# CoAR: Congestion-Aware Routing Protocol for Low Power and Lossy Networks for IoT Applications
## 2 Related Works
Attraction zone contains the parents and child of next hop nodes of the focal node in two-hop bases, whereas the repulsion zone contains, the focal node, its parents, and child in one hop basis. It improves the packet reception rate. UDP message is used in order to estimate the buffer in the zones. However, in LLN characteristic, it may not be so obvious a choice, especially for time critical and event-based IoT applications because the focal node always eavesdrops (passive listening) the UDP messages, which may result in the inaccurate buffer calculation. Moreover, the focal node always eavesdrops to the channel, as a result, the radio is always on and therefore depletes the energy. A game theory-based congestion control mechanism has been proposed in [18]. To detect the congestion on parent nodes, it uses the net packet flow rate as a metric which is the difference between the packet generation rate and packet service rate. In the protocol, as soon as the congestion is detected at a node, it broadcasts the congestion notification to its neighboring nodes. On receiving the message, a neighboring node triggers the parent change procedure. To carry out this procedure, the potential game theory method is used. If the congestion cannot be addressed successfully by the parent selection procedure, the parent node chooses a rate adjustment scheme. However, the rate adjustment scheme may drastically decrease the QoS of the network. Therefore, in IoT applications such as media streaming and emergency scenarios, this scheme may bring some negative impacts on desired requirements. The authors proposed a duty cycle-aware congestion control for 6 LoWPAN (DCCC6) protocol in [19]. The protocol controls the congestion using the presence of a radio duty cycle and regulates its operations accordingly. It detects the congestion based on a dynamic buffer. To reduce the congestion, it uses the modified additive increase multiplicative decrease (AIMD) mechanism. When a node detects the congestion, it informs the child nodes contributing to congestion to reduce the transmission rate based on the adjustment scheme. However, such a rate adaptation scheme may not be a desirable solution for our proposed IoT application scenario. A queue utilization based RPL (QU-RPL) has been introduced in [5], which is based on the queue utilization (QU) for load balancing under heavy traffic. It takes the QU of neighboring nodes into consideration during the parent selection process. The QU factor is defined and uses in parent selection process to achieve the traffic load balancing. In addition, QU-RPL performs the queue adjustment to lower the probability of a node being selected as a next hop towards the root when its parent node is severely congested. When a node experiences a certain number of consecutive buffer overflows, the node broadcasts a DODAG information object (DIO) message that contains the congestion information. Upon receiving the congestion information, the node changes its parent that has less buffer utilization and lower hop distance to root. The protocol has been tested in a real testbed network. However, in this protocol, the congestion threshold is static, which may be appropriate for balancing the load in high traffic, but may not be for dynamic traffic or bursty traffic, which is essential in the scope of effective IoT service provisioning. In [20], the authors proposed a game theory-based congestion control framework (GTCCF) for 6 LoWPAN networks. The adopted non-cooperative framework takes into account node priorities and application priorities. GTCCF resolves the congestion problem by adopting a node's sending rate using the Nash Equilibrium concept. Like other traffic control algorithms, GTCCF adjusts the node's sending rate, which is also not appropriate for our proposed scenario. Moreover, during the selection of alternative less congested paths, it increases the control message overhead. The authors proposed a congestion avoidance multipath routing protocol for time-critical applications named CA-RPL in [21].