مقاله انگلیسی رایگان در مورد رویکردهای شبکه های نرم افزار محور (SDN) – الزویر 2017

1- Introduction

2- An overview of SDN architecture and openflow protocol

3- Scalability and its causes in SDN

4- Classification of control plane scalability proposals

5- Topology-related approaches

6- Mechanisms-related approaches

7- Comparison of control plane scalability proposals

8- Challenges and existing proposals in SDN control plane

9- Conclusions

References

Abstract

Software-Defined Networking (SDN) architecture has emerged in response to limitations of traditional networking architectures in satisfying today’s complex networking needs. In particular, SDN allows network administrators to manage network services through abstraction of lower-level functionality. However, SDN is a logically centralized technology. Therefore, scalability, and especially the control plane (i.e. controller) scalability in SDN is one of the problems that needs more attention. In this survey paper, we first discuss the scalability problems of controller(s) in an SDN architecture. We then comprehensively survey and summarize the characterizations and taxonomy of state-of-the-art studies in SDN control plane scalability. We organize the discussion on control plane scalability into two broad approaches: Topology-related approaches and Mechanisms-related approaches. In Topology-related approaches, we study the relation between topology of architectures and scalability issues. It has sub-categories of Centralized (Single) Controller Designs and Distributed approaches. Distributed approaches, in turn, have also sub-categories: Distributed (Flat) Controller Designs, Hierarchical Controller Designs, and Hybrid Designs. In Mechanisms-related approaches, we review the relation between various mechanisms used to optimize controllers and scalability issues. It has sub-categories of Parallelism-based Optimization and Control Plane Routing Scheme-based Optimization. Furthermore, we outline the potential challenges and open problems that need to be addressed further for more scalable SDN control planes.

Introduction

Increasing cloud services, server virtualization, sharp growth of mobility and content-like video have led researchers to rethink today’s network architectures. In traditional architectures, network devices and appliances are complex and difficult for (re)configuration and (re)installation since they re-quire highly skilled personnel. Adding or moving a device from a network requires extra costs. It is also time-consuming because IT people need to deal with multiple switches, routers, etc. and update ACLs, VLANs and other mechanisms [1]. Furthermore, as business demands or user needs increase day by day, application developers, carriers, and enterprises delve into evolving new services and facilities. However, vendor dependency is an obstacle deterring them from developing new networking applications and services for their networks due to slow equipment product cycle, application testing and deploy ment. Therefore, today’s data centers, carriers, and campuses need more dynamic architectures. Software Defined Networking (SDN) [2]-[6] architecture has emerged in response to the aforementioned limitations of traditional networking architectures. SDN aims to decouple the control plane and data plane. This separation provides network operators/administrators with efficient use of network resources and eases provisioning of resources. Also, SDN brings ease of programmability in changing the characteristics of whole networks. This simplifies the management of the network, since it is decoupled from the data plane. Therefore, network operators can easily and quickly manage, configure, and optimize network resources with dynamic, automated and proprietary-free programs in SDN architecture [7]. Google’s datacenter WAN, B4 [8], is one of the examples for SDN adopted in a large-scale network with the aforementioned purposes. In addition, since the network is logically centralized in SDN, controllers have a global visibility of the whole network unlike conventional networking. Hence, they can dynamically optimize flow-management and resources. Despite the advantages of centralized control in SDN architectures, SDN faces some issues challenging its nature (i.e. centralized control) due to day by day increasing network demands. Although network operators enhance the performance of the network controllers, it still cannot be enough to meet the high network demands such as flow request and monitoring network statistics. For example, one of the earlier SDN controllers, NOX [9], can serve only 30K flow requests per second with a response time less than 10 ms. This insufficiency appears more in large-scale networks or data centers compared to small networks. Kandula et al. [10] report that a cluster of 1500 servers receives 100K flows per second on average. Also, Erickson [11] states that a network with 100 switches can result in 10 million flow arrivals per second in the worst case. These numbers indicate that the control plane in an SDN architecture is prone to suffer from scalability issues due to its centralized nature. Furthermore, Sezer et al. [1] state that one of the main challenges in SDN is the scalability issue, which especially needs more attention by researchers.