Network Outage Resolution: Vendor Coordination And Equipment Replacement. – Methodologies for determining the service quality of intercity rail service based on users’ perceptions and expectations in Thailand

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Network Outage Resolution: Vendor Coordination And Equipment Replacement.

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By Jehad Ali Jehad Ali Scilit Preprints.org Google Scholar View Publications 1 , Gyu-min Lee Gyu-min Lee Scilit Preprints.org Google Scholar View Publications 1 , Byeong-hee Roh Byeong-hee Roh Scilit Preprints.org Google Scholar View Publications 1 , * , Dong Kuk Ryu Dong Kuk Ryu Scilit Preprints.org Google Scholar View Publications 2 and Gyudong Park Gyudong Park Scilit Preprints.org Google Scholar View Publications 2

Received: April 7, 2020 / Viewed: May 13, 2020 / Accepted: May 21, 2020 / Published: May 22, 2020

Implementing new optimal routing rules in routers is difficult because of the dense coupling of data and control planes and the lack of global topological information. Due to the decentralized nature of traditional classical Internet Protocol networks, routing rules and policies are distributed in a decentralized manner, leading to loopback problems in the event of a link failure. Software-defined networking (SDN) provides programming from a central point to the network. As a result, the data plane nodes or devices in SDN only forward packets and the control plane complexity is left to the controller. Therefore, the controller installs rules and policies from a central location. With centralized management, switch failure detection and flexible recovery because the controller has knowledge of the global network topology. Similarly, new optimal rules can be deployed to restore links from a central point. Here we will review several schemes for restoring link failures using SDN while illustrating the shortcomings of the traditional network. We also explore open research questions presented by the SDN architecture. This paper also analyzes proactive and reactive plans in SDN using OpenDayLight and Minnet controller with simulation of application scenarios from tactical networks and data centers.

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Software-defined networking (SDN) separates the control plane from the data plane, i.e. transfers the control logic from network devices to a central controller. A central controller manages the data flow through a southbound application programming interface (SB-API). Similarly, centralized management of network facilities has the advantage that new applications, services and network functions can be implemented flexibly with minimal operational and capital costs. Several survey studies on SDN operation, history, architecture, programming and research directions are described in [1, 2, 3, 4, 5, 6].

Link failure recovery approaches take advantage of SDN’s unique features of centralized management and programmable data plane flexibility for real-time applications such as video conferencing [7] and Voice over IP (VOIP). reconstruction. Thus, the quality of service (QoS) can be maintained in case of connection failure to ensure smooth and constant connectivity. The reported average of daily link and device failures in a traditional data center network is recorded as 40.8 and 5.2 failures per time unit, respectively [8], which necessitates the discovery of a method that enables faster recovery of failed links. Research [8] also reported that the frequency of link failures is higher than that of node failures. Therefore, fault-tolerant approaches play an important role in traffic engineering for operator networks and ensure fast fault recovery that ultimately meets end-user requirements.

In legacy networks, the tight coupling of the control and data planes makes them slow and difficult to manage. Although traditional networks are accepted worldwide, their management and configuration are difficult for the following reasons [9]:

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In the event of a link failure, rerouting is performed to find an alternate path to route packets from the failed link to the alternate path. However, the implementation of traditional routing protocols hinders network growth and causes delays due to several problems, such as link state information overflow, long path discovery convergence time [14], network layout complexity [15], and induced routing. by instability in the prefix. flaps [16]. In addition, there may be instability in the network due to route collisions due to autonomous system (AS) [17]. As a result, there are no optimal decisions due to the lack of global statistics of the network. These problems exist in the traditional Internet architecture For two reasons: first, because implementing changes to traditional routing protocols is difficult due to the software embedded in the firmware; second, Internet companies feel the risk and are reluctant to implement new proposals, even if they can improve network performance, which will also increase network complexity and ultimately maintenance costs .

Fast fault recovery within a defined time interval is critical to ensuring service assurance in next-generation technologies. Several architectures [18, 19, 20] have been proposed in the literature to ensure fast recovery of networks. The architecture proposed in [18] consists of an automatic failure recovery or fault management framework. The research in [19] uses 5G, secure Internet of Things (IoT) and unmanned aerial vehicles (UAVs) to provide service in mission-critical infrastructures. Also, a platform for virtualization of services based on SDN and Network Function Virtualization ( NFV) [20] which enables the development, implementation and operation of media services on 5G networks.

In addition, nodes can operate in remote and harsh environments with the possibility of frequent failures. Therefore, sequential modifications are essential to find an alternative path to failed nodes [ 21 ]. In addition, SDN handles link failures using one of two main approaches, proactive and reactive [22]. In a proactive approach, alternate paths are predefined and disrupted flows are routed to the backup path in case of link failure. In contrast, in a reactive scheme, it approaches the controller to find an alternate path, and when the controller calculates the path, the flow rules for the new path are inserted. With access to global topology information, the SDN controller will search for the optimal alternate path for the failed link and apply flow rules to it. Thus, the data plane is undisturbed. As a result, due to the centralized management architecture, packets are not broadcast to the network here, which leads to improved network performance. However, both programs have their own advantages and disadvantages, as well as competition in terms of performance and efficiency.

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Link fault recovery in SDN is reviewed in [23, 24]. In this survey, we explore approaches for link failure detection and recovery in SDN. A demonstration of SDN-based fault recovery with proactive and reactive approaches is provided with pictorial diagrams. We compare proactive and reactive schemes in terms of latency, scalability, routing updates, triple memory space (TCAM), consistency of flow operations, configuration, robustness against backup path failures, information access routing, link processing. Routing, controller and switch overhead. Research issues in SDN-based link fault recovery schemes for large-scale, hybrid, cross-domain, in-band, and machine learning (ML) approaches are discussed and summarized. We simulate two application scenarios on the Mininet test bed for Navy Tactical Networks and Data Centers (DCN) and evaluate recovery time and throughput when using proactive and reactive schemes.

The rest of the paper is organized as follows. Section 2 provides an overview of SDN architecture and explains the importance of SDN in achieving recovery. In Section 3, we discuss various techniques for detecting link errors. Section 4 covers large-scale networks, cross-domain architecture, hybrid SDN, in-band environment, and more. ML-based techniques. In Section 5, we discuss SDN application scenarios, experimental setup, and proactive and experimental demonstration.

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