Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

Orthogonality defect and reduced search-space size for solving integer least-squares problems

In the context of ambiguity resolution (AR) of Global Navigation Satellite Systems (GNSS), decorrelation among entries of an ambiguity vector, integer ambiguity search and ambiguity validations are three standard procedures for solving integer least-squares problems. This paper contributes to AR issues from three aspects. Firstly, the orthogonality defect is introduced as a new measure of the performance of ambiguity decorrelation methods, and compared with the decorrelation number and with the condition number which are currently used as the judging criterion to measure the correlation of ambiguity variance-covariance matrix. Numerically, the orthogonality defect demonstrates slightly better performance as a measure of the correlation between decorrelation impact and computational efficiency than the condition number measure. Secondly, the paper examines the relationship of the decorrelation number, the condition number, the orthogonality defect and the size of the ambiguity search space with the ambiguity search candidates and search nodes. The size of the ambiguity search space can be properly estimated if the ambiguity matrix is decorrelated well, which is shown to be a significant parameter in the ambiguity search progress. Thirdly, a new ambiguity resolution scheme is proposed to improve ambiguity search efficiency through the control of the size of the ambiguity search space. The new AR scheme combines the LAMBDA search and validation procedures together, which results in a much smaller size of the search space and higher computational efficiency while retaining the same AR validation outcomes. In fact, the new scheme can deal with the case there are only one candidate, while the existing search methods require at least two candidates. If there are more than one candidate, the new scheme turns to the usual ratio-test procedure. Experimental results indicate that this combined method can indeed improve ambiguity search efficiency for both the single constellation and dual constellations respectively, showing the potential for processing high dimension integer parameters in multi-GNSS environment.

Advanced numerical characterization of silicon with defect by nanoindentation

Nano silicon is widely used as the essential element of complementary metal–oxide–semiconductor (CMOS) and solar cells. It is recognized that today, large portion of world economy is built on electronics products and related services. Due to the accessible fossil fuel running out quickly, there are increasing numbers of researches on the nano silicon solar cells. The further improvement of higher performance nano silicon components requires characterizing the material properties of nano silicon. Specially, when the manufacturing process scales down to the nano level, the advanced components become more and more sensitive to the various defects induced by the manufacturing process. It is known that defects in mono-crystalline silicon have significant influence on its properties under nanoindentation. However, the cost involved in the practical nanoindentation as well as the complexity of preparing the specimen with controlled defects slow down the further research on mechanical characterization of defected silicon by experiment. Therefore, in current study, the molecular dynamics (MD) simulations are employed to investigate the mono-crystalline silicon properties with different pre-existing defects, especially cavities, under nanoindentation. Parametric studies including specimen size and loading rate, are firstly conducted to optimize computational efficiency. The optimized testing parameters are utilized for all simulation in defects study. Based on the validated model, different pre-existing defects are introduced to the silicon substrate, and then a group of nanoindentation simulations of these defected substrates are carried out. The simulation results are carefully investigated and compared with the perfect Silicon substrate which used as benchmark. It is found that pre-existing cavities in the silicon substrate obviously influence the mechanical properties. Furthermore, pre-existing cavities can absorb part of the strain energy during loading, and then release during unloading, which possibly causes less plastic deformation to the substrate. However, when the pre-existing cavities is close enough to the deformation zone or big enough to exceed the bearable stress of the crystal structure around the spherical cavity, the larger plastic deformation occurs which leads the collapse of the structure. Meanwhile, the influence exerted on the mechanical properties of silicon substrate depends on the location and size of the cavity. Substrate with larger cavity size or closer cavity position to the top surface, usually exhibits larger reduction on Young’s modulus and hardness.

The rationale for using microscopic units of a donor matrix in cartilage defect repair

The efficacy of existing articular cartilage defect repair strategies are limited. Native cartilage tissue forms via a series of exquisitely orchestrated morphogenic events spanning through gestation into early childhood. However, defect repair must be achieved in a non-ideal microenvironment over an accelerated time-frame compatible with the normal life of an adult patient. Scaffolds formed from decellularized tissues are commonly utilized to enable the rapid and accurate repair of tissues such as skin, bladder and heart valves. The intact extracellular matrix remaining following the decellularization of these relatively low-matrix-density tissues is able to rapidly and accurately guide host cell repopulation. By contrast, the extraordinary density of cartilage matrix limits both the initial decellularization of donor material as well as its subsequent repopulation. Repopulation of donor cartilage matrix is generally limited to the periphery, with repopulation of lacunae deeper within the matrix mass being highly inefficient. Herein, we review the relevant literature and discuss the trend toward the use of decellularized donor cartilage matrix of microscopic dimensions. We show that 2-µm microparticles of donor matrix are rapidly integrate with articular chondrocytes, forming a robust cartilage-like composites with enhanced chondrogenic gene expression. Strategies for the clinical application of donor matrix microparticles in cartilage defect repair are discussed.

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

A bi-lineage conducive scaffold for osteochondral defect regeneration

Because cartilage and bone tissues have different lineage-specific biological properties, it is challenging to fabricate a single type of scaffold that can biologically fulfill the requirements for regeneration of these two lineages simultaneously within osteochondral defects. To overcome this challenge, a lithium-containing mesoporous bioglass (Li-MBG) scaffold is developed. The efficacy and mechanism of Li-MBG for regeneration of osteochondral defects are systematically investigated. Histological and micro-CT results show that Li-MBG scaffolds significantly enhance the regeneration of subchondral bone and hyaline cartilage-like tissues as compared to pure MBG scaffolds, upon implantation in rabbit osteochondral defects for 8 and 16 weeks. Further investigation demonstrates that the released Li+ ions from the Li-MBG scaffolds may play a key role in stimulating the regeneration of osteochondral defects. The corresponding mechanistic pathways involve Li+ ions enhancing the proliferation and osteogenic differentiation of bone mesenchymal stem cells (BMSCs) through activation of the Wnt signalling pathway, as well as Li+ ions protecting chondrocytes and cartilage tissues from the inflammatory osteoarthritis (OA) environment through activation of autophagy. These findings suggest that the incorporation of Li+ ions into bioactive MBG scaffolds is a viable strategy for fabricating bi-lineage conducive scaffolds that enhance regeneration of osteochondral defects.

Evaluation of BMP-2 gene-activated muscle grafts for cranial defect repair

Large, osseous, segmental defects heal poorly. Muscle has a propensity to form bone when exposed to an osteogenic stimulus such as that provided by transfer and expression of cDNA encoding bone morphogenetic protein-2 (BMP-2). The present study evaluated the ability of genetically modified, autologous muscle to heal large cranial defects in rats. Autologous grafts (8 mm � 2 mm) were punched from the biceps femoris muscle and transduced intraoperatively with recombinant adenovirus vector containing human BMP-2 or green fluorescent protein cDNA. While the muscle biopsies were incubating with the vector, a central parietal 8 mm defect was surgically created in the calvarium of the same animal. The gene-activated muscle graft was then implanted into the cranial defect. After 8 weeks, crania were examined radiographically, histologically, and by micro-computed tomography and dual energy X-ray absorptiometry. Although none of the defects were completely healed in this time, muscle grafts expressing BMP-2 deposited more than twice as much new bone as controls. Histology confirmed the anatomical integrity of the newly formed bone, which was comparable in thickness and mineral density to the original cranial bone. This study confirms the in vivo osteogenic properties of genetically modified muscle and suggests novel strategies for healing bone. � 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:1095–1102, 2012

Time kinetics of bone defect healing in response to BMP-2 and GDF-5 characterised by in vivo biomechanics

This study reports that treatment of osseous defects with different growth factors initiates distinct rates of repair. We developed a new method for monitoring the progression of repair, based upon measuring the in vivo mechanical properties of healing bone. Two different members of the bone morphogenetic protein (BMP) family were chosen to initiate defect healing: BMP-2 to induce osteogenesis, and growth-and-differentiation factor (GDF)-5 to induce chondrogenesis. To evaluate bone healing, BMPs were implanted into stabilised 5 mm bone defects in rat femurs and compared to controls. During the first two weeks, in vivo biomechanical measurements showed similar values regardless of the treatment used. However, 2 weeks after surgery, the rhBMP-2 group had a substantial increase in stiffness, which was supported by the imaging modalities. Although the rhGDF-5 group showed comparable mechanical properties at 6 weeks as the rhBMP-2 group, the temporal development of regenerating tissues appeared different with rhGDF-5, resulting in a smaller callus and delayed tissue mineralisation. Moreover, histology showed the presence of cartilage in the rhGDF-5 group whereas the rhBMP-2 group had no cartilaginous tissue. Therefore, this study shows that rhBMP-2 and rhGDF-5 treated defects, under the same conditions, use distinct rates of bone healing as shown by the tissue mechanical properties. Furthermore, results showed that in vivo biomechanical method is capable of detecting differences in healing rate by means of change in callus stiffness due to tissue mineralisation.

Ability of recombinant human bone morphogenetic protein 2 to enhance bone healing in the presence of tobramycin : evaluation in a rat segmental defect model

Objective To determine whether locally applied tobramycin influences the ability of recombinant human bone morphogenetic protein 2 (rhBMP-2) to heal a segmental defect in the rat femur. Methods The influence of tobramycin on the osteogenic differentiation of mesenchymal stem cells was first evaluated in vitro. For the subsequent, in vivo experiments, a 5-mm segmental defect was created in the right femur of each of 25 Sprague-Dawley rats and stabilized with an external fixator and four Kirschner wires. Rats were divided in four groups: empty control, tobramycin (11 mg)/absorbable collagen sponge, rhBMP-2 (11 μg)/absorbable collagen sponge, and rhBMP-2/absorbable collagen sponge with tobramycin. Bone healing was monitored by radiography at 3 and 8 weeks. Animals were euthanized at 8 weeks and the properties of the defect were compared with the intact contralateral femur. Bone formation in the defect region was assessed by dual-energy x-ray absorptiometry, microcomputed tomography, histology, and mechanical testing. Results Tobramycin exerted a dose-dependent inhibition of alkaline phosphatase induction and calcium deposition by mesenchymal stem cells cultured under osteogenic conditions. The inhibition was reversed in the presence of 500 ng/mL of rhBMP-2. Segmental defects in the rat femora failed to heal in the absence of rhBMP-2. Tobramycin exerted no inhibitory effects on the ability of rhBMP-2 to heal these defects and increased the bone area of the defects treated with rhBMP-2. Data obtained from all other parameters of healing, including dual-energy x-ray absorptiometry, microcomputed tomography, histology, and mechanical testing, were unaffected by tobramycin. Conclusions Although our in vitro results suggested that tobramycin inhibits the osteogenic differentiation of mesenchymal stem cells, this could be overcome by rhBMP-2. Tobramycin did not impair the ability of rhBMP-2 to heal critical-sized femoral defects in rats. Indeed, bone area was increased by nearly 20% in the rhBMP-2 group treated with tobramycin. This study shows that locally applied tobramycin can be used in conjunction with rhBMP-2 to enhance bone formation at fracture sites.

Multiphasic construct studied in an ectopic osteochondral defect model

In vivo osteochondral defect models predominantly consist of small animals, such as rabbits. Although they have an advantage of low cost and manageability, their joints are smaller and more easily healed compared with larger animals or humans. We hypothesized that osteochondral cores from large animals can be implanted subcutaneously in rats to create an ectopic osteochondral defect model for routine and high-throughput screening of multiphasic scaffold designs and/or tissue-engineered constructs (TECs). Bovine osteochondral plugs with 4 mm diameter osteochondral defect were fitted with novel multiphasic osteochondral grafts composed of chondrocyte-seeded alginate gels and osteoblast-seeded polycaprolactone scaffolds, prior to being implanted in rats subcutaneously with bone morphogenic protein-7. After 12 weeks of in vivo implantation, histological and micro-computed tomography analyses demonstrated that TECs are susceptible to mineralization. Additionally, there was limited bone formation in the scaffold. These results suggest that the current model requires optimization to facilitate robust bone regeneration and vascular infiltration into the defect site. Taken together, this study provides a proof-of-concept for a high-throughput osteochondral defect model. With further optimization, the presented hybrid in vivo model may address the growing need for a cost-effective way to screen osteochondral repair strategies before moving to large animal preclinical trials.

An instrument to assess the obesogenic environment of child care centers

OBJECTIVES To describe protocol and interobserver agreements of an instrument to evaluate nutrition and physical activity environments at child care. METHODS Interobserver data were collected from 9 child care centers, through direct observation and document review (17 observer pairs). RESULTS Mean agreement between observer pairs was 87.26% and 79.29% for the observation and document review, respectively. Items with lower agreement were primarily staff behavior, counting across the day/week, and policy classifications. CONCLUSIONS Although some revisions are required, the interobserver agreement for the environment and policy assessment and observation (EPAO instrument) appears to be quite good for assessing the nutrition and physical activity environment of child care centers.

Defect healing and enhanced nucleation of carbon nanotubes by low-energy ion bombardment

Structural defects inevitably appear during the nucleation event that determines the structure and properties of single-walled carbon nanotubes. By combining ion bombardment experiments with atomistic simulations we reveal that ion bombardment in a suitable energy range allows these defects to be healed resulting in an enhanced nucleation of the carbon nanotube cap. The enhanced growth of the nanotube cap is explained by a nonthermal ion-induced graphene network restructuring mechanism.

Reducing bubble defect on the outsole production process in the footwear manufacturing industry

The purpose of this study is to discover the significant factors causing the bubble defect on the outsoles manufactured by the Case Company. The bubble defect occurs approximately 1.5 per cent of the time or in 36 pairs per day. To understand this problem, experimental studies are undertaken to identify various factors such as injector temperature, mould temperature; that affects the production of waste. The work presented in this paper comprises a review of the relevant literature on the Six Sigma DMAIC improvement process, quality control tools, and the design of the experiments. After the experimentation following the Six Sigma process, the results showed that the defect occurred in approximately 0.5 per cent of the products or in 12 pairs per day; this decreased the production cost from 6,120 AUD per month to 2,040 AUD per month. This research aimed to reduce the amount of waste in men’s flat outsoles. Hence, the outcome of research presented in this paper should be used as a guide for applying the appropriate process for each type of outsole.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.