User Features-Aware Content Delivery in Cache-Enabled Mobile MD2D Network

• Published in: IEEE internet of things journal Vol. 10; no. 14; pp. 12703 - 12714
• Main Authors: Lin, Zhijian, Zeng, Zexiong, Chen, Xiaopei, Chen, Pingping, Wang, Ying
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.07.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Branch and bound methods; Cache-enabled; content delivery network; Content distribution networks; device-to-device (D2D); Device-to-device communication; Encoding; Energy consumption; Greedy algorithms; Internet of Things; mobility; Optimization; Social factors; Throughput; user features
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2023.3253251

Device-to-device (D2D) communication is one of the most promising technologies for relieving the pressure of demands in the 5G mobile networks. However, due to randomness of user request, limitation of storage space and transmission capacity, it is still a challenge for channel allocation to optimize the successful delivery ratio of contents. Thus, in this article, we first consider the link selection problem for mobile users in multi-D2D (MD2D)-based content delivery networks. We establish a content delivery utility that combines physical and social aspects, taking into account energy consumption, user mobility, and trust relationships. Second, we model the content delivery link selection as the maximum weighted matching problem. For this NP-hard problem, by relaxing the integer constraints, we propose a BnB-CDLS algorithm based on the branch-and-bound method for the proposed content delivery scheme. Furthermore, we prove that the problem can be computationally reduced to a monotone submodular problem subject to matroid and knapsack constraints, which can be solved by a greedy GA-CDLS algorithm. Numerical results show that as compared with the existing schemes, the proposed scheme can significantly improve the successful delivery ratio of contents.