Browsing by Author "Zhang, Huaqing"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item A Hierarchical Game Framework for Distributive Resource Allocation in Future Heterogeneous Network(2017-12) Zhang, Huaqing; Han, Zhu; Pan, Miao; Nguyen, Hien Van; Cai, Lin X.; Niyato, DusitThe explosive development of mobile data service makes our lives convenient and efficient. However, with the increasing demands of wireless data transmission, it is difficult to fulfill real-time requirements of mobile users in the traditional cellular architecture. In future wireless communication, the network is expected to be heterogeneous. On one hand, the large amount and different sizes of small cells are expected to be overlaid within the wireless network. On the other hand, wireless networks will be coordinated with other networks for expansion of available resources. Nevertheless, due to the distributive behaviors of multiple individuals in the heterogeneous network (HetNet), it is challenging to adopt resource allocations to achieve stable and high quality of service (QoS) for all mobile users. In this dissertation, we overview the development of wireless networks and summarize the wireless service into a 4-layer service architecture, consisting of the service layer, resource layer, infrastructure layer and user layer. Considering the heterogeneous architecture of future wireless network, a hierarchical game framework is proposed to determine distributive strategies for high performance and equilibrium solutions. We first analyze the distributive behaviors during the cooperation of multiple infrastructure providers, and propose a zero-determinant strategy for the administrator of the cooperation to maintain a high social welfare. Then, we analyze the distributive behaviors of multiple resource providers as well as infrastructure providers, with the applications of LTE unlicensed (LTE-U) and visible light communication (VLC). In LTE-U, multi-leader multi-follower Stackelberg game is employed among operators and users for resource management of licensed spectrum and unlicensed spectrum. In VLC, we combine VLC with Device-to-Device (D2D) communication and employ the Stackelberg game with a graphical game to analyze the equilibrium behaviors of all individuals. Finally, we consider the general heterogeneous network with the application of fog computing. With network virtualization, a hierarchical game framework combining the Stackelberg game and matching game are applied, where each mobile user is allocated with the optimal amount of computing resources from the selected fog node or cloud server.Item Computing Resource Allocation in Three-Tier IoT Fog Networks: A Joint Optimization Approach Combining Stackelberg Game and Matching(IEEE Internet of Things Journal, 3/29/2017) Zhang, Huaqing; Xiao, Yong; Bu, Shengrong; Niyato, Dusit; Yu, F. Richard; Han, ZhuFog computing is a promising architecture to provide economical and low latency data services for future Internet of Things (IoT)-based network systems. Fog computing relies on a set of low-power fog nodes (FNs) that are located close to the end users to offload the services originally targeting at cloud data centers. In this paper, we consider a specific fog computing network consisting of a set of data service operators (DSOs) each of which controls a set of FNs to provide the required data service to a set of data service subscribers (DSSs). How to allocate the limited computing resources of FNs to all the DSSs to achieve an optimal and stable performance is an important problem. Therefore, we propose a joint optimization framework for all FNs, DSOs, and DSSs to achieve the optimal resource allocation schemes in a distributed fashion. In the framework, we first formulate a Stackelberg game to analyze the pricing problem for the DSOs as well as the resource allocation problem for the DSSs. Under the scenarios that the DSOs can know the expected amount of resource purchased by the DSSs, a many-to-many matching game is applied to investigate the pairing problem between DSOs and FNs. Finally, within the same DSO, we apply another layer of many-to-many matching between each of the paired FNs and serving DSSs to solve the FN-DSS pairing problem. Simulation results show that our proposed framework can significantly improve the performance of the IoT-based network systems.