摘要:近年来，随着虚拟现实、物联网、云计算等新兴技术的发展，用户对网络带宽的需求迅猛增加，使用单一接入技术已经难以满足用户对网络带宽的需求.为了解决用户日益增长的带宽需求和有限的频率资源之间的矛盾，互联网端到端多路径传输技术应运而生.互联网端到端多路径传输协议，如MPTCP （multipath TCP），目前主要工作于传输层，能够利用终端已经具备的多块网卡（如WiFi网卡和4G网卡）同时进行数据的端到端并发传输，从而提高总的传输带宽和对网络动态性的适应能力.由于每条子流可以通过TCP协议及其优化算法实现端到端的可靠有序传输，因此端到端多路径传输的研究重点在于多条子流之间的智能协同，主要体现在子流选择、数据分配和调度、联合拥塞控制等方面.然而，底层链路的动态变化使得传输层所估计的链路参数无法及时地反映当前链路的状态，异构物理网络接口具有不同的资源分配特点，不同子流在网络层存在部分传输路径重合问题，上层应用的数据包在截止时间、重要性、失真率等方面存在差异，这些都将给端到端多路径传输中子流之间的智能协同带来影响.因此，仅仅依靠传统的传输层信息无法有效发挥多路径传输的优势，需要在传输层对其他层次的相关参数进行有效利用.为此，近年来有关研究着手利用物理层、链路层、网络层以及应用层的相关信息，通过跨层联合优化来有效地提升多路径传输的优势.比较了近年来利用跨层信息进行多路径传输优化的研究，分析了各层的功能特点及其与多路径传输的关系，并在最后对未来的研究趋势进行了展望.



Abstract:Recently, with the development of new technologies like virtual reality, Internet of Things, cloud computing, and so on, the user demand on network bandwidth increases sharply, and it is hard to meet user bandwidth demand by making use of single access technology. To solve the contradiction between users' increasing bandwidth demand and limited frequency resources, Internet end-to-end multipath transmission technologies are designed. Internet end-to-end multipath transmission protocols, like MPTCP (multipath TCP), mainly work at transport layer, and they can make use of existing multiple network cards (for example WiFi and 4G) to do concurrent transmission, the total transmission bandwidth and the adaptability to network variation are improved. Since the subflows of MPTCP can realize end-to-end reliable in order delivery based on TCP and its optimizations, research works related to multipath transmission focus on the intelligent coorperations among subflows, the coorperations mainly include subflow selection, data scheduling, coupled congestion control, and so on. Nevertheless, as the estimation of network status at transport layer may not reflect current link state accurately due to the variation of link and physical layer, heterogeneous network interfaces have different resource allocation schemes, different subflows may have partially overlapped paths, the upper application layer have different characteristics in deadline, frame importance, distortion rate, and so on. These will affect the performance of the intelligent coorpertaions among subflows, the advantage of multipath transfer can not be fully exploited by only making use of traditional transport layer information, the information at other layers should also be utilized. So in recent years, many research papers start to make use of physical, link, network, and application layer information to improve multipath transmission performance efficiently with cross layer cooperated optimization. This paper compares the research of multipath transfer optimization with cross layer information, analyzes the relationship between multipath transfer and the function of different layer, and the outlook of future research trends is provided in the end.



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