Novel energy-aware approach to resource allocation in cloud computing

In this paper, we address the issue of resource allocation in a Cloud Computing environment. Since the need for cloud resources has led to the rapid growth of data centers and the waste of idle resources, high-power consumption has emerged. Therefore, we develop an approach that reduces energy consumption. Decision-making for adequate tasks and virtual machines (VMs) with their consolidation minimizes this latter. The aim of the proposed approach is energy efficiency. It consists of two processes; the first one allows the mapping of user tasks to VMs. Whereas, the second process consists of mapping virtual machines to the best location (physical machines). This paper focuses on this latter to develop a model by using a deep neural network and the ELECTRE methods supported by the K-nearest neighbor classifier. The experiments show that our model can produce promising results compared to other works of literature. This model also presents good scalability to improve the learning, allowing, thus, to achieve our objectives.

Development of a Wireless Corrosion Detection System for Steel-Framed Structures Using Pulsed Eddy Currents

Structural health monitoring (SHM) can be more efficient with the application of a wireless sensor network (WSN). However, the hardware that makes up this system should have sufficient performance to sample the data collected from the sensor in real-time situations. High-performance hardware can be used for this purpose, but is not suitable in this application because of its relatively high power consumption, high cost, large size, and so on. In this paper, an optimal remote monitoring system platform for SHM is proposed based on pulsed eddy current (PEC) that is utilized for measuring the corrosion of a steel-framed construction. A circuit to delay the PEC response based on the resistance–inductance–capacitance (RLC) combination was designed for data sampling to utilize the conventional hardware of WSN for SHM, and this approach was verified by simulations and experiments. Especially, the importance of configuring sensing modules and the WSN for remote monitoring were studied, and the PEC responses caused by the corrosion of a specimen made with steel were able to be sampled remotely using the proposed system. Therefore, we present a remote SHM system platform for diagnosing the corrosion condition of a building with a steel structure, and proving its viability with experiments.

Power Consumption Analysis and Experimental Study on the Kneading and Cutting Process of Licorice Stem in Horizontal Total Mixed Ration Mixer

Aiming at the problems of high-power consumption and insufficient kneading and cutting of roughage in the total mixed ration mixer. In this paper, licorice stems were taken as experimental objects, the horizontal twin-shaft TMR mixer was used to carry out the experimental study. It should be as brief as possible and concise. Through the kneading and cutting process power analysis, determine the influencing factors of kneading and cutting power consumption. The auger speed, processing time and blade type were taken as experimental factors, with standard straw length rate and power consumption as indicators, Box–Behnken test with three factors and three levels was carried out, analysis of variance was performed on the test results, the results show that the significant effect of each factor on the standard grass length is processing time, blade type and auger speed in descending order. The significance of the influence on power consumption from large to small is auger speed, processing time and blade type. The response surface analysis and parameter optimization were carried out, the results show that the auger speed is 20 r/min, the processing time is 29 min, and the blade type is quincunx blade. At this time, the standard straw length was 82.634%; Power consumption 4525.815 kJ, TMR mixer performance reached the best. The results can provide a theoretical basis for the subsequent research and development of TMR mixer.

Novel non intrusive continuous use ZeBox technology to trap and kill airborne microbes

Preventing nosocomial infection is a major unmet need of our times. Existing air decontamination technologies suffer from demerits such as toxicity of exposure, species specificity, noxious gas emission, environment-dependent performance and high power consumption. Here, we present a novel technology called “ZeBox” that transcends the conventional limitations and achieves high microbicidal efficiency. In ZeBox, a non-ionizing electric field extracts naturally charged microbes from flowing air and deposits them on engineered microbicidal surfaces. The surface’s three dimensional topography traps the microbes long enough for them to be inactivated. The electric field and chemical surfaces synergistically achieve rapid inactivation of a broad spectrum of microbes. ZeBox achieved near complete kill of airborne microbes in challenge tests (5–9 log reduction) and $$>90\%$$ > 90 % efficiency in a fully functional stem cell research facility in the presence of humans. Thus, ZeBox fulfills the dire need for a real-time, continuous, safe, trap-and-kill air decontamination technology.

THE ASSESS THE FAULT-TOLERANCE, EFFİCİENCY AND PERFORMANCE OF MİLİTARY FİELD LOCAL NETWORK TOPOLOGY

Depending on the location of communication nodes of the control points and points of relay in the field, especially in mountainous areas, finding line of sight (LOS) and establishing a good radio relay connection can be challenging. In addition, depending on the requirements for bandwidth and communication stability, in the field, a situation often arises where it is possible to build a network only based on certain types of topologies. To assess the security of military field telecommunication networks, it is important to determine such important parameters as network stability or fault-tolerance, efficiency, transmission capacity and delay time. It is known that the greatest values of these parameters are achieved in the type of "fully connected" network topology. However, low efficiency, high power consumption, difficulties in safely and hidden placement of a large number of vehicles in the battle area and the complexity of maintenance, as well as the fact that radio relay hardware vehicles consist mainly of 2 sets of radio relay devices make this type of topology unsuitable for field networks. Therefore, it is important to define a network topology with high stability, using the minimum amount of radio relay vehicles. For the above reason, the article proposes mathematical methods for calculating the fault tolerance and efficiency of the selected network topology, as well as fault tolerance, bandwidth and latency for each network node.

Deep Learning-Based Service Scheduling Mechanism for GreenRSUs in the IoVs

Green roadside units (RSUs), also called renewable energy-powered RSUs, are utilized recently rather than the traditional electric-powered RSUs with high power consumption and the large infrastructure deployment cost in the Internet of vehicles (IoVs). However, the power of the green RSUs is limited and unstable, which is affected by the battery size and charging environment. Therefore, a big challenge to deploy green RSUs in the IoVs is to schedule their service process properly, in order to extend the service efficiency of RSUs. In this paper, a deep learning-based communication scheduling mechanism is proposed regarding the service scheduling problem. In particular, a three-part scheduling algorithm consisting of RSU clustering, deep learning-based traffic prediction, and a vehicle access scheduling algorithm is presented to maximize the service number of vehicles and minimize the energy cost. An extensive simulation is done, and the simulation results indicate that our algorithm can serve more vehicles with less energy consumption compared with other scheduling mechanisms under different scenarios.

DESIGN AND TEST OF NEGATIVE PRESSURE CHAMBER ROTARY BUCKWHEAT SEED METERING DEVICE

A negative pressure chamber rotary precision seed metering device was designed to achieve the buckwheat precision sowing goal, solving the problems of traditional negative pressure chamber poor sealing and air suction seed metering device high power consumption. The planting plate of the device was fixedly connected with the shell of the air chamber forming a negative pressure chamber, which rotates around an axis. A planting plate suitable for buckwheat seed metering was designed. Single factor test and response surface test were carried out on the seed metering device. Results showed that the buckwheat precision seed metering achieved best performance when the negative pressure, suction hole diameter and rotation speed was 2.4 kPa, 2.0 mm and 25 r/min respectively. The qualified index, multiples index and miss-seeding index were respectively 88.32%, 7.35%, and 4.33%, which met the technical requirements of buckwheat precision sowing. The results of the study provided references for the design and application of buckwheat precision seed metering device.

A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems

For the purpose of high performance computation, several machines are developed at an exascale level. These machines can perform at least one exaflop calculations per second, which corresponds to a billion billon or 108. The universe and nature can be understood in a better manner while addressing certain challenging computational issues by using these machines. However, certain obstacles are faced by these machines. As huge quantity of components is encompassed in the exascale machines, frequent failure may be experienced and also the resilience may be challenging. High progress rate must be maintained for the applications by incorporating certain form of fault tolerance in the system. Power management has to be performed by incorporating the system in a parallel manner. All layers inclusive of fault tolerance layer must adhere to the power limitation in the system. Huge energy bills may be expected on installation of exascale machines due to the high power consumption. For various fault tolerance models, the energy profile must be analyzed. Parallel recovery, message-logging, and restart or checkpoint fault tolerance models for rollback recovery are evaluated in this paper. For execution with failure, the most energy efficient solution is provided by parallel recovery when programs with various programming models are used. The execution is performed faster with parallel recovery when compared to the other techniques. An analytical model is used for exploring these models and their behavior at extreme scales.

ZeBox: A novel non-intrusive continuous-use technology to trap and kill airborne microbes

Preventing nosocomial infection is a major unmet need of our times. Existing air decontamination technologies suffer from demerits such as toxicity of exposure, species specificity, noxious gas emission, environment-dependent performance and high power consumption. Here, we present a novel technology called ZeBox that transcends the conventional limitations and achieves high microbicidal efficiency. In ZeBox, a non-ionizing electric field extracts naturally charged microbes from flowing air and deposits them on engineered microbicidal surfaces. The surfaces three dimensional topography traps the microbes long enough for them to be inactivated. The electric field and chemical surfaces synergistically achieve rapid inactivation of a broad spectrum of microbes. ZeBox achieved near complete kill of airborne microbes in challenge tests (5-9 log reduction) and >90% efficiency in a fully functional stem cell research facility in the presence of humans. Thus, ZeBox fulfills the dire need for a real-time, continuous, safe, trap-and-kill air decontamination technology.

Low-power sensor node for the detection of methane and propane

The detection of flammable gases is necessary to avoid explosive atmospheres. For this reason, low-cost pellistors are frequently used. However, such commercial pellistors require an operation temperature of 450 ∘C or more for the detection of methane and a correspondingly high power consumption. We present a novel wireless low-power catalytic gas sensor system based on non-precious metal catalyst for the detection of methane and propane operated at 350 ∘C. The combination of a microelectromechanical system (MEMS)-based sensor with a low-power radio system provides the opportunity to monitor complex infrastructure without using a power grid as power supply. The sensor system has been characterised extensively under the exposure to methane and propane at concentrations between 2000 and 8000 ppm, as these gases are the common test gases for pellistors in industry. Methane is the main component of natural gas; propane is an important component of liquified petroleum gas (LPG). In addition, the influence of changes in humidity on the sensor response to methane was examined in more detail. Due to the planned operation of the sensor and radio system in different application scenarios, short (3 s) and long (60 s) sampling rates were used for investigations.