Multi-Stage Graph-Based Approach for Managing Self-Organized IoT Networks
Abstract
The rapid development of smart devices and wireless sensors is having a major impact on many scientific disciplines as well as on many real world applications. An essential aspect of deploying sensors and devices in various application domains is to be connected to the Internet forming the so called Internet of Things (IoT). Having access to the massive public data and the various sources on the Internet is critical to the cognitive functionality of such Things. Connecting the devices/sensors to each other in a given environment is highly desirable as well since their functionality in most cases do overlap. Hence, there is a need for protocols to manage wireless devices in a seamless, organic and adaptive way; resulting in self-organized wireless networks. Current literature is rich with methods developed to manage self-organized networks of mostly homogeneous sensors in large fields or in remote areas such as glaciers, seafloors or agriculture fields. The focus of this project is to develop new methods for efficiently managing such large-scale networks composed of heterogeneous wireless IoT sensors/devices in urban environments such as homes, hospitals and public institutions.
Multi-Stage Graph-Based Approach for Managing Self-Organized IoT Networks
UNO Criss Library, Room 231
The rapid development of smart devices and wireless sensors is having a major impact on many scientific disciplines as well as on many real world applications. An essential aspect of deploying sensors and devices in various application domains is to be connected to the Internet forming the so called Internet of Things (IoT). Having access to the massive public data and the various sources on the Internet is critical to the cognitive functionality of such Things. Connecting the devices/sensors to each other in a given environment is highly desirable as well since their functionality in most cases do overlap. Hence, there is a need for protocols to manage wireless devices in a seamless, organic and adaptive way; resulting in self-organized wireless networks. Current literature is rich with methods developed to manage self-organized networks of mostly homogeneous sensors in large fields or in remote areas such as glaciers, seafloors or agriculture fields. The focus of this project is to develop new methods for efficiently managing such large-scale networks composed of heterogeneous wireless IoT sensors/devices in urban environments such as homes, hospitals and public institutions.