# A Comprehensive Survey on Knowledge-Defined Networking
## 7 Application Plane
### Application Scenarios
#### 7.3.2 Network Management
In [465], the optimal number of reserved channels is decided based on secondary user retainability and channel availability, while an application policy considers the primary user channel availability minimum by monitoring the incoming traffic requests. A Hierarchical Agglomerative Clustering (HAC) framework to control all sub-channels in the network to decide on cluster merging in ultra-dense small cell networks with an application policy to mitigate severe interference among small cell base stations has been proposed in [466]. Furthermore, mobility management also includes offloading, such as Wi-Fi device to device offloading from cellular networks when device to device communication is available [467]. By monitoring fluctuating traffic loads, work in [468] uses radio resource allocation and transmit beamforming using optimization to allocate physical resource blocks, user equipment, radio units, and the downlink transmit beamforming by having an application policy to consider imperfect channel state information. Mobility management also includes radio resource sharing. A framework known as LayBack, which has an application policy to facilitate communication and computation resource sharing among different wireless technologies and operators by organizing resources into layers, uses KDN to manage fronthaul and backhaul resources, and coordinates the corporation between different wireless technologies and operators, has been studied in [469]. OpenRadio and SoftRAN are platforms that define policies to allow a software abstraction layer for decoupling wireless protocol definition from the hardware to allow sharing of MAC layers among different protocols for better handover, resource block allocation, etc. [470]. Open Radio Access Network (ORAN) is an emerging approach for designing and deploying mobile network infrastructure that aims to create more interoperable wireless networks [471]. Research in [471] suggests the integration of AI and machine learning into ORAN so that KDN and ORAN can be integrated together for efficient wireless network resource utilization and mobility management. Energy management is a crucial application in a KDN that involves reducing network power consumption while attaining other infrastructure goals such as less latency, high throughput, high fault tolerance, etc., using specialized optimization algorithms and application policies. For instance, applications can use simple high-level policies such as shutting down or sleeping links or devices to reduce energy consumption [472]. Another energy-saving technique is Dynamic Voltage and Frequency Scaling (DVFS), where the manager in KDN can manage the operating voltage and frequency of the switches based on the knowledge of device workload to manage the energy of the devices [473]. Energy-aware routing has been employed with energy-aware application services such as tunneling for fast rerouting, smooth node disabling, and detection of traffic spikes and link failures, which has reduced the energy consumption of internet service providers by 5% to 35% [474]. In [475], the authors discuss the feasibility of an application that implements services in an ONOS network operating system to implement energy-awaretraffic engineering strategies. Therefore, routing and traffic engineering can also be adapted to optimize the energy efficiency of the network. Furthermore, applications can use network virtualization to save energy of the network, as it reduces the number of physical devices required. In [476], the authors use a multi-objective virtual network embedding with the objectives of minimizing network congestion and energy consumption, where they use a path service and a resource monitoring application in the manager. Network function virtualization, along with an application policy to utilize a cluster head selection algorithm in a blockchain-based distributed IoT network, has been utilized to save energy [477].