Modeling and analysis of high availability techniques in a virtualized system

Availability evaluation of a virtualized system is critical to the wide deployment of cloud computing services. Time-based, prediction-based rejuvenation of virtual machines (VM) and virtual machine monitors, VM failover and live VM migration are common high-availability (HA) techniques in a virtualized system. This paper investigates the effect of combination of these availability techniques on VM availability in a virtualized system where various software and hardware failures may occur. For each combination, we construct analytic models rejuvenation mechanisms to improve VM availability; (2) prediction-based rejuvenation enhances VM availability much more than time-based VM rejuvenation when prediction successful probability is above 70%, regardless failover and/or live VM migration is also deployed; (3) failover mechanism outperforms live VM migration, although they can work together for higher availability of VM. In addition, they can combine with software rejuvenation mechanisms for even higher availability; (4) and time interval setting is critical to a time-based rejuvenation mechanism. These analytic results provide guidelines for deploying and parameter setting of HA techniques in a virtualized system

Coal Rock Breaking Simulation and Cutting Performance Analysis of Disc Cutters

The coal rock breaking ability of disc cutters directly affects the construction efficiency and safety of rescue tunnels in collapsed coal rock formations. This paper establishes the plastic constitutive relationship under the Drucker-Prager (D-P) plasticity criterion, builds up a finite-element analysis (FEA) model for the coal rock breaking with a single cutter on Abaqus FEA, and explores the influence laws of different penetrations and cutting velocities on the rock breaking performance of the cutter. The results show that: as the penetration increased from 3.0 mm to 7.0 mm, the mean vertical force of the cutter grew from 16.97 kN to 23.36 kN, and the mean rolling force rose from 1.79 kN to 3.95 kN. The increase of the cutter\u27s vertical force improves the cutting efficiency, but intensifies the vertical impact, which undermines construction safety. As the cutting velocity increased from 0.6 rad/s to 1.5 rad/s, the mean vertical force grew from 15.64 kN to 22.94 kN, and the mean rolling force rose from 1.46 kN to 4.23 kN. With the increase of cutting velocity, the cutting force grew at an increasing speed. The increase of cutting velocity can improve cutting efficiency, but an excessively fast cutting velocity will weaken the stability of the cutting operation, and add to the wear of the tool. The research method provides theoretical supports to the cutterhead design of tunnel boring machine (TBM) and tunnelling control in broken coal rock formation

Multiple Attributes Decision Fusion for Wireless Sensor Networks Based on Intuitionistic Fuzzy Set

Decision fusion is an important issue in wireless sensor networks (WSN), and intuitionistic fuzzy set (IFS) is a novel method for dealing with uncertain data. We propose a multi-attribute decision fusion model based on IFS, which includes two aspects: data distribution-based IFS construction algorithm (DDBIFCA) and the category similarity weight-based TOPSIS intuitionistic fuzzy decision algorithm (CSWBT-IFS). The DDBIFCA is an IFS construction algorithm that transforms the original attribute values into intuitionistic fuzzy measures, and the CSWBT-IFS is an intuitionistic fuzzy aggregation algorithm improved by the traditional TOPSIS algorithm, which combines intuitionistic fuzzy values of different attributes and obtains a final decision for the monitoring target. Both algorithms have benefits, such as low energy consumption and low computational complexity, which make them suitable for implementation in energy-constrained WSNs. Simulation results show the efficiency of intuitionistic fuzzification for the DDBIFCA and a high classification accuracy, compared with traditional fuzzy fusion and other intuitionistic fuzzy aggregation algorithms, for the CSWBT-IFS

Experimental study on fracture plugging effect of irregular-shaped lost circulation materials

Using micro-visualization experimental device for the formation of fracture plugging zone, the plugging behavior of irregular-shaped lost circulation materials (LCMs) with different types and concentrations in fractures was experimentally analyzed. The results show that the sealing time decreases significantly with the increase of material concentration. When the concentration is 20%, the sealing times of materials LCM-1∼LCM-5 are 6s, 7s, 5s, 6s, 4s, respectively. The formation of fracture plugging zone includes two stages, and the main factors affecting the formation of fracture plugging zone are flatness, roundness, convexity and concentrations. Flatness affects the retention stage of LCMs through the matching degree between particle size and fracture width. Convexity and roundness affect the retention stage by increasing the friction coefficient between particles. The high-efficiency retention ability of irregular LCMs is characterized by strong matching to fracture width, and strong friction and sliding resistance between particles. It is recommended that the optimized geometric parameters of high-efficiency retention materials should meet the requirements of “low flatness, low roundness and low convexity” (flatness \u3c0.6, roundness \u3c0.6 and convexity \u3c0.8), which can improve the plugging effect significantly

Human Model Adaptation for Multiview Markerless Motion Capture

An approach to automatic modeling of individual human bodies using complex shape and pose information. The aim is to address the need for human shape and pose model generation for markerless motion capture. With multi-view markerless motion capture, three-dimensional morphable models are learned from an existing database of registered body scans in different shapes and poses. We estimate the body skeleton and pose parameters from the visual hull mesh reconstructed from multiple human silhouettes. Pose variation of body shapes is implemented by the defined underlying skeleton. The shape parameters are estimated by fitting the morphable model to the silhouettes. It is done relying on extracted silhouettes only. An error function is defined to measure how well the human model fits the input data, and minimize it to get the good estimate result. Further, experiments on some data show the robustness of the method, where the body shape and the initial pose can be obtained automatically