## 4 Partition Aware-RPL Protocol Overview  
In this section, we present our proposed algorithm, called PA-RPL, which stands for Partition Aware-RPL [14]. In order to emphasize the difference of PA-RPL with the standard RPL, we consider a typical smart farm, equipped with a set of sensors/actuators, uniformly distributed over its surface, aiming at ensuring its monitoring. At first, we show the DODAG built by the application of the standard RPL. We then, move to our proposal, PA-RPL, and show how it differs from the standard RPL.  
Our considered farmland is rectangular (see Figure 2), where one or more types of crops are implanted. Note that the rectangular shape of the farmland represents an arbitrary choice, corresponding to a use-case scenario. Thus, the present discussion remains valid for any different shape without loss of generality. This land is divided into several parcels, each of which is intended to hold simultaneously a single or different kinds of crop (i.e., tomatoes, potatoes, carrots, etc.).  
Throughout the farmland, IP-enabled wireless sensor/actuator nodes are uniformly distributed to monitor the cultivation. This includes the collection of data (such as the temperature or soil moisture), and the control of the irrigation and fertilization processes, etc. The start-up of the PA-RPL protocol follows almost the same steps as that of the RPL protocol. However, in PA-RPL it is necessary to pre-configure each node in order to make it know its position/adherence to a particular parcel.  
Figure 2: A farmland partitioning example: 5 parcels with randomly spread nodes.  
Information about the specific node partition can be obtained and/or simply configured in the node during deployment. This configuration can be easily done at the time of deployment by inserting in the flash memory of each node a small file containing the location of the node. Alternatively, over-the-air programming techniques can be used to provide each node with this information after deployment. A third option would be to disseminate the information in the network by flooding: the sink node floods such information in the network at the very beginning of the deployment. Each node receiving a message about itself keeps the position/color information and use it to build the DODAG as described in the rest of this section.  
In our simulation, once a node knows its partition (or parcel), it is assigned a color that is specific for its parcel. In the example of Figure 2, there are five parcels having five respective colors for their respective nodes. The sink is assigned a sixth color that is different from the others, avoiding considering it as a member of any particular parcel.  
The application of RPL would result in a structure similar to the one depicted in Figure 3. Recall that this DODAG is incrementally created/built based on an objective function (OF) to be satisfied. For the standard RPL, the physical land partitioning, according to crops, is totally transparent to the used OF, and thus, the built DODAG is completely independent from it. Of course, all communications are then driven by this tree-like structure. Adversely, PA-RPL aims at taking this physical partitioning into account when building the DODAG. This will be further discussed in the next two subsections.