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The outbreak of coronavirus 2019 (Covid-19) has imposed a worldwide lockdown, changing the way people live and work, and pressuring the healthcare systems in many countries. Contact tracing based on smartphone apps (app-based contact tracing) has emerged as a possible solution to trace contagions and enforce more sustainable and selective quarantines. However, these apps require a very high adoption rate to reach the critical mass for effective contact tracing. As an alternative, network-based contact tracing, which exploits geo-localization in next generation networks (e.g., 5G) can be used by mobile operators (MOs) to passively trace users' mobility and contacts, provided that a targeted localization accuracy of down to one meter can be achieved. To effectively trace contagions, the identities of positive individuals, which are known by governmental authorities (GAs), are also required. Hence, in network-based contact tracing, MOs and GAs must exchange users' privacy-sensitive data, as geo-locations and infection status, to compute the likelihood that an individual has been infected. To address the privacy issues raised by network contact tracing, after presenting an overview of app-based vs. network-based contact tracing systems, we propose a protocol to make network-based systems compliant with stringent privacy requirements. From extensive simulations, we observe that the cost to guarantee privacy (evaluated in terms of data overhead introduced by the protocol) is acceptable. Finally, we elaborate on the advantages of the proposed system (e.g., more efficient monitoring of virus spread), as well as on the open issues that should be solved before its adoption (e.g., extensive research on potential privacy leakage is required).

The future of industrial applications is shaped by intelligent moving IoT devices, such as flying drones, advanced factory robots, and connected vehicles, which may operate (semi-)autonomously. In these challenging scenarios, dynamic radio connectivity at high frequencies, augmented with timely positioning-related information, becomes instrumental to improve communication performance and facilitate efficient computation offloading. Our work reviews the main research challenges and reveals open implementation gaps in IIoT applications that rely on location awareness and multi-connectivity in super high and extremely high frequency bands. It further conducts a rigorous numerical investigation to confirm the potential of precise device localization in the emerging IIoT systems. We focus on positioning- aided benefits made available to multi-connectivity IIoT device operation at 28 GHz, which notably improve data transfer rates, communication latency, and the extent of control overhead. acceptedVersion

Vehicular fog computing extends the fog computing paradigm to conventional vehicular networks. This allows us to support more ubiquitous vehicles, achieve better communication efficiency, and address limitations in conventional vehicular networks in terms of latency, location awareness, and real-time response (typically required in smart traffic control, driving safety applications, entertainment services, and other applications). Such requirements are particularly important in adversarial environments (e.g., urban warfare and battlefields in the Internet of Battlefield Things involving military vehicles). However, there is no one widely accepted definition for vehicular fog computing and use cases. Thus, in this article, we formalize the vehicular fog computing architecture and present a typical use case in vehicular fog computing. Then we discuss several key security and forensic challenges and potential solutions. Refereed/Peer-reviewed

The virtually unlimited available resources and wide range of services provided by the cloud have resulted in the emergence of new cloud-based applications, such as smart grids, smart building control, and virtual reality. These developments, however, have also been accompanied by a problem for delay-sensitive applications that have stringent delay requirements. The current cloud computing paradigm cannot realize the requirements of mobility support, location awareness, and low latency. Hence, to address the problem, an edge computing paradigm that aims to extend the cloud resources and services and enable them to be nearer the edge of an enterprise's network has been introduced. In this article, we highlight the significance of edge computing by providing real-life scenarios that have strict constraint requirements on application response time. From the previous literature, we devise a taxonomy to classify the current research efforts in the domain of edge computing. We also discuss the key requirements that enable edge computing. Finally, current challenges in realizing the vision of edge computing are discussed.

Ambient assisted living (AAL) services that provide support for people to remain in their homes are increasingly being used in healthcare systems around the world. Typically, these ambient assisted living services provide additional information though location-awareness, presence-awareness, and context-awareness capabilities, arising from the prolific use of telecommunications devices including sensors and actuators in the home of the person receiving care. In addition there is a need to provide abstract information, in context, to local and remote stakeholders. There are many different viewing options utilizing converged networks and the resulting explosion in data and information has resulted in a new problem, as these new ambient assisted living services struggle to convey meaningful information to different groups of end users. The article discusses visualization of data from the perspective of the needs of the differing end user groups, and discusses how algorithms are required to contextualize and convey information across location and time. In order to illustrate the issues, current work on nighttime AAL services for people with dementia is described.

The PLASH platform is designed to help location- aware service providers deploy their applications easily so that users can contribute their efforts and location-related data by using the services, which is the main difference from traditional location-aware services. The collective efforts and data that may be generated by humans or sensors (or both) can be used to help solve difficult location awareness problems, such as realtime surface traffic estimation, city panoramas, and social networking analysis. The PLASH platform comprises three layers: communication, data, and service. An LAS application developed on PLASH can exploit the functions provided in each layer by using an application specification language provided by PLASH. In addition, application builders can contribute their mature applications as a service accommodated in the service layer for other application builders to expand and create more sophisticated applications.

Rapid advances in digital technology allow people to have a single wireless device that has multiple functions such as communication, computing, and entertainment. These functions are generally embedded into the devices as add-on hardware components such as sensors, digital cameras, and so on. Currently, the functions operate independent of each other, since there is no unit that controls and coordinates the add-on hardware. However, with the aid of a cognitive engine, CR can take advantage of each component to improve its communications. In this work, location awareness is exploited to improve the wireless communication system design in CR. It is shown that several crucial wireless channel parameters are environment-dependent. In order for CR to relate a corresponding empirical model with an environment, the classification of propagation environments is outlined as well. The methods of characterizing the propagation environment for CR are also discussed. In addition, it is described how CR can carry out all these steps with the aid of a KRS along with RKRL and complete its adaptation cycle. CR networks are also discussed, including disseminating the location awareness information, propagation characteristics, and their effects on the network itself.

Service providers, especially in the mobile entertainment domain, are facing increasing competition. The ability to design, develop, and deploy unique context-aware entertainment services fast and easily as well as the capability to provide intuitive user interfaces becomes essential for market players. Furthermore, today's mobile world is made up of heterogeneous networks accessible via various devices with different characteristics. Progressive users have the desire to utilize the same services and access the same information content on all available devices. At the same time, service providers have to diversify their services in order to remain competitive and attract the various customer segments making up the mass market. We introduce an agent-based serviceware framework to assist service providers in developing innovative services, thus reducing the time to market of the respective applications. The realized serviceware framework offers personalization, location awareness, and the multi-access service platform, a flexible solution for ubiquitous service access. Thus, our solution allows a heterogeneous landscape of end devices to access an application server's mobile services in a multimodal, multilingual, and multimedia-based manner. We describe the utilization of the different modules of the service framework as well as the BerlinTainment application, an entertainment planning system based on the framework.