# 5G Mobile Services and Scenarios: Challenges and Solutions
## 3 A Brief Review of Articles of this Special Issue
In fact, this concept provides unique and location-independent content, in-network caching and name-based routing. These features give NDN the potential to become a key technology for data dissemination in IoT. The NDN concept has abilities to mitigate the significant communication overhead caused by the distribution of commonly accessed contents. The Information-Centric Networking (ICN) [36, 37] concept is used to decrease the substantial communication overhead caused by the dissemination of analogously accessed contents. In-networking caching arranges a content replica that is cached at different locations to increase the availability of the desired data. Caching is a crucial component that makes ICN more beneficial than the present Internet architecture. It significantly minimizes the huge volume of data traffic and diminishes the bottleneck caused by publishing data in a unique location. Moreover, caches reduce the distance required for data retrieval. The cache performance totally depends on cache management schemes, which are divided into two mechanisms, namely, content placement strategies and replacement policies. [PERSON] et al. [38] addressed the caching strategies with the aim of recognizing which caching strategy is the most suitable for IoT networks. The simulations indicate the impact of different popularity-based caching strategies; of these, periodic caching is the most appropriate strategy for IoT environments in terms of a stretch that results in decreasing the content retrieval latency and improving the cache-to-hit ratio. Moreover, it is useful for all smart city applications, as it reduces the latency and improves the content response time. Cisco first introduced the term fog computing. The aim is to provide data storage, processing, and analysis capabilities at the edge devices instead of the cloud. Consequently, it improves the efficiency and performance of the overall system by reducing network load and delay. Integration of fog computing and IoT opens up new research venues, challenges and opportunities for the practitioners and researchers [39, 40, 41]. Dealing with the issue of energy crisis in SG is a challenging task. Load management using load balancing is one of the technique to cater this challenge. Virtual Machines (VMs) on the physical system is one of the techniques to manage resources efficiently and is also feasible for SGs management. [PERSON] et al. [42] addressed the issue of dynamic VM placement to reduce the computational cost, increase the system performance and reduce the delay for SG. Optimized Response Time Policy (ORTP) is used to route the request to fog. Thereafter, First Come First Serve (FCFS) or Ant Colony Optimization (ACO) policy assigns the request to the VM. The result shows that proposed system improves the overall system in terms of response time, processing time and the computation cost. It is interesting to see comprehensive analysis and evaluation by applying Best Fit (BF), First Fit (FF), First Fit Decreasing (FFD), and Best Fit Decreasing (BFD) heuristic algorithms in the future work.