# A Cooja-Based Tool for Coverage and Lifetime Evaluation in an In-Building Sensor Network+
## 5 Simulation Set-Up  
In the WSN-Maintain simulation with Cooja, we use datasets from five sensor network deployments: a data centre room at the Informatics Institute at Federal Fluminense University in 2013 (TMON) [20], the ground floor and first floor of the Nimbus building at the Cork Institute of Technology in 2013 (CIT-1 and CIT-G) and the second floor and third floor of the Strata Conference building in New York that was held in 2012 (NY-2 and NY-3) [21]. We chose these deployments as we require dense networks for our simulation, where some rooms must have multiple sensor nodes, as to be expected in large buildings. Unless otherwise specified, the five datasets that are used in our simulation consist of temperature sensor reading for 24-hour periods. The floor plan of the buildings and the sensor node locations that are used in the simulation are depicted in Figures 4-8. Figure 4: WSN deployment in a data centre room at the Informatics Institute at Federal Fluminense University (TMON). Figure 5: WSN deployment on the first floor of the Cork Institute of Technology (CIT-1). Figure 6: WSN deployment on the ground floor of the Cork Institute of Technology (CIT-G). Figure 7: WSN deployment on the second floor of the Strata Conference in New York (NY-2). The information for the five WSN deployments is summarised in Table 5. These deployments have different numbers of sensor nodes. Note that some rooms do not have sensor nodes, and so, they are not considered in the performance calculation. The simulation parameters are given in Table 6. We assume all sensor nodes communicate using the highest power level. For Tmote Sky's CC2420 radio, the output power is 0 dBm (Table 1). To have sufficient sensing coverage, we use 7.5 m as the sensing range for all sensor nodes in the CIT-1, CIT-G, NY-2 and NY-3 deployments. However, for the one-room TMON deployment, a 2.5-metre sensing range is sufficient to have the room covered. TMON needs higher accuracy because of the nature of the application, _i.e.,_ data centre monitoring. We also assume that all sensor nodes have the same initial energy. We choose a small amount of energy, _i.e.,_ one Joule for TMON, five Joules for CIT-1 and CIT-G and four Joules for NY-2 and NY-3. This is a pragmatic choice that allows us to run experiments that can produce results within practical time periods, since in reality, sensor networks are expected to have sufficient power for operation over several months. For the network connectivity, we use directed graph radio medium because for an in-building scenario, we take into account the effects of obstacles (walls and doors) between the transmitter and the receiver. For the sake of simplicity, we use the binary detection model, and all rooms have the same coverage requirements, _i.e.,_\(k\)=1. To have sufficient coverage redundancies, we use 75% local coverage threshold, as the deployments are not dense enough, except the TMON deployment, where we use 95%. For the reading correlation, a node is redundant if the difference between the predicted and its actual temperature readings is below 0.1 \({}^{\circ}\)C. This value is in the range of Tmote Sky's temperature sensor accuracy [22]. For two dimensions, we use the correlation's power parameter \(m=2\). Our simulation utilises the collection tree protocol (CTP) [23] implemented in Contiki and the duty-cycling Contiki MAC protocol [24].