Some projection-like methods for the generalized Nash equilibria

Zhang, Jianzhong; Qu, Bo; Xiu, Naihua

doi:10.1007/s10589-008-9173-x

Cited by 43 publications

(23 citation statements)

References 20 publications

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“…The argument based on projective dynamical systems has been exploited in the papers of Cavazzuti, Pappalardo and Passacantando [2], Xia and Wang [13], Zhang, Qu and Xiu [14] for Nash-type equilibria. Note that the present result for Stackelberg equilibria is slightly general than those in the above works.…”

Section: Remark 32mentioning

confidence: 99%

“…Due to the latter fact, we are able to guarantee not only existence but also location results (via projective dynamical systems) of the Stackelberg competition model whenever the strategy sets are compact or non-compact. Recently, projection-like methods for Nash equilibria have been developed by Cavazzuti, Pappalardo and Passacantando [2], Pang and Fukushima [10], Xia and Wang [13], Zhang, Qu and Xiu [14], and references therein. For generic equilibrium results via variational and non-variational methods, we refer the reader to the volumes [3,4,8].…”

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confidence: 99%

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Stackelberg equilibria via variational inequalities and projections

Nagy

2012

J Glob Optim

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Section: Remark 32mentioning

confidence: 99%

mentioning

confidence: 99%

Stackelberg equilibria via variational inequalities and projections

Nagy

2012

J Glob Optim

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“…The game theory is also efficient for the resource allocation with resource competition, and the Nash Equilibria are often needed to be verified first [46,47].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Resource Allocation for Load Balancing in Fog Environment

Qing

et al. 2018

Wireless Communications and Mobile Computing

162

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Fog computing is emerging as a powerful and popular computing paradigm to perform IoT (Internet of Things) applications, which is an extension to the cloud computing paradigm to make it possible to execute the IoT applications in the network of edge. The IoT applications could choose fog or cloud computing nodes for responding to the resource requirements, and load balancing is one of the key factors to achieve resource efficiency and avoid bottlenecks, overload, and low load. However, it is still a challenge to realize the load balance for the computing nodes in the fog environment during the execution of IoT applications. In view of this challenge, a dynamic resource allocation method, named DRAM, for load balancing in fog environment is proposed in this paper. Technically, a system framework for fog computing and the load-balance analysis for various types of computing nodes are presented first. Then, a corresponding resource allocation method in the fog environment is designed through static resource allocation and dynamic service migration to achieve the load balance for the fog computing systems. Experimental evaluation and comparison analysis are conducted to validate the efficiency and effectiveness of DRAM.

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“…On one hand, the explosively increasing data creates the limits for data storage and data transmission; on the other hand, data has become an important productivity resource that could help users make data-driven decisions by some computational methods, such as giving optimized scheme by operational research [1,2], giving accurate prediction by regression analysis [3], or carrying out geometrical computation [4]. Therefore, it is necessary to design an efficient data sharing model to share huge amount of data among different individuals or organizations.…”

Section: Introductionmentioning

confidence: 99%

Flexible, Secure, and Reliable Data Sharing Service Based on Collaboration in Multicloud Environment

Wei

Shao²,

Zhang

2018

Wireless Communications and Mobile Computing

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Due to the abundant storage resources and high reliability data service of cloud computing, more individuals and enterprises are motivated to outsource their data to public cloud platform and enable legal data users to search and download what they need in the outsourced dataset. However, in "Paid Data Sharing" model, some valuable data should be encrypted before outsourcing for protecting owner's economic benefits, which is an obstacle for flexible application. Specifically, if the owner does not know who (user) will download which data files in advance and even does not know the attributes of user, he/she has to either remain online all the time or import a trusted third party (TTP) to distribute the file decryption key to data user. Obviously, making the owner always remain online is too inflexible, and wholly depending on the security of TTP is a potential risk. In this paper, we propose a flexible, secure, and reliable data sharing scheme based on collaboration in multicloud environment. For securely and instantly providing data sharing service even if the owner is offline and without TTP, we distribute all encrypted split data/key blocks together to multiple cloud service providers (CSPs), respectively. An elaborate cryptographic protocol we designed helps the owner verify the correctness of data exchange bills, which is directly related to the owner's economic benefits. Besides, in order to support reliable data service, the erasure-correcting code technic is exploited for tolerating multiple failures among CSPs, and we offer a secure keyword search mechanism that makes the system more close to reality. Extensive security analyses and experiments on real-world data show that our scheme is secure and efficient.

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Some projection-like methods for the generalized Nash equilibria

Abstract: Generalized Nash equilibrium, Quasi-variational inequality, Projection-like method, Convergence,

Cited by 43 publications

References 20 publications

Stackelberg equilibria via variational inequalities and projections

Stackelberg equilibria via variational inequalities and projections

Dynamic Resource Allocation for Load Balancing in Fog Environment

Flexible, Secure, and Reliable Data Sharing Service Based on Collaboration in Multicloud Environment

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