Energy-Efficient Data Collection Using Mobile Sinks To Minimize Wsn Latency

Abstract

Reliable data collection is a crucial concern in Wireless Sensor Networks (WSNs), as it guarantees prompt transmission of data to the sink node while reducing network delay. The use of mobile sinks for data gathering has been recognized as a successful approach to improving the efficiency and dependability of wireless sensor networks (WSNs). This study examines two novel algorithms for enhancing data collection efficiency via the use of mobile sinks: the Opportunistic Data Collection Algorithm (ODCA) and the QoS-aware Mobile Sink Selection Algorithm (QMSSA). The ODCA utilizes the mobility of sink nodes by using a heuristic approach. It opportunistically collects data from sensor nodes when they are in close vicinity and dynamically adjusts the direction of the sink depending on real-time chances for data collection. ODCA's capacity to adapt enables it to remain efficient even when there are changes in network topology or failures in nodes. The QMSSA prioritizes the preservation of Quality of Service (QoS) by carefully choosing the most suitable mobile sink, taking into account factors such as network load, sink mobility, and energy use. QMSSA improves the overall performance and reliability of the WSN by selecting the best suitable sink. This research showcases notable improvements in data collecting efficiency and network latency via the use of ODCA and QMSSA, hence contributing to the progress of WSN technology.