Reversed Stackelberg bandwidth-sharing game for cognitive multi-hop cellular networks

Abstract

Multi-hop relaying cellular network (MCN) is a recently proposed architecture to preserve the advantages of traditional single-hop cellular networks and ad hoc relaying networks. In MCNs, efficient bandwidth management plays an important role in determining network performance. In this study, a new cognitive radio bandwidth-sharing scheme is proposed based on the reversed Stackelberg game model. In the proposed scheme, base station (BS) and relay stations (RSs) are hierarchically interconnected and interacting with one another to effectively share the wireless bandwidth. By using a trust model, the BS appropriately reacts to selfish RSs to maximise network performance. This approach can promote cooperation with respect to adaptive bandwidth allocation. With a simulation study, it is demonstrated that the proposed scheme can approximate an optimised solution under widely diverse traffic load intensities.

Towards Security Joint Trust and Game Theory for Maximizing Utility: Challenges and Countermeasures

“…In this section, we briefly describe our research work from three aspects: The application of game theory, the application of trust, and the application of joint game theory and trust; and give some examples in the literature. Through the investigation of literature, we have concluded that most researchers use the following types of games: Dynamic game [32][33][34][35][36][37][38][39][40][41][42][43][44][45], static game [46], non-cooperative game [47][48][49][50][51], cooperative game [52][53][54][55][56][57][58][59], security game [60][61][62][63][64], and trust game [65][66][67][68][69].…”

“…Researchers using the dynamic game have established some mechanisms or solutions for application scenarios, solving the issues of maximizing utility in the networks/systems. The dynamic game also has some applications in solving problems related to network security [35], gaining a higher network lifetime in wireless sensor network, and obtaining higher secure caching ratio of heterogeneous networks [38,42], such as improving the bandwidth utilization, network throughput, and other performance [32,34,36]. In some application scenarios, the main purpose of the game is to make an optimal pricing strategy to achieve higher utility of the system [39,40].…”

“…In this literature, researchers use trust relationships, trustworthiness, and other factors for decision-making. Based on trust, the researchers proposed some trust models [34,40,49,52,53,58,59,64,69,75,79], trust mechanisms [32,42,43,78,82], and trust frameworks [57]. They provide a better selection scheme for players in the network/system through trust evaluation.…”

Cooperative waiting‐time reduction for cognitive radio networks using Stackelberg game

“…With the utilisation of 'backward induction', TPU i can reach its maximal utility Up i, j (t)* in (11), the optimised Us i, j (t)* for TSU j in (15) can also be determined.…”

“…Wang et al [14] develops a framework that jointly considers power control, channel allocation and scheduling of a device-to-device communication with Stackelberg game. Kim [15] uses a reversed Stackelberg game model to consider the bandwidth-sharing problem in a multi-hop relaying cellular network. Wang et al [16] proposes a security game in which users pay a friendly jammer to jam the eavesdroppers and a trade-off between users and the jammer is analysed with Stackelberg game.…”