## 2 Related Work
### Traditional WSN Routing Approaches  
Traditionally, proactive and reactive routing is included in wireless network routing. Proactive routing (e.g., OLSR [15]) in each node depends on broadcast information, and all routing information (i.e., from the current node to all other nodes routing path information) is stored, which causes a memory overhead. That is why the high dynamic network does not adapt to active routing. Reactive routing, such as an ad-hoc on-demand distance vector (AODV), has become an Institute of Electronics and Telecommunication Engineers (IETE) standard and was presented in 1999. It selects the routing path from source to destination by considering the number of hops [16; 17]. AODV uses flooding to maintain and establish the route. Due to its flooding nature, the wastage of network resources is high. Clustering protocols may help to aggregate the data by organizing the network in an inefficient manner. A low-energy adaptive clustering hierarchy (LEACH) [18] is a hierarchical protocol that transmits the data from nodes to cluster heads (CHs) to forward to the base station (sink). The CH role among nodes is played based on a predetermined probability by avoiding the fast depletion of CH energy. LEACH has two phases: The first phase is the cluster setup phase that selects the CHs to aggregate the information from its cluster and broadcast it to other nodes, and the second one is  
Figure 2: Software defined wireless sensor networks (SDWSNs) architecture. the steady phase that is used for the actual transmission of data. However, during the setup phase, LEACH only takes into account energy consumption when advertisements are received from CHs at every node. CHs do not show a good distribution because of variation in the number of CHs. Moreover, in the LEACH protocol, a CH communicate with a sink node through a single hop in which a large amount of energy is consumed when the distance between CHs and sink is large. A heterogeneous protocol HEED (hybrid energy-efficient distributed) for clustering of wireless sensor network has been presented in [19]. Different levels of heterogeneity (i.e., 2-level, 3-level, and multi-level) are introduced to prolong network lifetime. In HEED, a cluster head is formed through the initial probability of every node based on its remaining energy that shows better performance in terms of network lifetime. A protocol named TEEN (threshold-sensitive energy-efficient sensor networks) has been presented for time critical based applications [20]. Often, data transmission is lesser as sensor nodes continuously sense the medium. A cluster sensor directs a small change in the soft threshold (ST) to trigger the node that has switched on its transmitter, and a hard threshold (HT) shows a value of sensed attribute. The disadvantage of this scheme is that the user does not receive any data because the nodes will not communicate when thresholds are not received. It also offers the implementation scheme of threshold-based functions [20] and suffers from the complexity in forming a cluster at multiple levels. In [21], zone probabilistic routing (ZPR) is proposed to reduce energy consumption and enhance network lifetime. The data packets are sent randomly routed from source to destination through any path within the defined routing zone. In ZPR, Four Probability Distributions (4 PD) are used to define the probability distribution that is completely controlled via a set of control parameters (residual energy, perpendicular distance, direction, and transmission distance). The issue of load balancing in WSN clustering also becomes critical that leads to increasing the WSN energy consumption and is addressed by some authors [22; 23] that consider the hop distances for the clusters. A scheme named energy-delay index for trade-off (EDIT) in [24] is proposed to select the CH for the optimization of both delay and energy. In [25], a delay award energy efficient Routing (DERM) protocol was proposed to achieve the energy efficiency of WSN with minimum delay.