Multi-leader Multi-follower Stackelberg Game Based Dynamic Resource Allocation for Mobile Cloud Computing Environment

Wang, Ying; Meng, Sachula; Chen, Yongce; Sun, Ruijin; Wang, Xinshui; Sun, Kai

doi:10.1007/s11277-016-3351-4

Cited by 24 publications

(11 citation statements)

References 17 publications

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“…Tärneberg et al [125] considered heterogeneous distribution of cost and capacity for network infrastructure in an MCC environment and accordingly proposed a resource management scheme to incorporate the analysis of data center utilization and communication link utilization so as to address the issues of elasticity for mobile cloud network. Wang et al [140] established a resource management method considering both the user experience of mobile devices and cost of service providing at cloud. They managed to allocate the communication network bandwidth efficiently so that the performance requirement from mobile devices could be satisfied at relatively low cost.…”

Section: Communication Networkmentioning

confidence: 99%

An Overview of Mobile Cloud Computing for Pervasive Healthcare

Wang

Jin

2019

IEEE Access

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Mobile devices, along with wearable sensors, allow patients to access healthcare services from anywhere at any time. The longstanding constraints of computational capability and storage space on mobile devices can be alleviated by outsourcing computation-or data-intensive tasks to remote cloud centers. Thus, mobile cloud computing (MCC) has been recognized as a promising approach to provide pervasive healthcare services to people in their daily life. As the development and adoption of MCC techniques in healthcare, new optimization strategies have been explored and studied to help mobile cloud healthcare services to be deployed in a more effective and efficient manner. In this survey, we demonstrate how MCC techniques have been extensively deployed in various healthcare applications and, specifically, describe the general architecture and design considerations one should take into account while designing an MCC for healthcare scenarios. Given a large number of factors that may affect the performance of the MCC and even result in catastrophic consequences in healthcare, this paper presents the state-of-the-art optimization methods on the MCC for meeting the diverse priorities and achieving the optimal tradeoff among multiple objectives. Finally, the security and privacy issues of the MCC in healthcare are also discussed. INDEX TERMS Mobile cloud computing, pervasive healthcare. optimization, offloading, security and privacy. NOMENCLATURE

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Section: Communication Networkmentioning

confidence: 99%

An Overview of Mobile Cloud Computing for Pervasive Healthcare

Wang

Jin

2019

IEEE Access

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“…Game theory is emerged as a pivotal tool for the resource allocation problem [19][20][21][22] in MCC networks. The interaction between remote cloud, cloudlet and mobile subscriber was modelled in [23][24][25][26]. A QoE-based dynamic radio resource allocation problem is formulated as two-stage Stackelberg game in [23].…”

Section: Application Of Game Theory In MCC Networkmentioning

confidence: 99%

“…The interaction between remote cloud, cloudlet and mobile subscriber was modelled in [23][24][25][26]. A QoE-based dynamic radio resource allocation problem is formulated as two-stage Stackelberg game in [23]. In [25], the resource allocation for heterogeneous MCC is modelled as a combinatorial auction.…”

Section: Application Of Game Theory In MCC Networkmentioning

confidence: 99%

“…The marginal payoff can be used to update the strategy and it can be calculated by the variation in utilities with a small variation φ (e.g. φ = 10 −4 ) which is given by (see (23)) (see (24)) After adjusting the size of the allocated resource and unit price, the small cell users will evolve to obtain a new evolutionary equilibrium. Based on the new evolutionary equilibrium, cloudlets will adjust their strategies again.…”

Section: Non-cooperative Equilibrium Of Cloudletsmentioning

confidence: 99%

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Hierarchical evolutionary game based dynamic cloudlet selection and bandwidth allocation for mobile cloud computing environment

et al. 2019

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“…Emerging mobile cloud computing technologies provide great potentials for mobile terminals to support highly complex applications. Wang Y et al [9], based on the two-stage Stackelberg game model of multi-master and multi-slave, adopted an acceptable QoE to solve the resource management problem of MCC networks which maximized the utility function of the network. Modern communication networks are becoming highly virtualized, with a two-layer hierarchical structure.…”

Section: Introductionmentioning

confidence: 99%

Study on Master Slave Interaction Model Based on Stackelberg Game in Distributed Environment

et al. 2020

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In view of the problems such as low efficiency, difficulty in resolving local conflicts and lack of practical application scenarios, existing in the interaction model of multi-agent systems in a distributed environment, a multi-master multi-slave interaction model was designed based on the Stackelberg game, which is applied to the interaction game problem between the controller and the participant in the command and control process. Through optimizing the Stackelberg game model and multi-attribute decision-making, the multi-master, multi-slave, multi-agent system of the Stackelberg game was designed, and the closed loop problem under the Stackelberg game is solved for dimension reduction and optimal function value. Finally, through the numerical derivation simulation and the training results of related system data, the high efficiency and strong robustness of the model were verified from multiple perspectives, and this model algorithm was proved to be true and highly efficient.

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Multi-leader Multi-follower Stackelberg Game Based Dynamic Resource Allocation for Mobile Cloud Computing Environment

Cited by 24 publications

References 17 publications

An Overview of Mobile Cloud Computing for Pervasive Healthcare

An Overview of Mobile Cloud Computing for Pervasive Healthcare

Hierarchical evolutionary game based dynamic cloudlet selection and bandwidth allocation for mobile cloud computing environment

Study on Master Slave Interaction Model Based on Stackelberg Game in Distributed Environment

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