You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Performances of OpenFlow-Based Software- Defined Networks: An overview 
Chapter Title:  C. Multithreading-Based Improvements 
1. Abstract of Cited Paper (BIB001):  OpenFlow is currently the most commonly deployed Software Defined Networking (SDN) technology. SDN consists of decoupling the control and data planes of a network. A software-based controller is responsible for managing the forwarding information of one or more switches; the hardware only handles the forwarding of traffic according to the rules set by the controller. OpenFlow is an SDN technology proposed to standardize the way that a controller communicates with network devices in an SDN architecture. It was proposed to enable researchers to test new ideas in a production environment. OpenFlow provides a specification to migrate the control logic from a switch into the controller. It also defines a protocol for the communication between the controller and the switches. As discussed in this survey paper, OpenFlow-based architectures have specific capabilities that can be exploited by researchers to experiment with new ideas and test novel applications. These capabilities include software-based traffic analysis, centralized control, dynamic updating of forwarding rules and flow abstraction. OpenFlow-based applications have been proposed to ease the configuration of a network, to simplify network management and to add security features, to virtualize networks and data centers and to deploy mobile systems. These applications run on top of networking operating systems such as Nox, Beacon, Maestro, Floodlight, Trema or Node.Flow. Larger scale OpenFlow infrastructures have been deployed to allow the research community to run experiments and test their applications in more realistic scenarios. Also, studies have measured the performance of OpenFlow networks through modelling and experimentation. We describe the challenges facing the large scale deployment of OpenFlow-based networks and we discuss future research directions of this technology.

Literature Review:
Authors in BIB001 attempt to understand the implication of using multi-threading techniques in SDNs. They have introduced a new multi-threaded controller called NOX-MT (new release of the NOX OpenFlow controller). The main conclusion is that NOX-MT improves the controller throughput by more than 30 times. Indeed, NOX-MT takes full advantage of multi-core processors using multithreading techniques that can run multi-tasks concurrently and handling different tasks at the same time, hence making optimal use of the available resources. An important study that investigates the impact of multithreading on performances is given BIB002 . The authors perform a comparison between different controllers in term of performance, especially the throughput. In fact, two major factors distinguish controllers, the first one is the algorithm of distributing incoming messages between threads, and the second one is the mechanism or the libraries used for network interaction. Using different number of threads (from 1 up to 12) shows that single threaded controllers (Nox and Ryu) are very limited regarding the throughput because they cannot handle a large number of flows, however the Beacon controller which is multi-threaded can handle a large number of flows per second. Knowing that Python controllers (POX and Ryu) do not support multi-threading, they show no scalability despite a number of CPU cores. Maestro's scalability is limited to 8 cores as the controller does not run with more than 8 threads. The performance of Floodlight increases steadily in line with the increase in the number of cores. Finally, Beacon achieves a throughput of nearly 7 million flows per second and shows the best scalability. From the previous studies, we conclude that the characteristics and performances of SDN controllers may be very different. So, it's important to carefully choose the OpenFlow controller. At the end of this section, we give a summary of some famous controllers and their characteristics in the table 1. In particular, we specify the OpenFlow version that they support, their throughput, if they are multi-threaded or not, if they can be distributed or not (distributed controllers will be considered in the next section). Also we classify all controllers by their ability to support OpenStack, which is an open source platform for creating and managing public or private cloud.