downloading cache based on user viewing history and network condition. We implemented GreenTube on Android-based smartphones. Experimental results show that GreenTube achieves large power reductions of more than 70% (on the 3G/4G radio) and 40% (for the whole system). We believe GreenTube is a desirable upgrade to the Android system, especially in the light of increasing LTE popularity. <s> BIB001 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> 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. <s> BIB002 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Mobile devices interact wirelessly with a growing proliferation of cloud-based applications. Due to significant traffic growth and a wide variety of multimedia solutions, enterprise IT departments are demanding more fine-grained visibility and control of mobile traffic. They want to deliver optimal performance and a high quality of experience to a variety of users and applications. In the wired world, Software-Defined Networking (SDN) is a technology being embraced to deliver performance guarantees to end users by dynamically orchestrating quality of service (QoS) policies on edge switches and routers. Guaranteeing performance in a wired access network does not require any network control on clients, because the last hop between the network edge and wired device is a dedicated point-to-point link (e.g. Ethernet). However, this is not the case with wireless LANs (WLAN), since the last hop is a shared half-duplex medium and the WiFi MAC protocol does not allow access points to coordinate client uplink transmissions or 802.11 QoS settings. Hence, we argue that the SDN paradigm needs to be extended to mobile clients to provide optimal network performance between the cloud and wirelessly-connected clients. In this paper, we propose a framework called meSDN and demonstrate that it enables WLAN virtualization, application-aware QoS and improves power-efficiency from our prototype on Android phones. <s> BIB003 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> 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. <s> BIB004 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Software Defined Networking (SDN) drastically changes the meaning and process of designing, building, testing, and operating networks. The current support for wireless networking in SDN technologies has lagged behind its development and deployment for wired networks. The purpose of this work is to bring principled support for wireless access networks so that they can receive the same level of programmability as wireline interfaces. Specifically we aim to integrate wireless protocols into the general SDN framework by proposing a new set of abstractions in wireless devices and the interfaces to manipulate them. We validate our approach by implementing our design as an extension of an existing OpenFlow data plane and deploying it in an IEEE 802.11 access point. We demonstrate the viability of software-defined wireless access networks by developing and testing a wireless handoff application. The results of the experiment show that our framework is capable of providing new capabilities in an efficient manner. <s> BIB005 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Driven by the unprecedented growth in the number of connected devices and mobile data traffic, 5G wireless network is expected to afford a full scale Internet of Things. Various wireless access networks will continue to coexist; one concept is allowing a device to virtually and simultaneously be connected to other devices using all available network resources at its location which is multi-homing. In this paper, we draw an overall picture of multi-homing based solution for provisioning Quality of Service and Quality of Experience taking into consideration the economics issues and the challenging problems that must be solved in the future. <s> BIB006 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Multipath TCP enables remarkable optimizations for throughput, load balancing, and mobility in today's networks. The design space of Multipath TCP scheduling, i.e., the application-aware mapping of packets to paths, is largely unexplored due to its inherent complexity. Evidence in this paper suggests that an application-aware scheduling decision, if leveraged right, pushes Multipath TCP beyond throughput optimization and thereby provides benefits for a wide range of applications. This paper introduces a high-level programming model that enables application-defined Multipath TCP scheduling. We provide an efficient interpreter and eBPF-based runtime environment for the Linux Kernel, enabling isolated application-defined schedulers in multi-tenancy environments. In combination with a high-level API, our work closes the gap between scheduler specification and deployment. We show the strength of our programming model by implementing seven novel schedulers tackling diverse objectives. Our real world measurements, for example, of an application- and preference-aware scheduler, show that the programming model enables timely scheduling decisions to retain fine-grained throughput objectives. Further measurements of a novel HTTP/2-aware scheduler show significantly improved interactions with upper-layer protocols, e.g., an optimized dependency resolution, while preserving path preferences. <s> BIB007 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> In the recent years it has become increasingly evident that the current end-to-end host-centric communication paradigm will not be capable of meeting the ongoing demand for massive data rates and ultra-low latency. With the advent of fifth generation of cellular architecture (5G) to support these requirements on the wireless edge of the network, the need for core network solutions to play a complementary role is conspicuous. In this paper we present and tackle some of the challenges of deploying a Future Internet Architecture (FIA), called MobilityFirst (MF), specifically for 5G use case scenarios. We report our findings of the deployment based on a setup on a small- scale testbed (ORBIT) and a nation-wide distributed testbed (GENI), and illustrate some results for the use case of device multihoming, in comparison with current TCP/IP based solution, i.e. Multipath TCP. <s> BIB008 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> We propose D2-ITS, a flexible and extensible framework to dynamically distribute network control to enable message dissemination in Intelligent Transport Systems (ITS). By decoupling the control- from the data plane, D2-ITS leverages network programmability to address ITS scalability, delay intolerance and decentralization. It uses a distributed control plane based on a hierarchy of controllers that can dynamically adjust to environment- and network conditions in order to satisfy ITS application requirements. We demonstrate the benefits of D2-ITS through a proof-of-concept prototype using the ns-3 simulation platform. Results indicate lower message delivery latency with minimal additional overhead. <s> BIB009 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Managing resources in dynamic vehicular environments is a tough task, which is becoming more challenging with the increased number of access technologies today available in connected cars (e.g., IEEE 802.11, LTE), in the variety of applications provided on the road (e.g., safety, traffic efficiency, and infotainment), in the amount of driving awareness/coordination required (e.g., local, context, and cooperative awareness), and in the level of automation toward zero-accident driving (e.g., platooning and autonomous driving). The open programmability and logically centralized control features of the software–defined networking (SDN) paradigm offer an attractive means to manage communication and networking resources in the vehicular environment and promise improved performance. In this paper, we enumerate the potentials of software-defined vehicular networks, analyze the need to rethink the traditional SDN approach from theoretical and practical standpoints when applied in this application context, and present an emulation approach based on the proposed node car architecture in Mininet-WiFi to showcase the applicability and some expected benefits of SDN in a selected use case scenario. <s> BIB010 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Client-side video players employ adaptive bitrate (ABR) algorithms to optimize user quality of experience (QoE). Despite the abundance of recently proposed schemes, state-of-the-art ABR algorithms suffer from a key limitation: they use fixed control rules based on simplified or inaccurate models of the deployment environment. As a result, existing schemes inevitably fail to achieve optimal performance across a broad set of network conditions and QoE objectives. We propose Pensieve, a system that generates ABR algorithms using reinforcement learning (RL). Pensieve trains a neural network model that selects bitrates for future video chunks based on observations collected by client video players. Pensieve does not rely on pre-programmed models or assumptions about the environment. Instead, it learns to make ABR decisions solely through observations of the resulting performance of past decisions. As a result, Pensieve automatically learns ABR algorithms that adapt to a wide range of environments and QoE metrics. We compare Pensieve to state-of-the-art ABR algorithms using trace-driven and real world experiments spanning a wide variety of network conditions, QoE metrics, and video properties. In all considered scenarios, Pensieve outperforms the best state-of-the-art scheme, with improvements in average QoE of 12%--25%. Pensieve also generalizes well, outperforming existing schemes even on networks for which it was not explicitly trained. <s> BIB011 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Abstract Business models of network service providers are undergoing an evolving transformation fueled by vertical customer demands and technological advances such as 5G, Software Defined Networking (SDN), and Network Function Virtualization (NFV). Emerging scenarios call for agile network services consuming network, storage, and compute resources across heterogeneous infrastructures and administrative domains. Coordinating resource control and service creation across interconnected domains and diverse technologies becomes a grand challenge. Research and development efforts are being devoted to enabling orchestration processes to automate, coordinate, and manage the deployment and operation of network services. In this survey, we delve into the topic of Network Service Orchestration (NSO) by reviewing the historical background, relevant research projects, enabling technologies, and standardization activities. We define key concepts and propose a taxonomy of NSO approaches and solutions to pave the way towards a common understanding of the various ongoing efforts around the realization of diverse NSO application scenarios. Based on the analysis of the state of affairs, we present a series of open challenges and research opportunities, altogether contributing to a timely and comprehensive survey on the vibrant and strategic topic of network service orchestration. <s> BIB012 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> The challenging requirements of fifth-generation (5G) Internet-of-Things (IoT) applications have motivated a desired need for feasible network architecture, while Named Data Networking (NDN) is a suitable candidate to support the high density IoT applications. To effectively distribute increasingly large volumes of data in large-scale IoT applications, this paper applies network coding techniques into NDN to improve IoT network throughput and efficiency of content delivery for 5G. A probability-based multipath forwarding strategy is designed for network coding to make full use of its potential. To quantify performance benefits of applying network coding in 5G NDN, this paper integrates network coding into a NDN streaming media system implemented in the ndnSIM simulator. The experimental results clearly and fairly demonstrate that considering network coding in 5G NDN can significantly improve the performance, reliability, and QoS. Besides, this is a general solution as it is applicable for most cache approaches. More importantly, our approach has promising potentials in delivering growing IoT applications including high-quality streaming video services. <s> BIB013 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> The explosion of enhanced applications such as live video streaming, video gaming and Virtual Reality calls for efforts to optimize transport protocols to manage the increasing amount of data traffic on future 5G networks. Through bandwidth aggregation over multiple paths, the Multi-Path Transmission Control Protocol (MPTCP) can enhance the performance of network applications. MPTCP can split a large multimedia flow into subflows and apply a congestion control mechanism on each subflow. Segment Routing (SR), a promising source routing approach, has emerged to provide advanced packet forwarding over 5G networks. In this paper, we explore the utilization of MPTCP and SR in SDN-based networks to improve network resources utilization and end- user's QoE for delivering multimedia services over 5G networks. We propose a novel QoE-aware, SDN- based MPTCP/SR approach for service delivery. In order to demonstrate the feasibility of our approach, we implemented an intelligent QoE- centric Multipath Routing Algorithm (QoMRA) on an SDN source routing platform using Mininet and POX controller. We carried out experiments on Dynamic Adaptive video Steaming over HTTP (DASH) applications over various network conditions. The preliminary results show that, our QoE-aware SDN- based MPTCP/SR scheme performs better compared to the conventional TCP approach in terms of throughput, link utilization and the end-user's QoE. <s> BIB014 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm. <s> BIB015 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> The increasing popularity of live video streaming from mobile devices, such as Facebook Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of quality of experience (QoE) as the basis for network control, customer loyalty, and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users’ quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) adaptation; 2) energy efficiency; and 3) multipath content delivery. Discussions, challenges, and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided. <s> BIB016 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> As video-based services become an integral part of the end-users' lives, there is an imminent need for increase in the backhaul capacity and resource management efficiency to enable a highly enhanced multimedia experience to the end-users. The next-generation networking paradigm offers wide advantages over the traditional networks through simplifying the management layer, especially with the adoption of Software Defined Networks (SDN). However, enabling Quality of Service (QoS) provisioning still remains a challenge that needs to be optimized especially for multimedia-based applications. In this paper, we propose LearnQoS, an intelligent QoS management framework for multimedia-based SDNs. LearnQoS employs a policy-based network management (PBNM) to ensure the compliance of QoS requirements and optimizes the operation of PBNM through Reinforcement Learning (RL). The proposed LearnQoS framework is implemented and evaluated under an experimental setup environment and compared with the default SDN operation in terms of PSNR, MOS, throughput and packet loss. <s> BIB017 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Classic network control techniques have as sole objective the fulfillment of Quality-of-Service (QoS) metrics, being quantitative and network- centric. Nowadays, the research community envisions a paradigm shift that will put the emphasis on Quality of Experience (QoE) metrics, which relate directly to the user satisfaction. Yet, assessing QoE from QoS measurements is a challenging task that powerful Software Defined Network controllers are now able to tackle via machine learning techniques. In this paper we focus on a few crucial QoE factors and we first propose a Bayesian Network model to predict re- buffering ratio. Then, we derive our own novel Neural Network search method to prove that the BN correctly captures the discovered stalling data patterns. Finally, we show that hidden variable models based and context information boost performance for all QoE related measures. <s> BIB018 </s> A Holistic Survey of Wireless Multipath Video Streaming <s> VII. OPEN RESEARCH ISSUES <s> Dynamic adaptive video streaming over HTTP (DASH) has been developed as one of the most suitable technologies for the transmission of live and on-demand audio and video content over any IP network. In this work, we propose a machine learning-based method for selecting the optimal target quality, in terms of bitrate, for video streaming through an MPEG-DASH server. The proposed method takes into consideration both the bandwidth availability and the client’s buffer state, as well as the bitrate of each video segment, in order to choose the best available quality/bitrate. The primary purpose of using machine learning for the adaptation is to let clients know/learn about the environment in a supervised manner. By doing this, the efficiency of the rate adaptation can be improved, thus leading to better requests for video representations. Run-time complexity would be minimized, thus improving QoE. The experimental evaluation of the proposed approach showed that the optimal target quality could be predicted with an accuracy of 79%, demonstrating its potential. <s> BIB019
Many research avenues around wireless multipath video streaming are open. In the following, we overview some relevant evolving aspects and present future work opportunities. Standardization developments. MMT is a recent standard protocol with potential abilities discussed in the survey. Future work could evaluate the performance of MMT over MPTCP or QUIC utilizing multipath scheduling methods defined in these protocols for video streaming over heterogeneous networks. HTTP/2 provides noticeable features such as the ability to push content in advance, and frame multiplexing. Therefore, further attention on multipath delivery over HTTP/2 shall be pursuit BIB007 . Another standards related topic would be the use of HEVC, especially SHVC, which do not seem to be widespread in the networking literature despite being widespread in the video coding community. Network Softwarization. Attempts to integrate SDN with multipath video streaming (Section IV-C) promise effectiveness for path-aware strategies due to its ability to programmatically define the end-to-end network behaviour. While OpenFlow is considered the mostly accepted interface between control and data planes  , alternative means for southbound interaction of controllers and datapath devices (e.g. P4 programmable data planes), including SDN protocol extensions relevant for wireless communications (e.g., BIB005 , BIB003 ) deserve further research efforts. SDN and NFV as enabling technologies of multi-domain network service orchestration BIB012 will certainly keep attracting research attention and will play a critical role in the realization of multipath strategies for video streaming and other types of services. 5G. Fifth generation (5G) cellular wireless roll-outs will become reality over the next years. 5G aims to introduce new services that require extreme bandwidth and ultra-low latency  . One concept presented in 5G to reach this goal is the presence of multihoming capability. There is some research on 5G multihoming open challenges and multihoming services BIB006 , BIB008 . Furthermore, there are several study and efforts for MPTCP operation in 5G  , BIB008 . In addition, studies show that emerging technologies such as SDN to MPTCP in 5G networks could improve the transmission performance due to SDN capability to control the subflows by monitoring network condition BIB013 , BIB014 . Therefore, video streaming over 5G networks is an important emerging research area where innovative solutions will be required considering multihoming solutions along SDN/NFV-based technologies. WiFi Evolution. There are also big advancement in wireless technologies from WiFi communication to increase the wireless networking performance such as 802.11ad and 802.11ay for 60 GHz, or 802.11ax for 2.4 Ghz and 5 Ghz concurrently, in the near future  ,  aim to achieve great throughput and ultra-low latency. Therefore, there is room to evaluate whether these new WiFi technologies can support video streaming alone or not? Another open question here is to explore the impact of these new WiFi technologies on multipath video streaming. Energy considerations. Power efficiency is an essential requirement. The work BIB001 shows high power consumption by LTE when video streams over HTTP. Energy consumption even increases more by using multiple network interfaces. Therefore, optimizing power consumption needs further attention in the proposed approaches. Security. Multipath delivery could mitigate some security threats inherently through the use of alternative paths throughout the network. There is little work in the scope of multipath multimedia streaming security. At the same time, Digital Rights Management (DRM) and the license issues are also security related issues critical for some video services. Mobility and Internet of Vehicles (IoV). Although terminal mobility, velocity, motion degree and related mobile aspects are factors affecting video quality, they are rarely discussed in the literature. This type of considerations are be key in the delivery of wireless video in mobile environments in scope of Intelligent Transport Systems (ITS) BIB009 and Vehicle-toeverything (V2X) communications BIB010 . Machine Learning and Artificial Intelligence. Leveraging artificial intelligence and machine learning methods are increasingly becoming key tools for network and service optimization BIB015 and can be used for advanced scheduling and adaptive coding decisions BIB011 . The importance of machine learning approaches to improve video quality has been recognized by Netflix which proposed a new video quality assessment method named Video Multimethod Assessment Fusion (VMAF). VMAF is a machine learning-based model that is trained and tested using the results of a subjective experiment in order to deliver the best video quality to the user BIB016 . Besides, there are also several machine learning-based efforts to learn QoS measurements BIB017 or QoE from user reactions BIB018 , BIB019 to solve various optimization and control problems for a single path video streaming. In our state-of-art, there are some approaches utilizing machine learning systems learning QoS from user device and using it for multipath scheduling decisions BIB002 , BIB004 . Thus, similarly, an interesting solution could be utilizing machine learning systems learning QoE from user reactions and using it for multipath scheduling decisions.