# Software Defined Wireless Mesh Network Flat Distribution Control Plane
## 1 Introduction  
Wireless Mesh Networks (WMNs)are multi-hop networks that are regarded as a wireless potential key architecture providing wide Internet coverage for specific areas. They have a significant role in various scenarios of applications such as public safety, transportation, enterprise networks, mining fields and emergency response, etc. The deployment and use of WMNs is relatively quick and low-cost due to there being no need for any wired network as a backbone [1]. A WMN consists of three types of nodes: mesh clients (any end-user wireless device e.g., smart phone, laptop, etc. ), mesh routers (to build a wireless network backbone), and gateways (special routers that can connect to the Internet). In infrastructure WMNs, mesh routers are static and can be equipped with several radio technologies, such as WiFi (IEEE 802.11), ZigBee (IEEE 802.15.4) and WiMAX (IEEE 802.16) [2; 3] fora high coverage of the targeted area. Despite the steadily evolving wireless technology standards, there are structural barriers that still prevent wireless networks' infrastructure from being open to fulfilling technical innovation requirements [4]. Software Defined Wireless Networks (SDWN) [5; 6] is the technical term of applying Software Defined Networking's (SDN) concepts to wireless networks. SDWN attempts to inherit (wired) SDN flexibility, it decouples radio control and radio data forward functions from each other, to assist wireless networks in becoming more flexible by abstracting the underlying wireless infrastructure from network services and applications through higher-level APIs. So, wireless networks under SDNarchitecture are becoming more innovative ecosystems and break down mentioned structural barriers. As a consequence, wireless networks were faced with applied challenges such as boot-strapping [7] (i.e., network control plane initialization), topology discovery, link quality specifications monitoring, among others [8]. In this work, we propose solutions to these challenges in an SDN-based WMN which is called the Software Defined Wireless Mesh Network (SDWMN) [9]. SDN can create resilient network architectures. It can create a physically centralized network control architecture (a single controller or controllers in a master/slave approach) or a physically distributed logically centralized architecture that relies on distributed controllers organized either hierarchically or flatly, to control multi-domains to achieve network reliability and scalability [10; 11]. The distributed control plane approach incurs different complexity to develop and manage SDN controllers. However, these solutions are more responsive to network status changing and handling related events, because the controllers distribute through the network closer to resources of events than in centralized architecture. Several studies [12; 13; 14] distribute SDN controllers to handle the network control plane workload based on topology. They follow topological structures on the controllers' distribution in network architecture in flat and hierarchical designs. An orchestration framework requires maintaining the topology of all network domains [15]. So, an effective network topology discovery mechanism is essential for managing the network and deploying end-to-end applications and services on top of the orchestration architecture among multiple distributed domains. The network global view is a critical factor in SDN architecture, and the controller provides such view by a topology discovery service. Thus, the information offered by topology discovery is crucial for network applications such as routing, network resources allocation and management, and fault recovery that reside on top of the SDN controller. In this context, the topology discovery process time and load are fundamental for a timely and lightweight response. Therefore, up-to-date network topology discovery must use efficient mechanisms in SDN architecture, and it becomes one of the significant design metrics for SDN scalability [16].