Search

The concept of fixed infrastructures capable of fulfilling the requirements of moving devices in terms of connectivity and reliability has been the optimal solution for the past few decades. Today, such a solution is no longer feasible in the Internet of Things (IoT) era. All things are now connected, and a significant number of them are mobile, hence leading to connectivity and reliability issues. Connected and autonomous vehicles, in addition to more contemporary flying and moving devices such as unmanned aerial vehicles (UAVs) and IoT devices, will play a significant role in next-generation networks (NGNs). Node-to-node communication will also play a key role in NGNs and will provide alternative solutions toward connectivity in many complex environments for applications such as smart transportation. With that said, today's wide availability of smart moving devices provides a wider set of alternatives to autonomy for NGNs. In this article, we discuss some of the existing solutions that use connected vehicles, UAVs, and other moving intelligent devices to not only provide connectivity support, but also perform on-location data collection, anal-ysis, and decision making to enable the management of moving NGNs for intelligent services and applications. We envision a solution that is capa-ble of adapting generalized and decentralized learning on mobile devices, such as federated learning, with the advances in deep learning to support the autonomy and configurability aspects of moving NGNs. [ABSTRACT FROM AUTHOR]

The Fifth Generation (5G) communication technology has paved the way for intelligent and diversified Internet of Connected Vehicles (IoCV) services that meet stringent Quality of Service (QoS) requirements. Both Artificial Intelligence (AI) and Blockchain are playing and will continue to play an imperative role in providing secure and decentralized resource sharing to solve complex and time-sensitive problems at the edge. The integration of both those techniques will enhance the performance of smart vehicular services, especially in beyond 5G (B5G) networks. Ensuring secure transactions in complex autonomous network architectures is an immense challenge. This article addresses computational, storage, connectivity and intelligence concerns using a collaborative approach to engage multiple Internet of Things (IoT) nodes such as connected- vehicles, drones and mobile devices for the provisioning of QoS-optimal complex service compositions in autonomous mobile networks. Continuous and fast compositions emerge using decentralized decisions and interactions with diversified neighboring nodes with the aid of reinforcement learning. Blockchain is used to ensure that nodes interact with each other verifiably and record transactions without the need for trusted intermediaries. We assess whether having an AI-enabled blockchain collaborative composition solution improves service availability and delivery of smart city vehicular services. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, which spread rapidly in late 2019, has revealed that the use of computing and communication technologies provides significant aid in preventing, controlling, and combating infectious diseases. With the ongoing research in next-generation networking (NGN), the use of secure and reliable communication and networking is of utmost importance when dealing with users' health records and other sensitive information. Through the adaptation of artificial-intelligence-enabled NGN, the shape of healthcare systems can be altered to achieve smart and secure healthcare capable of coping with epidemics that may emerge at any given moment. In this article, we envision a cooperative and distributed healthcare framework that relies on state-of-the-art computing, communication, and intelligence capabilities, namely, federated learning, mobile edge computing, and blockchain, to enable epidemic (or suspicious infectious disease) discovery, remote monitoring, and fast health authority response. The introduced framework can also enable secure medical data exchange at the edge and between different health entities. This technique, coupled with the low latency and high bandwidth functionality of 5G and beyond networks, would enable mass surveillance, monitoring, and analysis to occur at the edge. Challenges, issues, and design guidelines are also discussed in this article with highlights on some trending solutions. [ABSTRACT FROM AUTHOR]

The global economy is experiencing significant business growth leading to increasing demands for energy. Global energy consumption increased by 2.1 percent in 2017, and according to the 2019 U.S. Energy Information Administration (EIA) reports, the expected energy growth in Asia will reach 50 percent by 2050. Since it is unlikely that these demands will be met using conventional energy systems, the world is moving toward sustainable renewable energy systems (RESs) that are supported by cyberphysical technologies. Additionally, climate change is putting more pressure on governments to reduce their dependency on conventional energy resources and invest more in sustainable renewable energies. The shift from conventional energy sources to renewables is clear, as revealed in 2018 where 30 percent of the U.K. gross electricity consumption was generated by RES (according to the Green Match report on Renewable Energy in the United Kingdom). This transformation has led to the emergence of prosumers (i.e., producers and consumers) capable of both generating and consuming energy. Many households and buildings are now equipped with solar panels that can contribute to the overall energy needs. Power systems need to adapt to renewable energy to provide more efficient and sustainable operations. As such, the concept of smart grid needs to be promoted and looked at more closely in the research and development fields to support such sustainable power systems and energy solutions. [ABSTRACT FROM AUTHOR]

Fog-to-fog communication has been introduced to deliver services to clients with minimal reliance on the cloud through resource and capability sharing of cooperative fogs. Current solutions assume full cooperation among the fogs to deliver simple and composite services. Realistically, each fog might belong to a different network operator or service provider and thus will not participate in any form of collaboration unless self-monetary profit is incurred. In this paper, we introduce a fog collaboration approach for simple and complex multimedia service delivery to cloud subscribers while achieving shared profit gains for the cooperating fogs. The proposed work dynamically creates short-term service-level agreements (SLAs) offered to cloud subscribers for service delivery while maximizing user satisfaction and fog profit gains. The solution provides a learning mechanism that relies on online and offline simulation results to build guaranteed workflows for new service requests. The configuration parameters of the short-term SLAs are obtained using a modified tabu-based search mechanism that uses previous solutions when selecting new optimal choices. Performance evaluation results demonstrate significant gains in terms of service delivery success rate, service quality, reduced power consumption for fog and cloud datacenters, and increased fog profits. [ABSTRACT FROM AUTHOR]