Resource Allocation Algorithms of Vehicle Networks with Stackelberg Game

2020 ◽  
pp. 221-230
Author(s):  
Ying Zhang ◽  
Guang-Shun Li ◽  
Jun-Hua Wu ◽  
Jia-He Yan ◽  
Xiao-Fei Sheng
Keyword(s):  
Resource Allocation ◽  
Stackelberg Game ◽  
Vehicle Networks ◽  
Allocation Algorithms

Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

2020 ◽  
Vol 10 (5) ◽  
pp. 1557
Author(s):  
Weijia Feng ◽  
Xiaohui Li
Keyword(s):  
Resource Allocation ◽  
Incomplete Information ◽  
Stackelberg Game ◽  
Superior Performance ◽  
Channel Gain ◽  
Mobile Users ◽  
Pricing Strategies ◽  
Game Equilibrium ◽  
Allocation Process ◽  
Realistic Situation

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.

scholarly journals Minimizing Resource Waste in Heterogeneous Resource Allocation for Data Stream Processing on Clouds

2020 ◽  
Vol 11 (1) ◽  
pp. 149
Author(s):  
Wu-Chun Chung ◽  
Tsung-Lin Wu ◽  
Yi-Hsuan Lee ◽  
Kuo-Chan Huang ◽  
Hung-Chang Hsiao ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Data Stream ◽  
Limited Attention ◽  
Heterogeneous Servers ◽  
Resource Allocation Algorithm ◽  
System Utilization ◽  
Allocation Algorithms ◽  
Considerable Resource ◽  
Heterogeneous Resources

Resource allocation is vital for improving system performance in big data processing. The resource demand for various applications can be heterogeneous in cloud computing. Therefore, a resource gap occurs while some resource capacities are exhausted and other resource capacities on the same server are still available. This phenomenon is more apparent when the computing resources are more heterogeneous. Previous resource-allocation algorithms paid limited attention to this situation. When such an algorithm is applied to a server with heterogeneous resources, resource allocation may result in considerable resource wastage for the available but unused resources. To reduce resource wastage, a resource-allocation algorithm, called the minimizing resource gap (MRG) algorithm, for heterogeneous resources is proposed in this study. In MRG, the gap between resource usages for each server in cloud computing and the resource demands among various applications are considered. When an application is launched, MRG calculates resource usage and allocates resources to the server with the minimized usage gap to reduce the amount of available but unused resources. To demonstrate MRG performance, the MRG algorithm was implemented in Apache Spark. CPU- and memory-intensive applications were applied as benchmarks with different resource demands. Experimental results proved the superiority of the proposed MRG approach for improving the system utilization to reduce the overall completion time by up to 24.7% for heterogeneous servers in cloud computing.

scholarly journals Dynamic SPICE-model of resource allocation in marketing networks

2020 ◽  
Vol 13 ◽  
pp. 8-23
Author(s):  
Movlatkhan T. Agieva ◽  
◽  
Olga I. Gorbaneva ◽  
Keyword(s):  
Resource Allocation ◽  
Stackelberg Game ◽  
Target Audience ◽  
Opinion Leaders ◽  
Stackelberg Equilibrium ◽  
Common Interest ◽  
Theoretic Model ◽  
Goods And Services ◽  
Spice Model ◽  
Private Interests

We consider a dynamic Stackelberg game theoretic model of the coordination of social and private interests (SPICE-model) of resource allocation in marketing networks. The dynamics of controlled system describes an interaction of the members of a target audience (basic agents) that leads to a change of their opinions (cost of buying the goods and services of firms competing on a market). An interaction of the firms (influence agents) is formalized as their differential game in strategic form. The payoff functional of each firm includes two terms: the summary opinion of the basic agents with consideration of their marketing costs (a common interest of all firms), and the income from investments in a private activity. The latter income is described by a linear function. The firms exert their influence not to all basic agents but only to the members of strong subgroups of the influence digraph (opinion leaders). The opinion leaders determine the stable final opinions of all members of the target audience. A coordinating principal determines the firms' marketing budgets and maximizes the summary opinion of the basic agents with consideration of the allocated resources. The Nash equilibrium in the game of influence agents and the Stackelberg equilibrium in a general hierarchical game of the principal with them are found. It is proved that the value of opinion of a basic agent is the same for all influence agents and the principal. It is also proved that the influence agents assign less resources for the marketing efforts than the principal would like.

Adaptive Resource Allocation Algorithms for Multi-user MIMO-OFDM Systems

2014 ◽  
Vol 80 (1) ◽  
pp. 51-69 ◽  
Author(s):  
Najib A. Odhah ◽  
Emad S. Hassan ◽  
Mohamad Abdelnaby ◽  
Waleed E. Al-Hanafy ◽  
Moawad I. Dessouky ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Adaptive Resource Allocation ◽  
Ofdm Systems ◽  
Mimo Ofdm ◽  
Adaptive Resource ◽  
Allocation Algorithms
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