scholarly journals Evolutionary Game-Theoretic Solution for Virtual Routers with Padding Misbehavior in Cloud Computing

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Xia-an Bi ◽  
Xiaohui Wang ◽  
Hong Liu
Keyword(s):  
Cloud Computing ◽  
Equilibrium Points ◽  
Evolutionary Game ◽  
Interactive Applications ◽  
Network Applications ◽  
Normal Behavior ◽  
Game Theoretic ◽  
Virtual Routers ◽  
The Stability ◽  
Theoretic Solution

With the development of cloud computing and virtualization, a physical router can be multiplexed as a large number of virtual routers. TCP-based interactive applications have an incentive to improve their performance by padding “junk packets” into the network among real communication packets. This padding misbehavior will upgrade short TCP flows from “mice” to “elephants” and consequently lead to network congestion and breakdown. This paper presents a detailed solution and analysis for describing the normal behavior and padding misbehavior of virtual routers. In particular, a system model for analyzing behavior of virtual routers is based on evolutionary game model, and, through analyzing the stability of the equilibrium points, the stable point is the solution to the problem. The clear evolutionary path of network applications with the normal behavior and padding misbehavior is analyzed by the corresponding graph. Then this paper gives the behavior control suggestions to effectively restrain the padding misbehavior and maintain stable high-throughputs of the router. The simulation results demonstrate that our solution can effectively restrain the padding misbehavior and maintain stable high-throughputs of the router simultaneously compared with the classical queue management.

Research on Organization Tacit Knowledge Transferring: An Evolutionary Game Theoretic Analysis

2013 ◽  
Vol 756-759 ◽  
pp. 2597-2601
Author(s):  
Dan Li
Keyword(s):  
Game Theory ◽  
Tacit Knowledge ◽  
Evolutionary Game Theory ◽  
Process Model ◽  
Evolutionary Game ◽  
Dynamic Game ◽  
Theoretic Analysis ◽  
Game Theoretic Analysis ◽  
Game Theoretic ◽  
The Stability

The transfer and the management of the tacit knowledge is one of the most important issues in the knowledge transferring context to create organizational competitive advantage in the fast growing competitive world. As we know, organization tacit knowledge transferring is a dynamic game process, this research applies evolutionary game theory to analyze the tacit knowledge transferring activities among organizations and the stability balance issue in organization knowledge transferring. Based on the theory of games, this paper constructs the evolutionary game process model for organization tacit knowledge transferring. And through the equilibrium point of the model, the different knowledge transferring bodies game replicated dynamics and stability are analyzed. With this model, the reason why tacit knowledge is hard to be transferred and the path of tacit knowledge transferring is analyzed.

scholarly journals Multiagent Task Allocation in Complementary Teams: A Hunter-and-Gatherer Approach

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Mehdi Dadvar ◽  
Saeed Moazami ◽  
Harley R. Myler ◽  
Hassan Zargarzadeh
Keyword(s):  
Decision Making ◽  
Task Allocation ◽  
Equilibrium Analysis ◽  
Profit Margins ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Game Theoretic ◽  
Simulation Results ◽  
The Stability ◽  
Theoretic Solution

Consider a dynamic task allocation problem, where tasks are unknowingly distributed over an environment. This paper considers each task comprising two sequential subtasks: detection and completion, where each subtask can only be carried out by a certain type of agent. We address this problem using a novel nature-inspired approach called “hunter and gatherer.” The proposed method employs two complementary teams of agents: one agile in detecting (hunters) and another skillful in completing (gatherers) the tasks. To minimize the collective cost of task accomplishments in a distributed manner, a game-theoretic solution is introduced to couple agents from complementary teams. We utilize market-based negotiation models to develop incentive-based decision-making algorithms relying on innovative notions of “certainty and uncertainty profit margins.” The simulation results demonstrate that employing two complementary teams of hunters and gatherers can effectually improve the number of tasks completed by agents compared to conventional methods, while the collective cost of accomplishments is minimized. In addition, the stability and efficacy of the proposed solutions are studied using Nash equilibrium analysis and statistical analysis, respectively. It is also numerically shown that the proposed solutions function fairly; that is, for each type of agent, the overall workload is distributed equally.

scholarly journals Research on the Optimization Management of Cloud Privacy Strategy Based on Evolution Game

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Pan Jun Sun
Keyword(s):  
Cloud Computing ◽  
Evolutionary Game ◽  
Selection Strategy ◽  
Game Model ◽  
Classical Dynamic ◽  
Computing Services ◽  
Dynamic Replication ◽  
Optimization Management ◽  
Cloud Computing Services ◽  
The Stability

Cloud computing services have great convenience, but privacy security is a big obstacle of popularity. In the process result of privacy protection of cloud computing, it is difficult to choose the optimal strategy. In order to solve this problem, we propose a quantitative weight model of privacy information, use evolutionary game theory to establish a game model of attack protection, design the optimal protection strategy selection algorithm, and make the evolutionary stable equilibrium solution method from the limited rational constraint. In order to study the strategic dependence of the same game group, the classical dynamic replication equation is improved by using the incentive coefficient, an improved evolutionary game model of attack protection is constructed, the stability of equilibrium point is further analyzed by Jacobian matrix method, and the optimal selection strategy is obtained under different conditions. Finally, the correctness and validity of the model are verified by experiments, different strategies of the same group have the dual effects of promotion and inhibition, and the advantages of this paper are shown by comparing with other articles.

scholarly journals Infect While the Iron is Scarce: Nutrient Explicit Phage-Bacteria Games

2019 ◽  
Author(s):  
Daniel Muratore ◽  
Joshua S. Weitz
Keyword(s):  
Viral Infection ◽  
Nutrient Dynamics ◽  
Evolutionary Game ◽  
Tail Fiber ◽  
Theoretic Approach ◽  
Marine Microbes ◽  
Evolutionarily Stable Strategies ◽  
Game Theoretic ◽  
The Stability ◽  
Fiber Proteins

AbstractMarine microbial primary production is influenced by the availability and uptake of essential nutrients, including iron. Although marine microbes have evolved mechanisms to scavenge sub-nanomolar concentrations of iron, recent observations suggest that viruses may co-opt these very same mechanisms to facilitate infection. The “Ferrojan Horse Hypothesis” proposes that viruses incorporate iron atoms into their tail fiber proteins to adsorb to target host receptors. Here, we propose an evolutionary game theoretic approach to consider the joint strategies of hosts and viruses in environments with limited nutrients (like iron). We analyze the bimatrix game and find that evolutionarily stable strategies depend on the stability and quality of nutrient conditions. For example, in highly stable iron conditions, virus pressure does not change host uptake strategies. However, when iron levels are dynamic, virus pressure can lead to fluctuations in the extent to which hosts invest in metabolic machinery that increases both iron uptake and susceptibility to viral infection. Altogether, this evolutionary game model provides further evidence that viral infection and nutrient dynamics jointly shape the fate of microbial populations.

scholarly journals Analysis of a Multiparticipant Game under a Subsidy and Punishment Mechanism: An Evolutionary Theory Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Jiangchao Li ◽  
Shilei Yang
Keyword(s):  
Equilibrium Points ◽  
Pure Strategy ◽  
Evolutionary Game ◽  
Vital Role ◽  
Strategic Choices ◽  
Strategy Space ◽  
Market Sentiment ◽  
Punishment Mechanism ◽  
The Government ◽  
The Stability

In a market with intense competition, cost pressures tempt enterprises to seek profits in ways that infringe on the interests of consumers. This is especially true when market sentiment is weak. In such situations, governments play a vital role in protecting consumers’ interests and helping struggling enterprises. We construct a tripartite game model that includes the government, enterprises, and consumers under a subsidy and punishment mechanism. We use this model to investigate the strategic choices made by the participants in an evolutionary game theory (EGT) framework. We present four stable equilibrium points as pure strategy solutions with the aid of a replicator dynamic system. Three main findings are presented in this paper. First, not all equilibrium points can be evolutionary stable strategies (ESSs) when considering the potential motivations of the participants to change strategies. Second, there is an equilibrium point that satisfies the stability condition but changes periodically in its strategy space; strategy changes between participants are not synchronized. Third, the government prefers to subsidize enterprises when enterprise speculation is serious or when enterprise investment in improving production technology is high.

Four-party evolutionary game analysis of supervision for vaccine quality in major epidemics

2022 ◽  
pp. 1-20
Author(s):  
Rongjian Xie ◽  
Yucai Jia ◽  
Yuanmei Wu ◽  
Peiyun Zhang
Keyword(s):  
Equilibrium Points ◽  
Evolutionary Game ◽  
Regulatory System ◽  
External Information ◽  
The Public ◽  
Leading Role ◽  
Government Supervision ◽  
The Government ◽  
The Stability ◽  
The Cost

During major epidemics, monitoring vaccine quality can ensure the public health and social stability. Considering that social media has become an important way for the public to obtain external information during the epidemic. We developed a dual regulatory system of vaccine quality with the government in the leading role and the participation of We Media, and constructed a four-party evolutionary game model (government regulatory agency, We Media, vaccine industry groups, and the public) and analyzed the stability of each game player’s strategy choice. The system’s possible equilibrium points are identified using Lyapunov’s first law. Then the game trajectory between stakeholders is simulated by MATLAB, the effects of initial intention and parameters on the evolution process and results are analyzed. The results show that to ensure the quality and safety of vaccines and stabilize network public opinion during epidemics, the government should invest in an effective supervision mechanism. By strengthening responsibility, increasing penalties, and reducing supervision costs, the probability of vaccine industry groups providing high-quality vaccines is effectively enhanced. Restricting the behavior of We Media and supervising vaccine industry groups to reduce speculation reduces the cost of government supervision and improves its efficiency.

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