Resource Allocation Strategy Based on Matching Game

With the development of satellite communication technology,the traditional resource allocation strategies are difficult to meet the requirements of resource utilization efficiency.In order to solve the optimization problem of resource allocation for multi-layer satellite networks in multi-user scenarios,we propose a new resource allocation scheme based on the many-to-many matching game.This scheme is different from the traditional resource allocation strategies that just consider a trade-off between the new call blocking probability and the handover call failure probability.Based on different preference lists among different layers of medium earth orbit(MEO) satellites,low earth orbit(LEO) satellites,base stations and users,we propose the corresponding algorithms from the perspective of quality of experience(QoE).The simulation results show that the many-to-many matching game scheme can effectively improve both the resource utilization efficiency and QoE,compared with the one-to-one and many-to-one matching algorithms.

A Caching Strategy Based on Many-to-Many Matching Game in D2D Networks

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

Optimization of energy exchange in microgrid networks: a coalition formation approach

In this paper, we elaborate a new strategy based on cooperative game theory models to encourage and manage the interactions in a MicroGrid network. The proposed strategy optimizes the cooperation and the energy exchange in a distributed μGrid network. The strategy consists of a two stage algorithm: Coalition formation algorithm which was specifically created to approximate the optimal set of coalitions that return considerable savings. And the Matching game to manage the energy exchange inside each coalition. The performance of our strategy was verified through simulations. These latter show that the losses can be considerably decreased by the use of the proposed strategy: the rate of the loss reduction can reach up to 20% if the two stages are applied on the network. Moreover, the strategy proved to have a fast convergence which makes it operational for real implemented networks.