# Efficient Communication Model for a Smart Parking System with Multiple Data Consumers
## 4 Efficient Communication Model for an SPS with Multiple Data Consumers  
IoT applications implemented with low-power personal area networks have a variety of requirements such as low power consumption, low latency, less traffic overload and high reliability [41]. In order to satisfy these requirements, an efficient communication model must:  
* Provide reliable data collection in a large mesh network;
* Minimize the power consumption of the battery-operated IoT devices;
* Be quicker in collating and furnishing the data to consumer devices;
* Have a data format that compresses the volume of data.  
A parking lot application that generates parking availability data has to forge effective communication paths between IoT devices that generate occupancy data, devices that collate the occupancy data and devices that consume occupancy data. The performance of a multi-hop network depends on the number of hops between the source and the destination. When data are transmitted through a minimal number of nodes, the latency and power consumption are optimal. On this basis, five different communication models are evaluated for implementing an SPS with multiple data consumers:  
1. Border router with a single data collator at the perimeter of the parking lot;
2. Border router with a single data collator at the center of the parking lot;
3. Border router with multiple data collators distributed across the parking lot;
4. Border router with four data collators at the center of the parking lot;
5. Border router with four data collators at the center and each forwarder in the mesh aggregates occupancy data.  
A border router (BR) facilitates connections between the mesh devices and Internet backbone. A BR aggregates routes to all mesh nodes and utilizes the same to connect them with hosts from other IP-based networks [6]. The wireless connection between all these entities forms the communication ecosystem of the SPS. In order to realize the goals of an efficient communication model, several aspects such as the position of border router and data collators, radio duty cycling, and data formats are considered in this work. Figure 6a-d represent a class of communication model where IoT devices simply forwards data toward the data collator. However, the position of the data collators vary among them. Except for the third model in Figure 6c, the BR and data collators are neighbors. The third model has split the entire network into four quadrants and has one data collator at the center of each quadrant. This places the data collator nested among the data producers. In contrast, Figure 6e shows a model where forwarders accept data from their children nodes, aggregate and then send out a single data packet with the consolidated occupancy data.  
Figure 6: Flow of occupancy data (**a**) BR with one data collator at top. (**b**) BR with one data collator in middle (**c**) BR with four distributed data collators (**d**) BR with four data collators near BR. (**e**) Routers aggregate occupancy data at each hop.  
The past research work on RPL's performance provides several pieces of vital information, including ETX for best link assessment, the significance of radio power consumption, duty cycling for reducing energy consumption, the relation between topology and performance and load balancing with multiple sinks. As multiple sinks mean more border routers, it involves high control overhead in maintaining more than one instance of RPL. Instead, this paper explores several alternate aspects such as multiple data collators, their positions, relative positions with data consumers, duty cycles of IoT devices, and data exchange format for arriving at a simple and efficient communication model.