Rapid technological advances have revolutionized the industrial sector. 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). Restricting the definition of IIoT to manufacturing yields another subset of IoT, known as Industry 4.0. IIoT and Industry 4.0 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. Additionally, as industrial big data is 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 4.0. 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.

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.

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.

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.

IoT has been gaining a lot of attention in recent years. In fact, the number of connected devices has already surpassed the total population on Earth. Current developments in various technologies have paved the way for many IoT services that are now being deployed in different sectors. IoT can extend its scope and service provisioning capabilities with the integration of the cloud computing paradigm. Similarly, cloud cannot only access underlying IoT nodes and provide them with cloud services, but can also create further enhanced services based on the data collected from IoT nodes. However, IoT and sensor networks on the ground are often far from the cloud, which is normally accessible via the Internet. Some services require fast response and a great deal of pre-processing and filtering, and may also have security and privacy requirements. For all such cases, middleware, also known as fog, is required between the cloud and IoT devices. We present cloud-IoT integration issues followed by a comparison between fog and cloud computing. We evaluate the performance of fog computing using performance metrics such as processing delay, processing costs, and processing power, and derive the performance gains obtained in comparison to a cloud computing only approach. Finally, we identify some future research directions for fog computing.