DISTRIBUTED SENSOR SCHEDULING METHOD BASED ON EUCLIDEAN DISTANCE FOR LOCAL NETWORK IN IoT AND DEVICE HAVING SAME APPLIED THERETO

摘要

The present invention provides a distributed sensor scheduling technique based on Euclidean distance (referred to as DSS-ED) for IoT local networks. In order to support various IoT applications, the DSS-ED comprehensively considers characteristics of various variables to adjust states of individual sensor devices. The purpose of the DSS-ED is to maximize utilization of limited network capacities of IoT local networks while extending life of networks. Therefore, in the DSS-ED, each sensor device calculates Euclidean distance between a measured variable and an ideal value and then, adaptively determines a state by comparing the Euclidean distance with a distance from a neighboring router. To evaluate performances of the DSS-ED and compare performance of the DSS-ED with performance of LRTCP, the present invention performs an experiment simulation in an IEEE 802.15.4 network model. The result shows that the DSS-ED has a process capacity of 11.1% higher than the LRTCP because link quality between neighbors and a distance from a synchronization are additionally considered. In addition, the DSS-ED increases link quality of a sensor device in an activated state unlike the LRTCP, so an idle time of a sensor device is increased to attain energy consumption of 1.2% lower than the LRTCP.;COPYRIGHT KIPO 2019