Cooperative Task Offloading and Content Delivery for Heterogeneous Demands: A Matching Game-Theoretic Approach

In the mobile edge computing (MEC) networks, the heterogeneous demands can be met through device-to-device (D2D) technology due to the idle local resources from the neighbors. Although the overload of mobile edge computing servers can be relieved by sharing idle local resources among neighbors, the active impact of the cooperation in the close neighbors is ignored in the most existing works. In this paper, we study the mutual cooperation between the users with heterogeneous demands such as the computation tasks or the desired contents, and then propose an innovative D2D-assisted heterogeneous users cooperation framework where two users with different demands can share their idle local resources. The optimization is to minimize the aggregate delay of all users in MEC networks. First, the problem is formulated as a heterogeneous demands based matching game involving D2D matching and edge matching. Next, the multi-round cooperation matching (MRCM) algorithm is proposed to find the stable match of the proposed game. Finally, the simulation results present the validity and effectiveness of our proposed game as well as the proposed algorithm.