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 securitycritical 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.
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 securitycritical 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.
“…The authors of [14] performed a comprehensive survey of discovery technologies for IoT environments, analyzing and comparing solutions such as multicast DNS (mDNS), multicast CoAP, the Simple Service Discovery Protocol (SSDP), and others. In [15], the authors present the Smart and Power Efficient Node Discovery Protocol (SPEND), a reliable and energy-efficient discovery mechanism for IoT-Fog networking scenarios that leverages the MQTT protocol to keep track of Things, which act like publishers/advertisers in Fig. 4.…”
Smart Cities are among the most dynamic and rapidly evolving modern environments, driven by the development of new technologies and the fast growth of the Internet of Things (IoT), which enable the acquisition and processing of very large amounts of data. However, accessing IoT assets is proving to be a challenge, as neither formal nor de facto standards to discover connected Things have emerged. Services that provide discovery and access capability for IoT resources are in the rise, but they often adopt service-specific interfaces and authorization mechanisms that hinder the development and maintainability of IoT applications. Low flexibility and interoperability become especially problematic during emergency situations, when responders might need to access resources that normally would not be allowed to access. To address these issues, this paper describes MARGOT, a distributed edge computing platform that supports domain-aware and secure discovery of IoT resources in Smart Cities. Experimental results obtained using MARGOT in an emulated network environment show that our platform can effectively reduce discovery latency and bandwidth consumption under the considered use cases and network conditions.
“…The authors propose the adoption of a gateway solution called Future Internet eXchange Point (FIXP) to bridge the different communication protocols. In [21], the authors describe a discovery approach, which makes use of MQTT to keep track of publishers/advertisers (IoT devices) in a IoT-Fog environment. In particular, the authors propose a protocol, namely Smart and Power Efficient Node Discovery Protocol (SPEND) as solution to create a reliable and energy efficiency discovery solution for IoT applications.…”
The Smart City concept tries to inherit the advantages of Internet-of-Things (IoT) into its realm to function alongside the existing legacy systems. One of the most promising aspects of IoT is Edge Computing, which tries to move the computing, traditionally done via a centralized infrastructure like the cloud to the edge of the network. This allows remote deployment of IoT assets closer to the source and application area of information enabling faster response times of action. Smart Cities of future envision using Edge Computing to their advantage for remote and distributed computing. Sieve, Process and Forward (SPF) is an Edge Computing solution for dynamic IoT applications for Smart City scenarios. The military is looking forward to use, as well as develop the SPF platform for its Edge Computing requirements. But currently, the SPF platform does not have the mechanism for remote discovery of edge resources and their management to leverage its potential completely. This paper tries to propose a resource discovery and management architecture and methodology for SPF to support future Human Assistance and Disaster Recovery (HADR) operations in Smart City environments with the vision of enabling interoperability between civilian and military platforms.
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