A Survey on Efforts to Evolve the Control Plane of Inter-Domain Routing <s> Inter-Domain Routing Limitations <s> An Internet autonomous system (AS) uses BGP policies in order to meet its local objectives (e.g. optimal routing within AS) and peering contracts with neighboring ASes (e.g. advertising some specific routes to a neighbor, forwarding traffic over specific paths, etc.) In this paper we propose an enhancement of BGP route selection and advertisement processes, and demonstrate how the enhanced BGP can be used to flexibly implement diverse policies, regardless of the network topology, that were not feasible before. <s> BIB001 </s> A Survey on Efforts to Evolve the Control Plane of Inter-Domain Routing <s> Inter-Domain Routing Limitations <s> Software Defined Networking (SDN) separates the tightly coupled network control and data forwarding functions. During the past years, it has been applied in all kinds of intra-domain networks, such as enterprise networks, data centers and content provider networks. However, it is a big challenge to extend SDN to inter-domain networks. In this paper, we extend the advantage of SDN to an inter-domain network federation to improve the Internet routing flexibility. To achieve this goal, we propose a Multi-dimension Link Vector network view exchange mechanism (MLV) to exchange the fine-grained inter-domain routing information and enable programmable inter-domain routing. MLV can support flexible inter-domain routing control by exchanging multiple fields of the IP header. Based on MLV, innovations in inter-domain routing can be deployed as applications over SDN controllers. In order to validate the MLV design, we analyzed its performance with BGP-derived Internet AS topology. Finally, we implemented a prototype of MLV and tested it on an internationally collaborative inter-domain SDN testbed. <s> BIB002 </s> A Survey on Efforts to Evolve the Control Plane of Inter-Domain Routing <s> Inter-Domain Routing Limitations <s> The fast development of the Internet and the huge number of gadgets connected to it has immerged with the challenge of focusing on the requirement for further computerization and automation in the system administration and architecture of network field. It is becoming increasingly difficult for businesses to afford a downtime in their Internet system and it is also very important to make configuration management and error reduction easy [1]. Some of the tasks which are involved in the management of network configuration include maintaining configuration files, building a standard for all the device maintenance, repair, replacement and upgrades, issue proper rollback commands and have a proper backup archive [2]. <s> BIB003 </s> A Survey on Efforts to Evolve the Control Plane of Inter-Domain Routing <s> Inter-Domain Routing Limitations <s> Currently, the network traffic control systems are mainly composed of the Internet core and wired/wireless heterogeneous backbone networks. Recently, these packet-switched systems are experiencing an explosive network traffic growth due to the rapid development of communication technologies. The existing network policies are not sophisticated enough to cope with the continually varying network conditions arising from the tremendous traffic growth. Deep learning, with the recent breakthrough in the machine learning/intelligence area, appears to be a viable approach for the network operators to configure and manage their networks in a more intelligent and autonomous fashion. While deep learning has received a significant research attention in a number of other domains such as computer vision, speech recognition, robotics, and so forth, its applications in network traffic control systems are relatively recent and garnered rather little attention. In this paper, we address this point and indicate the necessity of surveying the scattered works on deep learning applications for various network traffic control aspects. In this vein, we provide an overview of the state-of-the-art deep learning architectures and algorithms relevant to the network traffic control systems. Also, we discuss the deep learning enablers for network systems. In addition, we discuss, in detail, a new use case, i.e., deep learning based intelligent routing. We demonstrate the effectiveness of the deep learning-based routing approach in contrast with the conventional routing strategy. Furthermore, we discuss a number of open research issues, which researchers may find useful in the future. <s> BIB004
The BGP will never select two, or more, next hops per prefix. It always chooses a unique best hop per prefix. Different from internal routing protocols (e.g., the ECMP) where multiple destinations are allowed to a given prefix for load balancing proposes, the BGP standard protocol does not incorporate this behavior. Hence, to network, operators maximize the utilization of external links, and they have to split the traffic using a subnet of the prefix, which has the side effect of increasing the global routing table (Figure 3) . The use of multiple links may have the consequence of improving path diversity and network reliability BIB001 . The BGP can filter routes by matching prefix, prefix-length and/or based on different path attributes that are associated with each BGP route and are part of an update message. However, the forwarding data plane elements can only forward the packet based on destination prefixes, once the BGP follows a destination-based forwarding paradigm  . In other words, routers can only apply their policies and forward decision based on the destination address of the IP packet. Routing systems that use source addresses, policy-based routing or are based on application requirements cannot be deployed on the current Internet as this is not supported by the current BGP logic of control. Furthermore, novel network applications may require some other fields in the packet header to optimize the inter-domain routing path or simply to distinguish routing by source addresses BIB002 . Those requirements are not available with the use of the BGP. Moreover, it has long been known that the Internet architecture has several issues, despite the Internet's unparalleled success. Highly rigid and static, the traditional networking infrastructure was initially designed to operate for a particular type of traffic (text-based content), and that does not satisfy today's increasingly demanding users that request interactive and dynamic multimedia streams. Along with the multimedia trends, the recent emergence of new and innovate technologies, e.g., IoT, has been pressuring the inter-domain infrastructure to support those new types of network demands. Previous works have attempted to solve these architectural deficiencies with brand new designs or incremental improvements, which have had limited success  . On the one hand, the resistance to these new efforts stems from the requirement that new solutions must be mature enough and have obvious benefits. In other words, an AS will not risk its business existence in adopting technologies with unproven scalability, reliability, interoperability and consistency. Moreover, the current Internet's infrastructure took years to reach its current size, and a myriad of ASs is still expecting to reach the Return on Investment (ROI) from that. On the other hand, many ASs are searching for ways to increase their profit: be more agile to address business requirement changes, provide a network that reduces cost, simplifies operations and supports new and innovative products and services. Thereby, the next generation control plane needs to be more suitable to their business needs, and it is expected that automation BIB003 and intelligent network traffic control systems BIB004 will play an important role in evolving the inter-domain routing. Therefore, to bridge the gap between what is expected and desirable on architectural evolvability and what is feasibly deployable has to include, among other ideas, modularity solutions with BGP compatibility and extensive support of automation.