# Proactive Caching at the Edge Leveraging Influential User Detection in Cellular D2D Networks
## 3 Related Work  
In recent years, a large number of studies have investigated caching on the edge in small cell networks. In [9], a proactive caching approach has been proposed. The authors studied two cases and utilized the spatial and social structure of the network. First, based on correlations among users and file popularity, files are cached during off-peak time. Secondly, influential users are detected and strategic content is cached using D2D communication and social networks. The authors used an eigenvector centrality measure for detecting influential users of the social network and model the content dissemination as a Dirichlet Process (CRP). In the experimental setup, a preferential attachment model is used to map the D2D small cellular network. The numerical results show a significant improvement in gain ratio; however, the proposed technique does not consider content of influential users in a specific community, which makes it less suitable for D2D communication in future cellular networks. The study in [11] introduced a new QoE metric for satisfying a given file request using proactive caching and then they proposed an optimization algorithm (_propCaching_) to maximize QoE. This algorithm is based on the popularity statistics of the requested files and cache files with highest popularity. However, unlike our proposed work, the algorithm has a limitation in that it chooses the popular files for caching based on their statistics or previous history. The work in [23] considers UE devices as cooperating nodes on which distributed cache is implemented for efficient downloading. However, this approach has certain drawbacks. Firstly, it does not consider the distance between D2D devices for cooperation and, secondly, it stores random content without prioritizing high in demand content. [PERSON] et al. [10] introduces a collaborative architecture which uses the distributed storage of popular content. In order to choose and cache random files at the user end, authors compute an average number of D2D links that can coexist without interference. However, this work also does not consider content of influential users to cache. A probabilistic approach for optimizing scheduling policies and D2D caching is considered in [24]. The authors first derived approximated uploading probability for uploading gain and then they optimize the scheduling factor and caching distribution to optimize the successful offloading probability. In [25], authors investigate an optimal caching strategy by formulating an optimization problem and showing the relationship between D2D caching distribution and demand distribution for homogeneous Poisson Point Process models with different noise levels. With the exponential increase in multimedia traffic, content caching at every edge node might become a challenging task. To overcome this problem, authors in [26] proposed an idea of peer-to-peer content delivery networks. The authors have exploited the benefits of distrusted fog nodes for content delivery among the networks. In order to efficiently deploy enabling 5G technologies, authors in [27] proposed an algorithm to reduce total installation costs. The proposed algorithm considers both the hardware and cloud enabled softwarized components (reusable functional blocks) to ensure the users' good performance as well as reduction in computation times. [PERSON] et al. [28] gives a comprehensive overview of modelling and solving optimization problems arising in wireless networks. Moreover, for a detailed review of applications of big data and caching techniques in mobile computing, the reader is referred to [9; 29]. Table 1 summarizes caching strategies in comparison with the one proposed in this paper.