Abstract:In order to improve clock synchronization precision of the power distribution field network, a power distribution field network with high‐speed power line broadband carrier communication is designed, and a step‐by‐step precision clock synchronization strategy is developed based on modified timing‐sync protocol for sensor networks. In the strategy, the clock of the central node is calibrated in real‐time as the master clock of the field network by the communication master station through the long‐distance commu… Show more
“…Time synchronization is a key requirement in real-time industrial IoT-based systems and other time-critical applications, such as cyber-physical systems [ 1 ], power grids [ 2 ], financial systems [ 3 ], transportation systems [ 4 ], and smart cities security applications [ 5 ]. Even a slight deviation in time reference can induce significant faults in these systems, and therefore, precise and reliable time synchronization is crucial [ 6 , 7 ].…”
Time synchronization is vital for accurate data collection and processing in sensor networks. Sensors in these networks often operate under fluctuating conditions. However, an accurate timekeeping mechanism is critical even in varying network conditions. Consequently, a synchronization method is required in sensor networks to ensure reliable timekeeping for correlating data accurately across the network. In this research, we present a novel dynamic NTP (Network Time Protocol) algorithm that significantly enhances the precision and reliability of the generalized NTP protocol. It incorporates a dynamic mechanism to determine the Round-Trip Time (RTT), which allows accurate timekeeping even in varying network conditions. The proposed approach has been implemented on an FPGA and a comprehensive performance analysis has been made, comparing three distinct NTP methods: dynamic NTP (DNTP), static NTP (SNTP), and GPS-based NTP (GNTP). As a result, key performance metrics such as variance, standard deviation, mean, and median accuracy have been evaluated. Our findings demonstrate that DNTP is markedly superior in dynamic network scenarios, a common characteristic in sensor networks. This adaptability is important for sensors installed in time-critical networks, such as real-time industrial IoTs, where precise and reliable time synchronization is necessary.
“…Time synchronization is a key requirement in real-time industrial IoT-based systems and other time-critical applications, such as cyber-physical systems [ 1 ], power grids [ 2 ], financial systems [ 3 ], transportation systems [ 4 ], and smart cities security applications [ 5 ]. Even a slight deviation in time reference can induce significant faults in these systems, and therefore, precise and reliable time synchronization is crucial [ 6 , 7 ].…”
Time synchronization is vital for accurate data collection and processing in sensor networks. Sensors in these networks often operate under fluctuating conditions. However, an accurate timekeeping mechanism is critical even in varying network conditions. Consequently, a synchronization method is required in sensor networks to ensure reliable timekeeping for correlating data accurately across the network. In this research, we present a novel dynamic NTP (Network Time Protocol) algorithm that significantly enhances the precision and reliability of the generalized NTP protocol. It incorporates a dynamic mechanism to determine the Round-Trip Time (RTT), which allows accurate timekeeping even in varying network conditions. The proposed approach has been implemented on an FPGA and a comprehensive performance analysis has been made, comparing three distinct NTP methods: dynamic NTP (DNTP), static NTP (SNTP), and GPS-based NTP (GNTP). As a result, key performance metrics such as variance, standard deviation, mean, and median accuracy have been evaluated. Our findings demonstrate that DNTP is markedly superior in dynamic network scenarios, a common characteristic in sensor networks. This adaptability is important for sensors installed in time-critical networks, such as real-time industrial IoTs, where precise and reliable time synchronization is necessary.
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