Cluster-based data aggregation protocol for real-time wireless sensor networks - Cruzada, Carla Jeannine O. (Animo Repository, 2023)
Wireless Sensor Networks (WSNs) are continuously used in different fields of application. As more data is sent through the network, there is a need to propose ways to improve energy consumption, data latency, reduce packet loss, and achieve high data accuracy. Minimizing energy consumption has always been an emphasis in the deployment of WSNs to prolong the lifespan of the network. Minimal data latency and high data accuracy are also essential for efficient data delivery. Data Aggregation is an approach to enhance network lifetime, data accuracy, data latency, and lessen packet loss when data is transmitted across the network. Data gathered in WSNs must be aggregated properly and arrive in time at the gateway as these are usually deployed to collect real-time data. Although different protocols have been developed in improving data aggregation, few have only been implemented in real-time WSNs. This study proposes a two-level cluster-based data aggregation protocol for real-time WSN clusters. The proposed data aggregation protocol is implemented in a testbed scenario adapted from the deployment of the DOST-PCIEERD project entitled “Structural Health Monitoring via Mesh of Tremor Sensors” and was evaluated using metrics that cover power consumption, packet transmissions between the sensor nodes and cluster head, percent of aggregation, total datapoints and the resources identified for the protocol to operate properly. Overall, the protocol can significantly lessen the amount of data points to be sent to the sink wherein a minimum of 50% of the data points are aggregated for accelerometer data while 40% for temperature data. However, using it will only be beneficial for temperature data as there was a significant decrease in the total number of data points transmitted that ranged from 28% up to 53% when it was applied to accelerometer data as compared to the version that did not use the protocol. As such, the network can also expect a decrease in congestion when the aggregation protocol is applied to temperature data as it results in a lower number of packets transmitted. On the other hand, applying the protocol using accelerometer data resulted in a higher number of packet transmissions, which made the network more congested. Additionally, the protocol was able to retain more original data when used in temperature data at 51% as compared to accelerometer data at 33%. There were also no observable instances of packets being lost during transmissions of the SNs and the CH as the protocol utilized TCP. Additionally, Raspberry Pi’s used for clients drew in more power at an additional range of 0.25 to 0.44 Watts when utilizing the protocol. Overall, the protocol is functional, and its development lays out a platform for future studies to further investigate its performance. Keywords: Wireless Sensor Networks, WSN, data aggregation, cluster-based, energy consumption, packet loss, number of transmissions, real-time, testbed, Structural Health Monitoring via Mesh of Tremor Sensors, meSHM