With the recent development of big data technology that collects and analyzes various data,the technology that continuously collects and analyzes the observed data is also drawing attention.Moreover,its importance is ...With the recent development of big data technology that collects and analyzes various data,the technology that continuously collects and analyzes the observed data is also drawing attention.Moreover,its importance is growing in data collection in areas where people cannot access.In general,it is not easy to properly deploy IoT wireless devices for data collection in these areas,and it is also inappropriate to use general wheel-based mobile devices for relocation.Recently,researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions.The majority of studies,however,so far have unrealistic assumptions that all IoT devices know the overall state of the network and the current state of each device.Moreover,various physical terrain environments,such as coarse gravel and sand,can change from time to time,and it is impossible for all devices to recognize these changes in real-time.In this paper,with the migration success rate of IoT hopping devices being relocated,the method of estimating the varying environment is proposed.This method can actively reflect the changing environment in real-time and is a realistic distributed environment-based relocation protocol on behalf of non-realistic,theory-based relocation protocols.Also,one of the significant contributions of this paper is to evaluate its performance using the OMNeT++simulation tool for the first time in the world to reflect actual physical environmental conditions.Compared to previous studies,the proposed protocol was able to actively reflect the state of the surrounding environment,which resulted in improved migration success rates and higher energy efficiency.展开更多
基金This work was supported by Research Assistance Program(2019)in the Incheon National University and the National Research Foundation of Korea(NRF)grant funded by the Ministry of Science,ICT&Future Planning(No.NRF-2019R1G1A1007832).
文摘With the recent development of big data technology that collects and analyzes various data,the technology that continuously collects and analyzes the observed data is also drawing attention.Moreover,its importance is growing in data collection in areas where people cannot access.In general,it is not easy to properly deploy IoT wireless devices for data collection in these areas,and it is also inappropriate to use general wheel-based mobile devices for relocation.Recently,researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions.The majority of studies,however,so far have unrealistic assumptions that all IoT devices know the overall state of the network and the current state of each device.Moreover,various physical terrain environments,such as coarse gravel and sand,can change from time to time,and it is impossible for all devices to recognize these changes in real-time.In this paper,with the migration success rate of IoT hopping devices being relocated,the method of estimating the varying environment is proposed.This method can actively reflect the changing environment in real-time and is a realistic distributed environment-based relocation protocol on behalf of non-realistic,theory-based relocation protocols.Also,one of the significant contributions of this paper is to evaluate its performance using the OMNeT++simulation tool for the first time in the world to reflect actual physical environmental conditions.Compared to previous studies,the proposed protocol was able to actively reflect the state of the surrounding environment,which resulted in improved migration success rates and higher energy efficiency.
