Consolidation Technique Research Articles

EBWO‐GE: An innovative approach to dynamic VM consolidation for cloud data centers

SummaryCloud data centers (CDCs) have revolutionized global computing by offering extensive storage and processing capabilities. Nevertheless, the environmental impact of these processes, including their substantial energy consumption and carbon emissions, calls for implementing more efficient techniques. Efficient virtual machine (VM) consolidation is crucial in optimizing resource utilization and reducing energy consumption. Current methods for enhancing energy efficiency often lead to issues such as service level agreements (SLAs) violations and quality of services (QoS) degradation. This study presents a novel approach to host selection using a grey‐extreme (GE) machine learning model, which accurately predicts over and underutilized hosts. In addition, a VM placement technique called enhanced black widow optimization (EBWO) utilizes black widow optimization heuristic techniques and a differential evolutionary approach to optimize VM placement. The proposed dynamic VM consolidation technique optimizes energy utilization while meeting strict SLA requirements and enhancing QoS metrics in CDCs. Extensive analyses were conducted using the Cloudsim toolkit to validate the approach's effectiveness. These analyses encompassed conditions such as random workloads in heterogeneous environments. The simulation results showed that GE‐EBWO outperforms other techniques and improves energy efficiency by 12%–15%. In addition, it significantly decreases VM migrations by 11%–14% compared to other advanced methods. The study validates the practicality of the proposed technique in moving towards environmentally friendly CDCs.

Utilizing Inherent Bias for Memory Efficient Continual Learning: A Simple and Robust Baseline

Learning from continuously evolving data is critical in real-world applications. This type of learning, known as Continual Learning (CL), aims to assimilate new information without compromising performance on prior knowledge. However, learning new information leads to a bias in the network towards recent observations, resulting in a phenomenon known as catastrophic forgetting. The complexity increases in Online Continual Learning (OCL) scenarios where models are allowed only a single pass over data. Existing OCL approaches that rely on replaying exemplar sets are not only memory-intensive when it comes to large-scale datasets but also raise security concerns. While recent dynamic network models address memory concerns, they often present computationally demanding, over-parameterized solutions with limited generalizability. To address this longstanding problem, we propose a novel OCL approach termed “Bias Robust online Continual Learning (BRCL).” BRCL retains all intermediate models generated. These models inherently exhibit a preference for recently learned classes. To leverage this property for enhanced performance, we devise a strategy we describe as ‘utilizing bias to counteract bias.’ This method involves the development of an Inference function that capitalizes on the inherent biases of each model towards the recent tasks. Furthermore, we integrate a model consolidation technique that aligns the first layers of these models, particularly focusing on similar feature representations. This process effectively reduces the memory requirement, ensuring a low memory footprint. Despite the simplicity of the methodology to guarantee expandability to various frameworks, extensive experiments reveal a notable performance edge over leading methods on key benchmarks, getting continual learning closer to matching offline training. (Source code will be made publicly available upon the publication of this paper.)

Structural evolution and mechanical properties of 9Cr ferritic/martensitic ODS steels developed by a direct powder forging route

ABSTRACT A nominal composition of mechanically alloyed Fe-9Cr-2W-0.2Ti-0.12C-0.35Y2O3 steel powders was consolidated via a direct powder forging route. The powder-forged samples exhibited an equiaxed grain structure with the formation of Y-Ti-O (Y2Ti2O7 or YTiO3) complex oxides and the absence of prior particle boundaries. The powder-forged samples were further heat treated, i.e. cooled at three different rates, i.e. furnace cooling, air cooling, and water quenching, followed by tempering for the air-cooled and water-quenched samples. The tensile strength at room temperature for water-quenched and normalised samples was comparable, whereas the ductility for the normalised samples was higher, while at high temperature, a good combination of strength and ductility was achieved in the tempered air-cooled samples among all the heat-treated samples. The mechanical properties achieved in the present study were at par and superior in some cases to those reported in literature. The absence of prior particle boundaries network, almost full density and equiaxed grains indicated that the powder forging route can emerge as an alternative consolidation technique to HIP and hot extrusion for the consolidation of powder metallurgy oxide dispersion strengthened steels for nuclear applications.

Annealing Behavior of a Mg-Y-Zn-Al Alloy Processed by Rapidly Solidified Ribbon Consolidation.

Mg-Y-Zn-Al alloys processed by the rapidly solidified ribbon consolidation (RSRC) technique are candidate materials for structural applications due to their improved mechanical performance. Their outstanding mechanical strength is attributed to solute-enriched stacking faults (SESFs), which can form cluster-arranged layers (CALs) and cluster-arranged nanoplates (CANaPs) or complete the long-period stacking ordered (LPSO) phase. The thermal stability of these solute arrangements strongly influences mechanical performance at elevated temperatures. In this study, an RSRC-processed Mg-0.9%, Zn-2.05%, Y-0.15% Al (at%) alloy was heated at a rate of 0.666 K/s up to 833 K, a temperature very close to melting point. During annealing, in situ X-ray diffraction (XRD) measurements were performed using synchrotron radiation in order to monitor changes in the structure. These in situ XRD experiments were completed with ex situ electron microscopy investigations before and after annealing. At 753 K and above, the ratio of the matrix lattice constants, c/a, decreased considerably, which was restored during cooling. This decrease in c/a could be attributed to partial melting in the volumes with high solute contents, causing a change in the chemical composition of the remaining solid material. In addition, the XRD intensity of the secondary phase increased at the beginning of cooling and then remained unchanged, which was attributed to a long-range ordering of the solute-enriched phase. Both the matrix grains and the solute-enriched particles were coarsened during the heat treatment, as revealed by electron microscopy.

Assessment of Soil Consolidation Techniques in Ecuador: Preloading and Wick Drains in the Exodo-Fertisa Project

Assessment of Soil Consolidation Techniques in Ecuador: Preloading and Wick Drains in the Exodo-Fertisa Project

Code-Based Differential GNSS Ranging for Lunar Orbiters: Theoretical Review and Application to the NaviMoon Observables

In the near future, international space agencies have planned to achieve significant milestones in investigating the utilization of Global Navigation Satellite Systems (GNSS) within and beyond the current space service volume up to their application to lunar missions. These initiatives aim to demonstrate the feasibility of GNSS navigation at lunar altitudes. Based on the outcomes of such demonstrations, dozens of lunar missions will likely be equipped with a GNSS receiver to support autonomous navigation in the lunar proximity. Relying on non-invasive, consolidated differential techniques, GNSS will enable baseline estimation, thus supporting a number of potential applications to lunar orbiters such as collaborative navigation, formation flight, orbital manoeuvers, remote sensing, augmentation systems and beyond. Unfortunately, the large dynamics and the geometry of such differential GNSS scenarios set them apart from current terrestrial and low-earth orbit use cases. These characteristics result in an increased sensitivity to measurements time misalignment among orbiters. Hence, this paper offers a review of baseline estimation methods and characterizes the divergences and limitations w.r.t. to terrestrial applications. The study showcases the estimation of the baseline length between a lunar CubeSat mission, VMMO, and the communication relay Lunar Pathfinder mission. Notably, real GNSS measurements generated by an Engineering Model of the NaviMoon receiver in the European Space Agency (ESA/ESTEC) Radio Navigation Laboratory are utilized. A radio-frequency constellation simulator is used to generate the GNSS signals in these hardware-in-the-loop tests. The performed analyses showed the invalidity of common terrestrial differential GNSS ranging techniques for space scenarios due to the introduction of significant biases. Improved ranging algorithms were proposed and their potential to cancel ranging errors common to both receivers involved was confirmed.

Last decade insights on cemented carbides: A review on alternative binders, new consolidation techniques and advanced characterization

Last decade insights on cemented carbides: A review on alternative binders, new consolidation techniques and advanced characterization

A model assisted probability of detection for guided wave SHM systems: comparative study on recent statistical developments

Despite the potential benefits, industrial implementation of guided wave monitoring systems remains limited today. One of the reason behind this is the lack of consolidated reliability assessment techniques. Recent works clearly illustrated that the classical statistical methodology adopted from nondestructive evaluation to estimate POD is not directly applicable to structural health monitoring (SHM): the hypothesis of independence does not hold for the data obtained from permanently attached sensors and growing defects. The experimental determination of POD for SHM systems requires extensive and costly studies, in addition to the numerous representative structures. Involving numerical studies can complement experimental trials, inform POD evaluation and reduce this cost drastically. We propose in this work a comparative study to demonstrate the application of Model Assisted Probability Of Detection approach (MAPOD) for elastic guided wave monitoring systems. We apply classical and recently developed statistical methods proposed in the literature, using simulated data obtained thanks to the CIVA SHM module. The MAPOD estimation is validated in comparison to experimental studies.

Impact of soil density on biomineralization using EICP and MICP techniques for earthen sites consolidation

Enzyme-induced calcium carbonate precipitation (EICP) and microbially-induced calcium carbonate precipitation (MICP) techniques represent emerging trends in soil stabilization. However, the impact of soil density on biomineralization, particularly in historical earthen sites, remains unclear. This study compares the consolidation effects of EICP and MICP on cylindrical samples (10 cm × 5 cm) with three densities (1.5 g/cm3, 1.6 g/cm3, and 1.7 g/cm3) derived from the soil near the UNESCO World Cultural Heritage Site of Suoyang Ancient City, Gansu Province, China. Results showed that calcium carbonate production increased across all densities through bio-cementation, with higher densities producing more calcium carbonate. MICP-treated specimens exhibited larger increases in calcium carbonate production compared to those treated with EICP. Specimens with a density of 1.7 g/cm³ showed a wave velocity increase of 3.26% (EICP) and 7.13% (MICP), and an unconfined compressive strength increase of 8% (EICP) and 26% (MICP). These strength increases correlated with the generation of calcium carbonate. The findings suggest that biomineralization can be effectively utilized for in situ consolidation of earthen sites, emphasizing the importance of considering soil density in biologically-based conservation technologies. Furthermore, MICP shows potential advantages over EICP in providing stronger, compatible and more sustainable soil reinforcement.

An Innovative, Lightweight, and Sustainable Solution for the Integrated Seismic Energy Retrofit of Existing Masonry Structures

A large percentage of existing building stock in Italy and throughout Europe is ageing and no longer complies with current regulations, particularly in terms of sustainability. For these reasons, an urgent consolidation plan is needed to ensure an increase in both seismic response and energy response. Indeed, these constructions were built before the actual technical codes, and currently, they are not able to withstand seismic actions. Meanwhile, they are subject to thermal dispersions that could be due to the use of materials with poor properties or construction errors. Among the numerous consolidation techniques, an innovative solution consisting of a coating system has appeared on the construction market in recent decades. It is an integrated solution that simultaneously improves the seismic and energy behaviour of the building. The paper proposes the evaluation of this lightweight and sustainable solution through some experimental tests which were performed at the National Institute for Research and Development in Constructions, located in the city of Timişoara (Romania). The tests were aimed to investigate the out-of-plane behaviour of a masonry wall (1.20 m × 2.40 m × 0.60 m) obtained by combining two smaller panels with mortar and subjecting them to constant vertical force and pushing by an increasing horizontal one. Its response was assessed before and after the application of extruded aluminium alloy base profiles belonging to the system under study.

Exploring electron transfer: Bioinspired, biomimetics, and bioelectrochemical systems for sustainable energy and Value-Added compound synthesis

Electron transfer (ET) is a fundamental process that underlies various phenomena in physics, chemistry, and biology. Understanding ET mechanisms is crucial for developing sustainable energy solutions and synthesizing value-added compounds efficiently. In this context, the present review provides the fundamental aspects of ET involving bioinspired, biomimetics, and biological entities and its significance for sustainable energy and green electrosynthesis fields. Among the theoretical and experimental cornerstones, Marcus Theory, electronic conductance, computational modeling, biomolecular thermodynamics, electrochemical and kinetic theories, protein film voltammetry, and the emergence of in situ and operando techniques are explored. Theoretical modeling is vital for understanding and predicting ET processes. Additionally, the significance of experimental techniques for investigating the ET process in biological entities and interfaces is discussed. Protein film voltammetry is a valuable and consolidated technique for studying ET processes at the protein-electrode interface, whereas in situ and operando techniques for interrogating ET processes in real time provide insights into the dynamics and mechanisms of ET. The concept of quantum conductance in biological structures is addressed, evidencing a trend and power of single-entity analysis. Aspects of extracellular and interfacial ET processes are presented and discussed in the electrochemical energy conversion systems. A deep understanding of these processes can improve the design of efficient bioinspired catalysts. Therefore, this multidisciplinary work aims to fill the gaps between different scientific fields related to ET involving bioentities to develop innovative energy and value-added compound synthesis solutions.

Reactive cold sintering of dense barium sulfate ceramics for high-reliability chip packaging in integrated circuits

Reactive cold sintering (RCS) is an innovative ceramic consolidation technique that combines a low-temperature reaction with the cold sintering process. In this work, equimolar (CH3COO)2Ba and (NH4)2SO4 were homogeneously mixed to obtain a reactive activator abbreviated as RA and then added to barium sulfate (BaSO4) powder obtaining BaSO4–xwt%RA (x = 5, 7.5, 10, 12.5, and 15). Dense (>96 % theoretical) BaSO4 ceramics were successfully fabricated via RCS of BaSO4–xwt%RA at 200℃ with a constantly applied pressure of 250 MPa. The Woolfrey-Bannister method provided quantitative insights into the activation energy, indicating that RA effectively reduced the energy required for densification. The Vickers hardness (1.76 GPa) and coefficient of thermal expansion (CTE, 18.8 ppm/°C) of the RCSed BaSO4 ceramics were comparable to the high-temperature (850 °C) sintered counterparts. Moreover, finite element analyses confirmed the high CTE value of the RCSed BaSO4 ceramics holds great promise for high-reliability chip packaging applications.

Verification of passivity condition of carbon steel under cathodic protection through in-situ spectroscopy

Cathodic protection (CP) is a consolidated technique involving the circulation of a cathodic current (iprot) from an anode to a structure. This causes the electrode alkalisation depending on iprot and on the kinetics of the diffusive motion of ions, influencing the surface state of the metal. In this paper, the surface condition of carbon steel under CP has been studied through in-situ Raman spectroscopy and atomic force microscopy (AFM), combined with electrochemical impedance spectroscopy (EIS), for a protection potential (Eprot) of − 1.1 V/CSE (Cu/CuSO4). Results show that depending on alkalisation, Fe3O4 converts to other ferric species like γ-Fe2O3 and α-FeOOH.

Friction stir consolidation for recycling AA6061 chips with its metal flow investigation for billet production

This study aims to produce a billet from AA6061 chips recycling by adopting friction stir consolidation (FSC) technique. AA6061 was used to form different shapes of chips with a thickness of 1 mm. The billet was produced by stacking and forming the chips inside the cylindrical die adopting the friction stir consolidation technique with a rotating tool. Three parameters were considered: preheating time, rotating speed of tool, and depth of plunging, with three levels for each parameter. A Taguchi strategy was implemented to design the experiments (DOE) and analyse the billet properties. The billet cross-section was examined by the optical and scanning electron microscope examinations. The billet was successfully produced by recycling the AA6061 chips. The production mechanism occurred by grains elongating, metal flow, and welding the chip’s boundaries with the applied pressure and input heat. Minor defects such as cracks and porosities were found in the entire surfaces of the billets. The presence of the defects relied on the process variables. The billet's surface appearance or quality depended on the tool's depth of plunging. The tool's revolving speed and depth of plunge determined the process's temperature. The depth of plunging was the most influential parameter on the surface quality of the billets. Raising the depth of plunging and rotational speed generated higher heat input, which increased the weldability between the chip’s boundaries and reduced the surface defects. Regions of sufficient input heat during the stir forming process exhibited complete welding between the chip’s boundaries without defects. The best forming condition achieved among all runs was at (1800 rpm rotational speed, 1 min. preheating time, and 35 mm depth of plunging). For the first time, the friction stir consolidation process produced the billets by recycling the AA6061 chips without any material loss.

The use of terrestrial monoscopic time-lapse cameras for surveying glacier flow velocity

Glacier flow velocity is crucial information to assess the impact of global warming on glaciers since it is related to the ice thickness, its variations provide information on mass balance and, in general, on the current state of glacier “health”. Moreover, flow anomalies are often an indicator of glacier instabilities. Therefore, more attention has been dedicated to surveying glacier kinematics. Historically, flow velocity was the first quantitative variable measured on glaciers since the 19th century. In the last decades, terrestrial monoscopic time-lapse digital cameras have permitted to conduct automatic surveying at high spatial and temporal resolutions using digital image correlation. Even though terrestrial time-lapse imagery is currently a consolidated technique in glacier monitoring, possible strategies, limitations and potentialities have never been systematically reviewed. This work aims to illustrate the typical procedures required to monitor glacier flow velocity using terrestrial monoscopic time-lapse cameras. We describe possible inconveniences that can arise during the survey and provide some guidelines to minimise such issues. We present six study cases in the European Alps (Mont Blanc and Bernina massifs) that feature different monitoring equipment, site geometry and glacier morphodynamics to illustrate possible solutions for terrestrial imagery monitoring. The results of this review highlight the high benefit-to-cost ratio of terrestrial time-lapse cameras in glacier flow surveying.

Sandstone chemical consolidation and wettability improvement using furan polymer-based nanofluid

The oil and gas industry faces a challenge in meeting global energy demand due to sand production in unconsolidated or semi-consolidated reservoirs, leading to equipment wear, production instability, and significant financial burdens. Mechanical and chemical sand control methods are being used among which chemical sand consolidation techniques have emerged as a promising solution. In this research, furan polymer-based nanofluid is investigated as a chemical consolidant to explore its intriguing properties and characteristics and how the quantity of nanoparticles influences the fundamental properties of curing resin and wettability while pioneering a groundbreaking approach to enhancing regaining permeability. According to the findings, a substantial boost in core compressive strength has been achieved as well as an impressive increase in re-permeability, especially for the foam injection case, by the meticulous optimization of nanofluid composition. The results include a remarkable regain permeability of 91.37%, a robust compressive strength of 1812.05 psi, and a noteworthy 15.32-degree shift towards water-wet wettability. Furthermore, silica nanoparticles were incorporated to enhance the thermal stability of the fluid, rendering it more adaptable to higher temperatures. Therefore, Furan polymer-based nanofluid is not only expected to present a solution to the challenge of sand production in the oil and gas industry but also to provide operational sustainability.

FPHO: Fractional Pelican Hawks optimization based container consolidation in CaaS cloud

AbstractContainers in cloud computing provide a logical packaging technique for applications to be isolated from the computing environment in which they actually execute, allowing for efficient sharing of memory, processor, storage, and network resources at the Operating System (OS) level. Since they are so compact, container‐based clouds have recently gained significant popularity. In order to maximize resource usage and minimize energy consumption, the container consolidation technique is widely employed in the cloud environment. This work introduces container consolidation in cloud computing that exploits Fractional Pelican Hawks Optimization (FPHO). In Container as a Service (CaaS) model, containers are placed in the Virtual Machines (VMs), and virtual machines are hosted in Physical Machines (PMs) or servers. The proposed method for container consolidation consists of two modules, namely, the host status module and the consolidation module. In the host status module, the PM's load is predicted using Long Short Term Memory (LSTM) and checked whether the PM is overloaded or underloaded using a threshold. If it is overloaded, the container selection algorithm is performed, and the migration list is also generated. In the consolidation module, the created migration list which is employed for the destination list to be created by an overloaded destination selector. In the same way, the underloaded list is also generated by the underloaded destination selector. Finally, the container and VM migration is carried out by considering the multi‐objectives such as predicted load, migration cost, resource utilization, energy consumption, network, and bandwidth which are optimally selected by the proposed FHPO. Here, FHPO is the combination of Fractional Pelican Optimization (FPO) and Fire Hawk Optimizer (FHO). The designed model achieved the measures with minimum energy consumption, resource utilization, Service Level Agreement (SLA), and Makespan as 0.066, 0.019, 0.054, and 0.066, respectively for setup one.

Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies

As landmines and other unexploded ordnances (UXOs) present a great risk to civilians and infrastructure, humanitarian demining is an essential component of any post-conflict reconstruction. This paper introduces the Minefield Observatory, a novel web-based datastore service that semantically integrates diverse data in humanitarian demining to comprehensively and formally describe suspected minefields. Because of the high heterogeneity and isolation of the available minefield datasets, extracting relevant information to determine the optimal course of demining efforts is time-consuming, labor-intensive and requires highly specialized knowledge. Data consolidation and artificial intelligence techniques are used to convert unstructured data sources and store them in an ontology-based knowledge database that can be efficiently accessed through a Semantic Web application serving as the Minefield Observatory user interface. The MINEONT+ ontology was developed to integrate diverse mine scene information obtained through non-technical surveys and remote sensing, such as aerial and hyperspectral satellite imagery, indicators of mine presence and absence, contextual data, terrain analysis information, and battlefield reports. The Minefield Observatory uses the Microdata API to embed this dataset into dynamic HTML5 content, allowing seamless usage in a user-centric web tool. A use-case example was provided demonstrating the viability of the proposed approach.

Energy and Performance Centric Resource Allocation Framework in Virtual Machine Consolidation Using Reinforcement Learning Approach

Abstract:: Virtual machines are used to reduce cloud platform application performance, management costs, and access irregularities. Virtual machines are frequently vulnerable to delays, overburdening workloads, and other obstacles while consolidating and migrating servers. To significantly disperse loads among virtual machines, dynamic consolidation techniques are implemented to control energy dissipation, monitor overloading, and address underloading problems. Background:: The process of consolidation involves more calculations and resources in order to transfer services between virtual machines, provided that Service Level Agreements are observed. Methods:: The suggested approach promotes the use of cutting-edge architecture to combine virtual machines, and, therefore, strike a balance between performance and energy requirements. The main design considerations for the suggested Dynamic Weightage algorithm, which includes the clustering approach in relation to reinforcement learning approaches, are overall resource needs and Performance to Power Ratio (PPR). A cluster of ideal virtual machines is created, and resources are distributed according to performance and energy requirements. Virtual machine resource requests are converted into a matching relationship factor, which represents the individual hosts while taking PPR into account. The overall workload associated with virtual machine consolidation is also provided by these estimations. It is noted that there is little energy trade-off and that performance is maintained at a nominal level across the cluster. The architecture is put into practice throughout offline platforms, which are dispersed ecosystems that allow for increased system performance and scaling. Results:: The CloudSim simulator is used to validate the system using datasets that are obtained from PlanetLab. According to the data, energy saving has produced yields of up to 47% and promising quality of service attributes. Conclusion:: The validation of the system is performed using the CloudSim simulator with datasets from PlanetLab. The results indicate significant energy conservation, up to 47%, along with promising quality of service parameters. The proposed architecture is compared with other state-of-the-art algorithms for distributed architectures and heterogeneous environments, showcasing its efficiency. The conclusion emphasizes the prioritization of VM consolidation and energy efficiency in the proposed architecture, which has been tested on a Proliant G7- based data center using a variety of hosts. Notably, the CloudSim Toolkit is highlighted as outperforming OpenStack-based techniques in simulation results.

FROM 3D METRIC SURVEY TO HBIM MODEL. TESTING OF DIFFERENT SCAN2BIM APPROACHES FOR THE ARCHAEOLOGICAL DOCUMENTATION

Abstract. The research presented in this work is focused on describing part of the activities related to the 1st edition of the SUNRISE Summer School (Seashore and UNderwater documentation of aRchaeological herItage palimpSests and Environment) and a comprehensive approach to the documentation of an archaeological site. In the paper data acquisition and processing will be described in detail, together with the design of the survey project and the main specifications of the sensors and techniques adopted. The 3D metric data derived from the use of these consolidated geomatics techniques were validated during the processing and used as the basis for the generation of other added-value products: traditional 2D drawings and an HBIM model. More specifically, two different approaches for the modelling phase were followed: a more consolidated approach driven by the 2D representation and a more experimental one that foresaw NURBS modelling from the point clouds. The pros and cons of both approaches will be analyzed, and a metric validation of each strategy will be presented. In the paper's conclusions, some considerations are summarized on the use of HBIM for the management of the archaeological data, together with some further perspectives.