# Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges
## 5 Challenges with Solutions
### Cache Enabled Edge Devices  
Fog networking is a vast field, which uses both smart objects and the already deployed network infrastructure. System can ensure QoS either by using already deployed network devices or by optimally dividing the tasks among edge devices or using both at the same time. Cache placement in edge devices/fog nodes in a network improves the efficiency of a system in terms of low power consumption, low-latency, high throughput, and efficient spectrum use. To deal with the congestion problem at the backhaul link of F-RAN, authors have proposed a projection gradient method in [93]. To increase the throughput, they have used stochastic geometry to derive a close-form of successful transmission probability (STP). Afterward, the optimal placement of cache over the network was done. To fulfill the delay requirements, authors in [94] have proposed a decentralized asynchronous coding caching scheme. The result shows that the proposed algorithm is more efficient than existing algorithms present in the literature. A convex optimization problem of minimizing the worst-case fronthaul delay was formulated by the authors. Depending on application delay requirements, the proposed coded scheme gives synchronous and asynchronous transmission methods. The problem of user association with a fog node on the basis of lower latency is formulated in [95]. The authors have formulated the problem using game theory, for which they have used a proactive caching scheme and Boltzmann-Gibbs learning algorithm for solution. Latency of proposed fog network is the sum of computing and queuing delays.  
Different researchers have worked on the F-RAN design considering various aspects. For a green system, as discussed by [PERSON] et al. [67; 96], minimization of energy consumption is done by considering an F-RAN that is cache-enabled for the selection of Remote Radio Head (RRHs). For balancing front-haul traffic, [PERSON] et al. [97] have discussed a scheme to deliver data from Base Band Unit (BBU) and RRHs. Content placement problem involving caching has been discussed in [PERSON] et al. [98] and [PERSON] et al. [99]. F-RANs accommodate caching in the road-side units. [PERSON] et al. [100] have worked on maximizing the Signal to Interference Noise Ratio (SINR) to ensure fairness while jointly optimizing cluster formation and multicast beamforming. The objective function in this work has non-convex constraints and is collectively an NP-hard problem. Sensor-cloud system gives solutions to many applications in a smart city. The system was developed by the integration of CPS and cloud computing. Besides many benefits, a major problem is coupling resource management, which was discussed in [101]. They have introduced a fog layer between sensor and cloud layer, which emphasizes the services. Firstly, authors have proposed an algorithm for caching at fog layer, afterwards, Hungarian algorithm was extended to deal with the optimal use of resources on basis of maximum matching. The proposed algorithms result in the minimization of latency for sustainable services.