# Software Defined Networking for Improved Wireless Sensor Network Management: A Survey
## 5 Management of WSNs Based on SDN
### Energy Management  
Energy management focuses on the several techniques available to leverage SDN in ensuring that energy utilization is minimized in an already energy resource constrained WSN. Several proposals for adopting energy management in the SDN controller for the global balance of energy utilized in the WSN have been made. Integration SDN in WSNs allows for energy consuming tasks such as data traffic routing decisions to be handled in the controller leaving the energy constrained sensor only with the task of forwarding data traffic inherently reducing the amount of energy used. Part of the topology management of WSNs based on SDN is focused on using SDN for resource allocation control. To enhance resource allocation architectures and topologies likewise have been proposed such as the SDWN [60] and Smart [14] both executing controller functions on the sink node freeing remaining sensor nodes from functions like localization, QoS and mobility management resulting in energy efficient operation. Similarly, a general framework for has been been proposed that places the controller at the base station with centre nodes in each cluster integrating switching and communication functions with the controller based on OpenFlow [119]. Management of energy has also been demonstrated by establishing control through software in a method referred to as duty cycling, focusing on reducing the amount of energy consumed by the sensor nodes through control of the sleep and wake up states. This technique has been proposed severally for managing WSNs [35, 120, 121] however SDN-based architectures rely on cross layer communication between the decoupled control and data planes which may require a robust link for the control traffic flow to be optimized in addition to the need for energy saving through data aggregation; using techniques that switch nodes on and off may result in unreliability in the communication links. Multi-tasking of WSNs has been proposed as an architecture based on SDN to minimize energy utilization in [122]. Multi-tasking is possible through the ability of the sensor node to carry out multiple tasks at the same time achieving different sensing outputs and to achieve a desired Quality of Sensing (QoSen) a task is carried out collectively by multiple nodes. [PERSON] et al. [122] present an architecture allowing for energy efficiency in sensor scheduling and management while producing the required QoSen. A Mixed Integer Linear Program (MILP) is formulated to take into account three objectives: sensor activation, task mapping and sensing scheduling. Further work is also done on developing an on-line algorithm to handle the dynamics associated with nodes entering the network (mobility) or leaving the network (mobility or node failure) with simulation results showing equal energy efficiency as a global optimized network with the advantage of having a lower rescheduling time and overhead control data. Inherent in the SDN-based management is a high control traffic overhead to maintain the global view of the logically centralized controller; a process that requires more energy for operation and thus affecting the energy efficiency of the network. [PERSON] et al. [123] propose a prototype based on reinforcement learning to improve energy efficiency of SDN-based WSNs. The technique reduces overhead control traffic by filtering redundancy and performing a load-balancing routing mechanism in accordance to data flow distribution with the required QoS. Experiments on the proposed SDN-based WSN prototype showed an improved energy efficiency performance. Energy management techniques such as data aggregation and information fusion [124] coupled with multi-hop communication used in WSNs [125] can be extended and applied to within each cluster. Multi-hop links can take advantage of the densely located sensor nodes to transmit data at low power [108]. More recently, an efficient energy harvesting management technique based on wireless power transfer for SDN-based WSNs has been proposed [126].