All one needs to know about fog computing and related edge computing paradigms: A complete survey

The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey toward the fifth generation of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of multi-access edge computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC’s ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultralow latency and high quality of service due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

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Survey on Multi-Access Edge Computing for Internet of Things Realization

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Клініко-епідеміологічні особливості спалаху кору в м. Суми у 2014 році

With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and humans to bring promising advantages for us. With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of security-critical and time-sensitive data that is being produced by the IoT. In this paper, we first provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences. Next, we provide a taxonomy of research topics in fog computing, and through a comprehensive survey, we summarize and categorize the efforts on fog computing and its related computing paradigms. Finally, we provide challenges and future directions for research in fog computing.

All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey

The development of light detection and ranging, Radar, camera, and other advanced sensor technologies inaugurated a new era in autonomous driving. However, due to the intrinsic limitations of these sensors, autonomous vehicles are prone to making erroneous decisions and causing serious disasters. At this point, networking and communication technologies can greatly make up for sensor deficiencies, and are more reliable, feasible and efficient to promote the information interaction, thereby improving autonomous vehicle’s perception and planning capabilities as well as realizing better vehicle control. This paper surveys the networking and communication technologies in autonomous driving from two aspects: intra- and inter-vehicle. The intra-vehicle network as the basis of realizing autonomous driving connects the on-board electronic parts. The inter-vehicle network is the medium for interaction between vehicles and outside information. In addition, we present the new trends of communication technologies in autonomous driving, as well as investigate the current mainstream verification methods and emphasize the challenges and open issues of networking and communications in autonomous driving.

Networking and Communications in Autonomous Driving: A Survey

Connected vehicle systems form the basis for future features of functions and applications within the automotive domain. In order to allow resource intensive services, cloud offloading and especially Mobile Edge Computing is a promising approach. In this paper, we present a detailed futuristic vehicular scenario -- Electronic Horizon -- and list the challenges. We argue that the resulting challenges are representative of many of the envisioned use-cases of Mobile Edge Computing. We then present how Information-Centric Networking in combination with Mobile Edge Computing has the potential to support such a futuristic scenario. Finally, we present research directions that could enhance the solution space.

https://dl.acm.org/doi/pdf/10.1145/3098208.3098210

Information-Centric Mobile Edge Computing for Connected Vehicle Environments: Challenges and Research Directions

The networking of components, machines and everyday objects is progressing rapidly. This development also affects the automotive industry. Vehicle systems are getting connected with other cars, infrastructure components or cloud servers. This raises the question if the current host-centric communication model of today's networks is ready for networking billions of new devices. The Information-Centric Networking (ICN) paradigm is a promising candidate to solve the issues set by connected vehicles and host-centric communication, for example by providing in-network caching capabilities. However, placing the right content at the right node in-time is a non trivial task. Within this paper, we introduce PeRCeIVE, a PRoactive Caching approach for Icn-based Vehicular ad-hoc nEtworks (VANETs). PeRCeIVE shows that a directed placement of data will improve the performance of the network by distributing the content with a minimal number of replicas one-hop away from the consumer.

PeRCeIVE: Proactive caching in ICN-based VANETs

State of the art automotive software systems presume a static configuration of electronic control units and software components. Assuming that future Driver Assistance Systems (DAS) will deploy dynamically changing software configurations, the authors propose an approach towards an adaptive software and systems architecture for DAS. The paper focuses on systems, which assist the driver while backing up truck and trailer combinations. These systems are characterized by a high degree of distribution as well as a high level of heterogeneity and changeability even at runtime. In order to meet these demands, the authors suggest the usage of service orientation combined with software agents. The functional units of these systems are encapsulated in services which are dynamically orchestrated by the agents whenever the system changes. This paper describes the ideas of this approach using a real world example. It also names and classifies the scenarios of re-configuration. The article concludes with a lookout on the future work within this project.

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An Adaptive Software and Systems Architecture for Driver Assistance Systems based on Service Orientation

The networking of components, machines, and everyday objects is progressing rapidly. Such development also affects the automotive industry. In the future, vehicles will be connected with other vehicles, infrastructure components or cloud servers. This raises the question, whether the current host-centric communication model of today’s networks is ready for networking billions of new devices. In recent years, information-centric networking (ICN) has been identified as a potential paradigm to solve the issues set by connected vehicles. This paper provides a detailed examination of the different available ICN approaches regarding the specific requirements of connected vehicles. While some first publications showed the principal applicability of particular ICN architectures in vehicular ad-hoc networks, a detailed comparison has not been conducted yet. This paper closes the gap by discussing and comparing the available ICN architectures in an automotive context and identifies open research questions in ICN.

A Domain-Specific Comparison of Information-Centric Networking Architectures for Connected Vehicles

Upcoming connected vehicle applications will rely on large amounts of data to provide safety or comfort functionalities Delivering such data, reliably on time is a challenge due to the inherent mobility in connected vehicle environments The Information-Centric Networking (ICN) paradigm is a promising candidate to tackle the challenges of such environments Addressing data by name instead of location, and the resulting capabilities such as in-network caching, make it a good fit for scenarios with a high degree of mobility In this paper, we propose and evaluate an adaptive decentralized prefetching mechanism for ICNs in vehicular scenarios By proactively placing relevant data in caches near to consumers, the overall service quality and delivery rate in the network is improved The algorithm is evaluated using simulations based on a real V2X highway testbed in Austria

Marco Wagner

Papers

Information-Centric Mobile Edge Computing for Connected Vehicle Environments: Challenges and Research Directions

PeRCeIVE: Proactive caching in ICN-based VANETs

An Adaptive Software and Systems Architecture for Driver Assistance Systems based on Service Orientation

A Domain-Specific Comparison of Information-Centric Networking Architectures for Connected Vehicles

ADePt: Adaptive Distributed Content Prefetching for Information-Centric Connected Vehicles