A Specific Risk Evaluation System for Live Virtual Machine Migration Based on the Uncertain Theory

Benefiting from the convenience of virtualization, virtual machine migration is generally utilized to fulfil optimization objectives in cloud/edge computing. However, live migration has certain risks and unapt decision may lead to side effects and performance degradation. Leveraging modified deep Q network, this paper provided an advanced risk evaluation system. Thorough formulation was given in this paper and a specific integration method was innovated based on uncertain theory. Series experiments were carried on computing cluster with OpenStack. The experimental results showed deep Q network for risk system was reliable while the uncertain approach was a proper way to deal with the risk integration.

Statistical Convergence of Order α for Complex Uncertain Sequences

In this paper, we introduce convergence concepts namely, statistical convergence of order [Formula: see text], statistical convergence of order [Formula: see text] almost surely, statistical convergence of order [Formula: see text] in measure, statistical convergence of order [Formula: see text] in mean, statistical convergence of order [Formula: see text] in distribution in complex uncertain theory. We also investigate some relationships among them.

Multistage decision approach for short life cycle products using Pythagorean fuzzy set

In this paper, a multistage decision-making problem concerning uncertainty and ambiguity is discussed using Pythagorean fuzzy sets. Complement Pythagorean fuzzy membership grades and their properties are also considered. Using the definition of an alpha-level set, we introduce the multistage decision-making problems, where the possibility theory and satisfaction grades are declared with the help of Pythagorean membership grades. Pythagorean multistage decision-making is an uncertain theory, where decision-maker has only one opportunity to choose the scenario under the combination of Pythagorean possibility and satisfaction grades at each stage. According to the selection of criteria, a series of decision points are concluded. The payoff collaborates with these decision points at each stage. The multistage decision-making using Pythagorean fuzzy sets is the scenario-based theory in place of other theories like lottery-based theory etc. The results have been calculated using multistage Pythagorean fuzzy sets in which the decision-maker has only one chance to select the optimal solution. The TOPSIS technique has been applied and the comparison between these two techniques is highlighted.

Grain Emergency Transport Model on Unascertained Number

The question to choose a grain supplement emergency path is uncertain. By using uncertain methods, integration of experts can be done. Base on the uncertain theory, we build the model of choosing a path with minimum risk in the process of grain emergency transportation and the algorithm. Firstly, estimate every path in the net to get the unascertained numbers of experts. Then, the unascertained number of experts with the uncertain operate rule is computed. Thirdly, the expectation and reliability of its unascertained number can be gotten. At last, get the minimum risk path by operate the expectation and the experiential value. This model has certain rationality and validity by data test.