scholarly journals Location-Aware Incentive Mechanism for Traffic Offloading in Heterogeneous Networks: A Stackelberg Game Approach

Entropy ◽  
2018 ◽  
Vol 20 (4) ◽  
pp. 302 ◽  
Author(s):  
Kailing Yao ◽  
Yunpeng Luo ◽  
Yang Yang ◽  
Xin Liu ◽  
Yuli Zhang ◽  
...  
Keyword(s):  
Heterogeneous Networks ◽  
Stackelberg Game ◽  
Incentive Mechanism ◽  
Location Aware ◽  
Traffic Offloading

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

Incentive mechanism for computation offloading using edge computing: A Stackelberg game approach

2017 ◽  
Vol 129 ◽  
pp. 399-409 ◽  
Author(s):  
Yang Liu ◽  
Changqiao Xu ◽  
Yufeng Zhan ◽  
Zhixin Liu ◽  
Jianfeng Guan ◽  
...  
Keyword(s):  
Stackelberg Game ◽  
Incentive Mechanism ◽  
Edge Computing ◽  
Computation Offloading

scholarly journals A Joint Constraint Incentive Mechanism Algorithm Utilizing Coverage and Reputation for Mobile Crowdsensing

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4478
Author(s):  
Jing Zhang ◽  
Xiaoxiao Yang ◽  
Xin Feng ◽  
Hongwei Yang ◽  
An Ren
Keyword(s):  
Information Quality ◽  
Stackelberg Game ◽  
Incentive Mechanism ◽  
Response Strategy ◽  
Mobile Users ◽  
Target Area ◽  
Mobile Crowdsensing ◽  
Sensing Data ◽  
Priority Order

Selection of the optimal users to maximize the quality of the collected sensing data within a certain budget range is a crucial issue that affects the effectiveness of mobile crowdsensing (MCS). The coverage of mobile users (MUs) in a target area is relevant to the accuracy of sensing data. Furthermore, the historical reputation of MUs can reflect their previous behavior. Therefore, this study proposes a coverage and reputation joint constraint incentive mechanism algorithm (CRJC-IMA) based on Stackelberg game theory for MCS. First, the location information and the historical reputation of mobile users are used to select the optimal users, and the information quality requirement will be satisfied consequently. Second, a two-stage Stackelberg game is applied to analyze the sensing level of the mobile users and obtain the optimal incentive mechanism of the server center (SC). The existence of the Nash equilibrium is analyzed and verified on the basis of the optimal response strategy of mobile users. In addition, mobile users will adjust the priority of the tasks in time series to enable the total utility of all their tasks to reach a maximum. Finally, the EM algorithm is used to evaluate the data quality of the task, and the historical reputation of each user will be updated accordingly. Simulation experiments show that the coverage of the CRJC-IMA is higher than that of the CTSIA. The utility of mobile users and SC is higher than that in STD algorithms. Furthermore, the utility of mobile users with the adjusted task priority is greater than that without a priority order.

scholarly journals Resource Management for Device-to-Device Communications in Heterogeneous Networks Using Stackelberg Game

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Yinuo He ◽  
Feiran Wang ◽  
Jianjun Wu
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Networks ◽  
Stackelberg Game ◽  
Interference Management ◽  
D2d Communication ◽  
Allocation Scheme ◽  
D2d Communications ◽  
Device To Device ◽  
Group A ◽  
Resource Allocation Scheme

Device-to-device (D2D) communications and femtocell systems can bring significant benefits to users’ throughput. However, the complicated three-tier interference among macrocell, femtocell, and D2D systems is a challenging issue in heterogeneous networks. As D2D user equipment (UE) can cause interference to cellular UE, scheduling and allocation of channel resources and power of D2D communication need elaborate coordination. In this paper, we propose a joint scheduling and resource allocation scheme to improve the performance of D2D communication. We take UE rate and UE fairness into account by performing interference management. First, we construct a Stackelberg game framework in which we group a macrocellular UE, a femtocellular UE, and a D2D UE to form a two-leader one-follower pair. The cellular UE are leaders, and D2D UE is the follower who buys channel resources from the leaders. We analyze the equilibrium of the game and obtain solutions to the equilibrium. Second, we propose an algorithm for joint scheduling of D2D pairs based on their utility. Finally, we perform computer simulations to study the performance of the proposed scheme.

Location-Aware Pilot Assignment for Massive MIMO Systems in Heterogeneous Networks

2016 ◽  
Vol 65 (8) ◽  
pp. 6815-6821 ◽  
Author(s):  
Peiyao Zhao ◽  
Zhaocheng Wang ◽  
Chen Qian ◽  
Linglong Dai ◽  
Sheng Chen
Keyword(s):  
Heterogeneous Networks ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Location Aware
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