Collaborative content distribution in mobile networks with caching and D2D-assistance

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University of New Brunswick


While the mobile networks are evolving to a content-centric paradigm, the surging traffic demands keep stressing the ever-increasing network capacities. In-network caching offers an effective means to alleviate the traffic pressure by saving bandwidth utilization and balancing traffic loads. In this thesis, we first introduced an integrated content distribution framework that integrates universal in-network caching and enables collaboration across domains. This framework takes advantage of appealing design principles in device-to-device (D2D) communications, mobile edge computing (MEC), network function virtualization (NFV), and software-defined networking (SDN). Leveraging this framework, we studied the request screening problem, which aims to appropriately select the video requests offloaded to energy-efficient D2D communications. We redirected content requests to maximize the coverage of requests that can be fulfilled through D2D communications. Given the constraints of individual transmission and caching capacities, the number of available D2D channels, and information privacy with social-awareness, we can decouple the screening problem into two subproblems, i.e., the device caching and matching problem, and the D2D channel allocation problem. As we proved that both problems are NP-hard, we proposed social-aware heuristic algorithms that iteratively make the best offloading decision in each step. Simulation results show that the proposed algorithms perform fairly closely to optimal solutions in small-scale instances and outperform the reference schemes under various situations. Then, we studied the request routing problem, which selects sources and redirects video streams appropriately to optimize in-network flows. We proposed a context-aware approach for request routing through the integrated edge-core. The results demonstrate that the proposed solution achieves significant performance gain over the reference schemes in exploiting network dynamics and user context to relieve network congestion.