Hengwei Zhang

A grid resource matching algorithm

Resource matching is one of the core functions of the grid resource management. Currently, the resource matching algorithm is mainly divided into two categories: the performance indicated matching algorithm and the cost indicated matching algorithm. This paper use correlation matrix designed a performance and cost constrained resource matching algorithm, which based on weighted Euclidean distance. The matlab simulation results show that the algorithm can effectively find the matched resource out in the network environment.

Network defense strategy selection based on best-response dynamic evolutionary game model

Since traditional game theory applying to network attack and defense has the restriction of complete rational, we establish non-cooperative evolutionary game model of network attack and defense on the premise of bounded rationality, and solved by the replicator dynamic equations. For the strategy learning evolution process of defender, we use the Best-response dynamic learning mechanism to establish the dynamic evolutionary game model between defenders, which can analyze the dynamic evolution process and defense evolution equilibrium point of defending strategy selection. Then, we summarize the evolution laws of network defense strategy selection under bounded rationality. The validity of the model and method is validated by system simulation.

Markov Evolutionary Games for Network Defense Strategy Selection

Since the characteristics of opposite objectives, non-cooperation relationship, and dependent strategies of network attack and defense are highly consistent with game theory, researching the decision-making methods of network defense and applying the game models to analyze the network attack–defense behaviors has been of concern in recent years. However, most of the research achievements regarding to the game models are based on the hypothesis that both the two sides’ players are completely rational, which is hard to meet. Therefore, we combined the evolutionary game theory and Markov decision-making process to construct a multi-stage Markov evolutionary game model for network attack–defense analysis, in view of the bounded rationality constraint. The model, based on the non-cooperative evolutionary game theory, could accomplish dynamic analysis and deduction for the multi-stage and multi-state network attack–defense process. In addition, an objective function with discounted total payoffs was designed by analyzing payoff characteristics of the multi-stage evolutionary game, which is more consistent with the reality of network attack and defense. Besides, the solving method for multi-stage game equilibrium was proposed on the basis of calculating the single-stage evolutionary game equilibrium. In addition, an algorithm for optimal defense strategy of the multi-stage evolutionary games was given. Finally, the experiments showed the high effectiveness and validity of the model and method that has a guiding significance for the network attack and defense.

Research for modeling network security based on attack-defense grapy of state reduction

In order to assess network security threats better, we model the attackers and defenders behavior based on attack-defense graph from the perspective of both attacker and defender, which lays the foundation of the further research for the scientific and precise information security threat assessment. Due to the existing problems of generating traditional attack-defense graph (e.g. explosion of state space, and the large-scale and complex generation of attack-defense graph), we in this paper propose a method for generating attack-defense graph based on state reduction, then we model the behavior of attacker and defender in network security. Finally, the method and the model proposed in this paper are proved to be scientific and effective within a typical network scenario.

Research on requirement schemes evaluation algorithm of electronic products

Requirement analysis is the starting point and basis of electronic products development. With the higher investment and longer cycle being significant features during the development process of electronic products, small deviations on the requirement may result in serious consequences and directly affect the benefit. Requirement analysis has been very important in product development. As the result of requirement analysis, requirement scheme is the accurate, standardized description of product requirement, the traction and evaluation criteria of subsequent development and production. When choosing requirement scheme that closely matches the product development goal, both the performance parameters and cost parameters are supposed to consider. However, the current evaluation algorithms mostly focus on one of them, or with high computational complexity. In order to solve the above problems, a new requirement schemes evaluation algorithm based on weighted Euclidean distance is proposed. The algorithm uses the cost-effective correlation matrix to take into account the performance parameters and cost parameters. The simulation experiments show that the algorithm own higher accuracy and efficiency.

Design of a resource selection approach in grid

Resource selection is the premise and foundation to ensure the quality of resource scheduling in grid. Accurate resource reliability risk, credibility, and real-time load filter can effectively ensure the success rate of users job. This paper use the historical information of resources, combined with real-time load of resources, designed a new resource selection approach in grid. Simulation experiments show that this approach can effectively select the available resource set, improve the quality of resource scheduling and reduce the failure rate of grid job.