Fog computing extends the cloud computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are 1) low latency and location awareness, 2) widespread geographical distribution, 3) mobility, 4) very large number of nodes, 5) predominant role of wireless access, 6) strong presence of streaming and real time applications, and 7) heterogeneity. In this chapter, the authors argue that the above characteristics make the Fog the appropriate platform for a number of critical internet of things (IoT) services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).

Fog Computing and Its Role in the Internet of Things

http://wpage.unina.it/valerio.persico/pubs/CloudIoT_FGCS.pdf

Integration of Cloud computing and Internet of Things

Multi-access edge computing (MEC) is an emerging ecosystem, which aims at converging telecommunication and IT services, providing a cloud computing platform at the edge of the radio access network MEC offers storage and computational resources at the edge, reducing latency for mobile end users and utilizing more efficiently the mobile backhaul and core networks This paper introduces a survey on MEC and focuses on the fundamental key enabling technologies It elaborates MEC orchestration considering both individual services and a network of MEC platforms supporting mobility, bringing light into the different orchestration deployment options In addition, this paper analyzes the MEC reference architecture and main deployment scenarios, which offer multi-tenancy support for application developers, content providers, and third parties Finally, this paper overviews the current standardization activities and elaborates further on open research challenges

/pdf/on-multi-access-edge-computing-a-survey-of-the-emerging-5g-q09cwte3qi.pdf

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

On blockchain and its integration with IoT. Challenges and opportunities

Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges

With the increasing applications in the domains of ubiquitous and context-aware computing, Internet of Things (IoT) are gaining importance. In IoTs, literally anything can be part of it, whether it is sensor nodes or dumb objects, so very diverse types of services can be produced. In this regard, resource management, service creation, service management, service discovery, data storage, and power management would require much better infrastructure and sophisticated mechanism. The amount of data IoTs are going to generate would not be possible for standalone power-constrained IoTs to handle. Cloud computing comes into play here. Integration of IoTs with cloud computing, termed as Cloud of Things (CoT) can help achieve the goals of envisioned IoT and future Internet. This IoT-Cloud computing integration is not straight-forward. It involves many challenges. One of those challenges is data trimming. Because unnecessary communication not only burdens the core network, but also the data center in the cloud. For this purpose, data can be preprocessed and trimmed before sending to the cloud. This can be done through a Smart Gateway, accompanied with a Smart Network or Fog Computing. In this paper, we have discussed this concept in detail and present the architecture of Smart Gateway with Fog Computing. We have tested this concept on the basis of Upload Delay, Synchronization Delay, Jitter, Bulk-data Upload Delay, and Bulk-data Synchronization Delay.

/pdf/fog-computing-and-smart-gateway-based-communication-for-3327fed4g1.pdf

Fog Computing and Smart Gateway Based Communication for Cloud of Things

Rapid technological advances have revolutionized the industrial sector These advances range from automation of industrial processes to autonomous industrial processes, where a human input is not required Internet of Things (IoT), which has emerged a few years ago, has been embraced by industry, resulting in what is known as the Industrial Internet of Things (IIoT) IIoT refers to making industrial processes and entities part of the Internet Restricting the definition of IIoT to manufacturing yields another subset of IoT, known as Industry 40 IIoT and Industry 40, will consist of sensor networks, actuators, robots, machines, appliances, business processes, and personnel Hence, a lot of data of diverse nature would be generated The industrial process requires most of the tasks to be performed locally because of delay and security requirements and structured data to be communicated over the Internet to web services and the cloud To achieve this task, middleware support is required between the industrial environment and the cloud/web services In this context, fog is a potential middleware that can be very useful for different industrial scenarios Fog can provide local processing support with acceptable latency to actuators and robots in a manufacturing industry Additionally, as industrial big data are often unstructured, it can be trimmed and refined by the fog locally, before sending it to the cloud We present an architectural overview of IIoT and Industry 40 We discuss how fog can provide local computing support in the IIoT environment and the core elements and building blocks of IIoT We also present a few interesting prospective use cases of IIoT Finally, we discuss some emerging research challenges related to IIoT

Deploying Fog Computing in Industrial Internet of Things and Industry 4.0

With the trend going on in ubiquitous computing, everything is going to be connected to the Internet and its data will be used for various progressive purposes, creating not only information from it, but also, knowledge and even wisdom. Internet of Things (IoT) becoming so pervasive that it is becoming important to integrate it with cloud computing because of the amount of data IoT's could generate and their requirement to have the privilege of virtual resources utilization and storage capacity, but also, to make it possible to create more usefulness from the data generated by IoT's and develop smart applications for the users. This IoT and cloud computing integration is referred to as Cloud of Things in this paper. IoT's and cloud computing integration is not that simple and bears some key issues. Those key issues along with their respective potential solutions have been highlighted in this paper.

Cloud of Things: Integrating Internet of Things and cloud computing and the issues involved

Pervasive and ubiquitous computing services have recently been under focus of not only the research community, but developers as well. Prevailing wireless sensor networks (WSNs), Internet of Things (IoT), and healthcare related services have made it difficult to handle all the data in an efficient and effective way and create more useful services. Different devices generate different types of data with different frequencies. Therefore, amalgamation of cloud computing with IoTs, termed as Cloud of Things (CoT) has recently been under discussion in research arena. CoT provides ease of management for the growing media content and other data. Besides this, features like: ubiquitous access, service creation, service discovery, and resource provisioning play a significant role, which comes with CoT. Emergency, healthcare, and latency sensitive services require real-time response. Also, it is necessary to decide what type of data is to be uploaded in the cloud, without burdening the core network and the cloud. For this purpose, Fog computing plays an important role. Fog resides between underlying IoTs and the cloud. Its purpose is to manage resources, perform data filtration, preprocessing, and security measures. For this purpose, Fog requires an effective and efficient resource management framework for IoTs, which we provide in this paper. Our model covers the issues of resource prediction, customer type based resource estimation and reservation, advance reservation, and pricing for new and existing IoT customers, on the basis of their characteristics. The implementation was done using Java, while the model was evaluated using CloudSim toolkit. The results and discussion show the validity and performance of our system.

Mohammad Aazam

Papers

Fog Computing and Smart Gateway Based Communication for Cloud of Things

Deploying Fog Computing in Industrial Internet of Things and Industry 4.0

Cloud of Things: Integrating Internet of Things and cloud computing and the issues involved

Fog Computing Micro Datacenter Based Dynamic Resource Estimation and Pricing Model for IoT

Offloading in fog computing for IoT: Review, enabling technologies, and research opportunities