# Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges
## 5 Challenges with Solutions  
In general, there are many challenges towards industry 4.0 digital transformation. For M2M communication, reliable and stable connectivity with bounded delays is a mandatory requirement. Real-time communication is on the higher priority for this fourth revolution, which brings many technical challenges for future network development. A well-designed network architecture can increase the sustainability and performance of the entire system. The journey towards industry 4.0 is on its way and until now there are no such standards, regulations, and certification to follow them.Although fog becoming a developing key enabling technology for IoT architecture, it still faces some issues while integrating into the current architecture. Complex software applications and solutions are needed to achieve an efficient fog network. Fog network will be analyzed in terms of key performance measurements, which are bandwidth use, energy consumption, low latency, maximum throughput, and resource management. In this section, critical technical communication and networking challenges in the context of fog computing for IIoT applications are listed. All of them have potential for future work. * **Power Consumption/Energy Efficiency:** Several smart devices supporting an IIoT application will consume a massive amount of energy on a different scale according to their requirements. Ensuring network QoS with minimum energy consumption of smart IoT devices, fog nodes and cloud in an optimized way is an open challenge for every upcoming future IIoT application. * **Throughput/Rate/Capacity:** Throughput or network bandwidth, data rate and storage capacity depends on how much data is used and where data is stored in a fog network. This data placement on fog nodes or edge devices or cloud server has effects on cost, delays, bandwidth, and network coverage. The optimal placement of data on cloud server or fog cloudlet is one of the critical technical challenges for fog-IoT architecture. * **Spectrum Use/Resource Allocation:** Geographically separated fog, cloud nodes and their interconnection makes the backbone of any network that relies on offloading services. Most of the cloud computing interconnection mechanisms are not enough for fog networking due to their limitations including relying on a centralized cloud which cannot fulfill the latency and location awareness requirements of distributed devices, etc. Fog computing must encompass features, such as multi-tenancy, scalability, heterogeneity and quick resource provisioning. An architecture including fog and cloud computing must meet all these requirements for which resource allocation/use is the most critical challenge for better network performance. It has effects on all other QoS parameters. * **Latency:** IIoT applications requirement is real-time connectivity. All applications are time-sensitive and require real-time streaming rather than batch processing. Fog computing gives a better result for such decentralized solutions. It gives low latency with reliable connectivity and mobility. Optimized placement of data centers, resource allocation, network architecture, energy consumption of nodes, and storage capacity of nodes have impact on latency. Latency for a network is the sum of transmission, processing, propagation and queuing delays. To achieve the low-latency requirement, there is need mitigate all types of delays. * **Cache Enabled Edge Devices:** Caching content locally, reduces the access delay time and increases the energy and spectral usage efficiency. Since the Internet has multiple bottlenecks while accessing data from across continents and oceans, caching does not have to be dependent on any of these bottlenecks and instead makes the same data available locally. Furthermore, caching incredibly reduces the load on backhaul links since they do not have to be used anymore for accessing data.