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Fault tolerant spatio-temporal data monitoring applied on drone-system in cyber-physical systems
- Alternative Title
- Kwanghoon Choi
- Author(s)
- 최광훈
- Alternative Author(s)
- Kwanghoon Choi
- Advisor
- 김재훈
- Department
- 일반대학원 컴퓨터공학과
- Publisher
- The Graduate School, Ajou University
- Publication Year
- 2019-02
- Language
- eng
- Alternative Abstract
- Recently, the industry of drone systems has come into the spotlight because a new potential market has been revealed. As considerable number of drones are deployed worldwide, they can be used in many applications providing a broad range of services such as monitoring the surrounding environment, delivering services, in farming, and in rescue activities from disasters and accidents. This expansion is fostering the development of a comprehensive approach, including the construction of general systems such as cyber-physical systems and IoT middleware platforms. In comparison with the quantitative aspects of the drone industry, we still have many issues to solve and improve such as privacy protection, human safety, improvement of resources, and especially, power consumption and efficiency. To overcome these problems, the systems have to generate an efficient and easy-to-follow path, able to dynamically adjust to new situations. Thus, we propose an ON/OFFLINE path planning algorithm and evaluate the results of a simulation on a DroneKit with SITL. The ONLINE and OFFLINE path-planning algorithm is applied to discover a path to the destination under a changeable situation, and it is simulated on a real-life map, which includes a restricted area. Cost effective schemes are essential in cyber-physical system to gathering a huge amount of data from physical system in real-time. In general, sensor networks monitor the physical system and transfer the data to cyber system which analyzes the data and provides many kinds of useful services for users and controls physical system. Sensors, as elements of ubiquitous sensor networks, have very limited resources (power capacity, processing power, and networking capability). Therefore, in the absence of energy efficient mechanisms for ubiquitous sensor networks, the network life time will be reduced. In this paper, we present a cost effective monitoring scheme for cyber-physical system platform using spatio-temporal model. Our proposed model combines space and time domains. Sensor data is sent only when data is changed in space and time domains. If the data is not changed in any domain then the previous data (time domain) or neighboring data (space domain) is used without additional communication cost. We also analyze and compare cost between periodic and aperiodic monitoring model. Using the analysis, we can choose the proper model (periodic or aperiodic) according to cyber-physical system parameters. This study proposes platform technology to overcome defects by performing reliable work using spatio-temporal cost model and drone system to collect and monitor data in the surrounding environment or specific area. For reliable utilization of the data, a method of retrieving and reusing the most cost-effective data based on temporal, spatial, and spatio-temporal methods when data of a specific node at the present time is inaccessible is taken. In addition, we implemented a system that collects essential data by using drone system for the purpose of collecting data which can not be physically accessed due to a network defect, or to reduce the cost or extend the resource life of the sensor network.
- Fulltext
- Appears in Collections:
- Graduate School of Ajou University > Department of Computer Engineering > 4. Theses(Ph.D)
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