Social-Aware Energy-Efficient Data Offloading With Strong Stability

Abstract

The exploding popularity of mobile devices enables people to enjoy the benefits brought by various interesting mobile apps. The ever-increasing data traffic has exacerbated energy consumption on both cellular service providers and mobile users. It has become an urgent need to reducing the energy consumption in the cellular network while satisfying users’ increasing traffic demands. Mobile data offloading is an effective energy-saving paradigm to tackle the above-mentioned problem. However, the current approaches cannot fully address the issue in terms of user demands and offloaded traffic. With the observation that duplicated data transmission often happens in the crowd with similar social interests, we deploy device-to-device (D2D) data offloading to achieve the energy efficiency at the user side while adapting their increasing traffic demands. Specifically, we investigate the stochastic optimization of the long-term time-averaged expected energy consumption while guaranteeing the strong stability of the network by utilizing the social-aware and energy-efficient D2D mobile offloading. By jointly considering interference among D2D users, social-aware caching, link scheduling, and routing, an offline finite-queue-aware energy minimization problem is formulated, which is a time-coupling stochastic mixed-integer non-linear programming (MINLP) problem. We propose an online finite-queue-aware energy algorithm by employing the Lyapunov drift-plus-penalty theory. Extensive analysis and simulations are conducted to validate the proposed scheme.