Edge Computing: The Computing Infrastructure for the Smart Mega-cities of the Future

Future mega-cities are expected to be smart and integrate sensing, wireless communications, and artificial intelligence to offer innovative services to their citizens. This development has the potential to generate massive amounts of data which need to be processed in a cost-effective, scalable, and continuous manner. Fulfilling this requirement requires solutions that can offer the necessary computational infrastructure while meeting the constraints of cities (e.g., budget and energy). This paper contributes a research vision for using edge computing to deliver the computing infrastructure for emerging smart mega-cities. We present use cases, identify key requirements, and reflect on the current state-of-the-art. We also address edge server placements, which is a key challenge for the adoption of edge computing, demonstrating how it is needed to determine a scalable and effective deployment of edge nodes for satisfying the processing needs of smart mega-cities.Peer reviewe

Edge Computing : The Computing Infrastructure for the Smart Megacities of the Future

Future mega-cities are expected to be smart and integrate sensing, wireless communications, and artificial intelligence to offer innovative services to their citizens. This development has the potential to generate massive amounts of data which need to be processed in a cost-effective, scalable, and continuous manner. Fulfilling this requirement requires solutions that can offer the necessary computational infrastructure while meeting the constraints of cities (e.g., budget and energy). This paper contributes a research vision for using edge computing to deliver the computing infrastructure for emerging smart mega-cities. We present use cases, identify key requirements, and reflect on the current state-of-the-art. We also address edge server placements, which is a key challenge for the adoption of edge computing, demonstrating how it is needed to determine a scalable and effective deployment of edge nodes for satisfying the processing needs of smart mega-cities.Peer reviewe

Privacy-Aware Blockchain Innovation for 6G: Challenges and Opportunities

6G Wireless Summit, Levi, Finland, 17-20 March 20206G wireless networks improve on 5G by further increasing reliability, speeding up the networks and increasing the available bandwidth. These evolutionary enhancements, together with a number of evolutionary improvements such as high precision 3D localization, ultra-high reliability and extreme mobility, introduce a new generation of 6G-native applications. Such application can be based on, for example, distributed, ubiquitous Artificial Intelligence (AI) and ultra-reliable, low-latency Internet of Things (IoT). Along with the enhanced connectivity and novel applications, privacy and security of the networks and the applications must be ensured. Distributed ledger technologies such as blockchain provide one solution for application security and privacy, but introduce their own set of security and privacy risks. In this work, we discuss the opportunities and challenges related to blockchain usage in 6G, and map out possible directions for overtaking the challenges.Science Foundation IrelandInsight Research Centr

Digital Twins for Smart Spaces - Beyond IoT Analytics

Smart spaces, physical spaces that are integrated with sensor-enabled IoT devices, are a powerful paradigm for optimizing the operations of the space and improving its quality for the occupants. Managing the applications and services running in the space is a complex task as the operations of the devices and services are dependent on the physical characteristics of the space, the occupants of the space, and the technologies that are being integrated. Digital twinning, the combination of physical representations with a virtual counterpart, is a potential technology for facilitating the management of smart space devices and services. While digital twins are increasingly adopted in industry, their use in everyday environments remains low due to difficulties in creating and linking the virtual representation with the physical environment. In this paper, we propose our vision for the adoption of digital twinning as a pathway to improve the functions of smart spaces. We derive a generic reference architecture that comprises four layers, covering the physical space, the sensing infrastructure, the network interfaces, and the underlying computational infrastructure. Next, we identify and address key requirements for the uptake of digital twins in smart space and assess their benefits using the ascendancy model of business analytics. Finally, to demonstrate the practicality of digital twinning, we present a proof-of-concept digital twin for the TellUs smart space at the University of Oulu in Finland and use it to highlight the potential benefits of different ascendancy levels.Peer reviewe

Privacy-aware blockchain innovation for 6G:challenges and opportunities

Abstract 6G wireless networks improve on 5G by further increasing reliability, speeding up the networks and increasing the available bandwidth. These evolutionary enhancements, together with a number of revolutionary improvements such as high-precision 3D localization, ultra-high reliability and extreme mobility, introduce a new generation of 6G-native applications. Such application can be based on, for example, distributed, ubiquitous Artificial Intelligence (AI) and ultra-reliable, low-latency Internet of Things (IoT). Along with the enhanced connectivity and novel applications, privacy and security of the networks and the applications must be ensured. Distributed ledger technologies such as blockchain provide one solution for application security and privacy, but introduce their own set of security and privacy risks. In this work, we discuss the opportunities and challenges related to blockchain usage in 6G, and map out possible directions for overtaking the challenges

Revealing reliable information from taxi traces:from raw data to information discovery

Abstract In this paper we present procedures for processing raw data collected with moving vehicles and for fusing this data with digital map data. The goal is to have a better understanding of the city traffic via quantitative research on collected taxi data in relation to digital map properties. Map attributes are provided by Digiroad, which is a database of Finnish road and street network. We define methods to clean up data that has been collected with taxis equipped with on-board vehicle tracking devices from real customer service situations. Consequently, the driving behavior may be inconsistent and sensor data can be limited and contain errors. We explain procedures of preparing data; filtering the most obvious errors from the data set, map-matching moving object data, and fetching map attributes along the routes of the moving vehicles. The fetched properties, as well as other measurement data, are used for deriving statistics and illustrations to study driving behavior in downtown Oulu, Finland