## 4 Congestion Mitigation Algorithms for WSNs
### Previous Work on WSN Congestion Mitigation Schemes
#### 4.1.2 RPL-Based Algorithms for Congestion Mitigation in WSN  
A plan to reduce IoT congestion was presented in [60] by [PERSON] and colleagues. IoT traffic congests the nodes on the sink side. The proposed routing protocol is based on a three-phase balanced zone to solve this problem. In the first phase, the network is divided into clusters of equal size. In the second phase, a zone leader is selected for each zone with the least IoT traffic. For this zone, this leader is responsible for routing. In the third stage, the zones are divided according to the degree of congestion. This research can be used to reduce congestion at both the inter-cluster and intra-cluster levels.  
[PERSON] et al. in [45] proposed a Reliable and Energy Efficient Protocol (REEP), a reliable data routing protocol with congestion mitigation for IoT networks. This routing technology is data-centric and demand-driven. The routing stage is determined by local communication. However, this technique incurs significant transmission cost and message overhead in WSNs.  
To reduce congestion in WSN, [PERSON] et al. in [49] developed the Congestion-Aware Clustering and Routing (CCR) protocol. This protocol increases the number of packets sent and the lifetime of the WSN while satisfying the QoS requirements. Bandwidth allocation is an effective solution in a network congestion scenario where other applications interfere with high-priority traffic.  
[PERSON] et al. proposed an RPL-based multipath routing mechanism for congestion avoidance called CA-RPL in [61]. They also developed the DELAY ROOT RPL routing method that reduces the average delay of the root node. CA-RPL reduces network congestion by distributing large amounts of traffic among numerous channels. The proposed methodsalso include three additional metrics: the rank of ETX (Anticipated Transmission Count), the selection of the parent using multiple packets, and DELAY ROOT.  
A unique RPL-based objective function called \"congestion-aware objective function (CA-OF)\" was proposed by [PERSON] et al. in [62]. This method works well for high traffic volumes. This formula combines two measurements. The packet is forwarded to the sink node via less congested nodes: 1) buffer occupancy and 2) ETX. Algorithms to reduce congestion in wireless IoT networks are summarized in Table 3.  
A congestion-aware routing protocol to minimize congestion was proposed in [43], and it is based on the survivable path routing protocol. The target of the method is a high-traffic WSN (IoT in healthcare). The signal to interference and noise ratio of the link are used to determine the routing path. The ratio between the minimum remaining energy of the nodes on the path and the total energy consumed on the potential communication path is used to determine the survivability of the path.  
RPL is proposed for limited IoT devices and WSNs [63]. Numerous studies have been conducted to apply RPL in different contexts, including node mobility [38; 64], different traffic patterns [65], forwarding, and multi-casting. The RPL network still provides unusual work that solves the congestion problem [66]. This study extends the web-based CoAP/6 LoWPAN protocol stacks by integrating congestion mitigation functionalities. The congestion mitigation mechanism was proposed in [67]. The Cooja simulator and Contiki OS have not yet been tested with the above work [68].