Bargaining Strategies for Networked Multimedia Resource Management

Park, Hyunggon; Schaar, Mihaela van der

doi:10.1109/tsp.2007.893755

Cited by 151 publications

(158 citation statements)

References 26 publications

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“…Because the convexity for any two joint utility points X and Y in S is proved in [3], the feasible solution of our problem S also becomes convex. Therefore, this feasible utility set S is nonempty, convex, closed, and bounded.…”

Section: Bargaining Gamementioning

confidence: 99%

“…In the model, users can change their service selections according to the expected utility of each service that is decided by the service providers. We adopted the Kalai-Smorodinsky bargaining solution (KSBS) [3], which guarantees fair resource allocations proportional to maximum achievable utilities of users. The second model is a repeated Stackelberg game between a service provider and the user group.…”

Section: Multimedia Service Discrimination Based On Fair Resource Allmentioning

confidence: 99%

“…In the aspect of proportional fairness, the KSBS was compared with the NBS because it applies individual monotonicity instead of the third axiom of the NBS. The optimality conditions of both solutions and differences between the quantitative proportional fairness of the NBS and the qualitative proportional fairness of the KSBS for multimedia services are analyzed in [3]. The KSBS allows choosing a proportional fair solution among the Nash equilibrium if it preserves four axioms: Pareto optimality, symmetry, independence from linear transformation, and individual monotonicity [13].…”

Section: Bargaining Gamementioning

confidence: 99%

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Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

Shin¹

2012

ETRI J

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We deal with a resource allocation problem for multimedia service discrimination in wireless networks. We assume that a service provider allocates network resources to users who can choose and access one of the discriminated services. To express the rational service selection of users, the utility function of users is devised to reflect both service quality and cost. Regarding the utility function of a service provider, total profit and efficiency of resource usage have been considered. The proposed service discrimination framework is composed of two game models. An outer model is a repeated Stackelberg game between a service provider and a user group, while an inner model is a service selection game among users, which is solved by adopting the Kalai-Smorodinsky bargaining solution. Through simulation experiments, we compare the proposed framework with existing resource allocation methods according to user cost sensitivity. The proposed framework performed better than existing frameworks in terms of total profit and fairness.

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Section: Bargaining Gamementioning

confidence: 99%

Section: Multimedia Service Discrimination Based On Fair Resource Allmentioning

confidence: 99%

Section: Bargaining Gamementioning

confidence: 99%

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Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

Shin¹

2012

ETRI J

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“…The maximization of the sum of users' expected video quality is considered in [4] using a pricing-based resource allocation mechanism which, however, doesn't guarantee convergence. Maximizing the system utility has also been analyzed for a cooperative environment within the framework of bargaining in [5], but this solution cannot be applied in the case of individual selfish users who are competing for some expensive resources. In [6], the authors make use of Ausubel's ascending-bid auction [7] to fairly allocate rate among different users.…”

Section: Introductionmentioning

confidence: 99%

A Quality-of-Experience driven bidding game for uplink video transmission in next generation mobile networks

Schroeder

Essaili

Steinbach

et al. 2012

2012 19th IEEE International Conference on Image Processing

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Centralized approaches to solve resource allocation problems for wireless real-time multimedia communications have been intensively studied but require the availability of meta information about the multimedia content and channel information of all users. In this paper, we propose a Quality of Experience (QoE) driven bidding game for de-centralized uplink resource allocation among multiple mobile video producers. Different from previous works, the price per resource unit is defined on a Mean Opinion Score (MOS) scale and users bid for the resources that maximize their own utility function. Simulations in an LTE environment show the benefits of our distributed approach in terms of convergence time and QoE performance, compared to a centralized greedy scheme and a state-of-theart game-theoretic approach.

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“…게임이론은 대역폭 할당 [1,2] , 채널 할당 [3] , 네트 워크 흐름 제어 [4] , 전력 제어 [5] 및 비디오 압축 [6] 을 제안하였다. 그리고 NBS를 비디 오 압축 기술에 이용하여 그 효율성을 높였다 [6] .…”

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Cleaning Area Division Algorithm for Power Minimized Multi-Cleanup Robots Based on Nash Bargaining Solution

Choi¹,

Park²

2014

The Journal of Korea Information and Communications Society

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In this paper, we propose an approach to minimizing total power consumption by deploying multiple clean-up robots simultaneously in a given area. For this, we propose to use the cooperative game theoretic approaches (i.e., Nash bargaining solution (NBS)) such that the robots can optimally and fairly negotiate the area division based on available resources and characteristics of the area, thereby leading to the minimum total power consumption. We define a utility function that includes power consumptions for characteristics of areas and the robots can agree on a utility pair based on the NBS. Simulation results show that the proposed approach can reduce the total average power consumption by 15-30% compared to a random area division approach.

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Bargaining Strategies for Networked Multimedia Resource Management

Cited by 151 publications

References 26 publications

Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

A Quality-of-Experience driven bidding game for uplink video transmission in next generation mobile networks

Cleaning Area Division Algorithm for Power Minimized Multi-Cleanup Robots Based on Nash Bargaining Solution

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