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In a recent paper, the Lefschetz number for endomorphisms (modulo trace class operators) of sequences of trace class curvature was introduced. We show that this is a well defined, canonical extension of the classical Lefschetz number and establish the homotopy invariance of this number. Moreover, we apply the results to show that the Lefschetz fixed point formula holds for geometric quasiendomorphisms of elliptic quasicomplexes.
Background Transcatheter aortic-valve implantation (TAVI) is an established alternative therapy in patients with severe aortic stenosis and a high surgical risk. Despite a rapid growth in its use, very few data exist about the efficacy of cardiac rehabilitation (CR) in these patients. We assessed the hypothesis that patients after TAVI benefit from CR, compared to patients after surgical aortic-valve replacement (sAVR).
Methods From September 2009 to August 2011, 442 consecutive patients after TAVI (n=76) or sAVR (n=366) were referred to a 3-week CR. Data regarding patient characteristics as well as changes of functional (6-min walk test. 6-MWT), bicycle exercise test), and emotional status (Hospital Anxiety and Depression Scale) were retrospectively evaluated and compared between groups after propensity score adjustment.
Results Patients after TAVI were significantly older (p<0.001), more female (p<0.001), and had more often coronary artery disease (p=0.027), renal failure (p=0.012) and a pacemaker (p=0.032). During CR, distance in 6-MWT (both groups p0.001) and exercise capacity (sAVR p0.001, TAVI p0.05) significantly increased in both groups. Only patients after sAVR demonstrated a significant reduction in anxiety and depression (p0.001). After propensity scores adjustment, changes were not significantly different between sAVR and TAVI, with the exception of 6-MWT (p=0.004).
Conclusions Patients after TAVI benefit from cardiac rehabilitation despite their older age and comorbidities. CR is a helpful tool to maintain independency for daily life activities and participation in socio-cultural life.
Background: Chronic kidney disease (CKD) is a frequent comorbidity among elderly patients and those with cardiovascular disease. CKD carries prognostic relevance. We aimed to describe patient characteristics, risk factor management and control status of patients in cardiac rehabilitation (CR), differentiated by presence or absence of CKD.
Design and methods: Data from 92,071 inpatients with adequate information to calculate glomerular filtration rate (GFR) based on the Cockcroft-Gault formula were analyzed at the beginning and the end of a 3-week CR stay. CKD was defined as estimated GFR <60 ml/min/1.73 m(2).
Results: Compared with non-CKD patients, CKD patients were significantly older (72.0 versus 58.0 years) and more often had diabetes mellitus, arterial hypertension, and atherothrombotic manifestations (previous stroke, peripheral arterial disease), but fewer were current or previous smokers had a CHD family history. Exercise capacity was much lower in CKD (59 vs. 92Watts). Fewer patients with CKD were treated with percutaneous coronary intervention (PCI), but more had coronary artery bypass graft (CABG) surgery. Patients with CKD compared with non-CKD less frequently received statins, acetylsalicylic acid (ASA), clopidogrel, beta blockers, and angiotensin converting enzyme (ACE) inhibitors, and more frequently received angiotensin receptor blockers, insulin and oral anticoagulants. In CKD, mean low density lipoprotein cholesterol (LDL-C), total cholesterol, and high density lipoprotein cholesterol (HDL-C) were slightly higher at baseline, while triglycerides were substantially lower. This lipid pattern did not change at the discharge visit, but overall control rates for all described parameters (with the exception of HDL-C) were improved substantially. At discharge, systolic blood pressure (BP) was higher in CKD (124 versus 121 mmHg) and diastolic BP was lower (72 versus 74 mmHg). At discharge, 68.7% of CKD versus 71.9% of non-CKD patients had LDL-C <100 mg/dl. Physical fitness on exercise testing improved substantially in both groups. When the Modification of Diet in Renal Disease (MDRD) formula was used for CKD classification, there was no clinically relevant change in these results.
Conclusion: Within a short period of 3-4 weeks, CR led to substantial improvements in key risk factors such as lipid profile, blood pressure, and physical fitness for all patients, even if CKD was present.
The International Project for the Evaluation of Educational Achievement (IEA) was formed in the 1950s (Postlethwaite, 1967). Since that time, the IEA has conducted many studies in the area of mathematics, such as the First International Mathematics Study (FIMS) in 1964, the Second International Mathematics Study (SIMS) in 1980-1982, and a series of studies beginning with the Third International Mathematics and Science Study (TIMSS) which has been conducted every 4 years since 1995. According to Stigler et al. (1999), in the FIMS and the SIMS, U.S. students achieved low scores in comparison with students in other countries (p. 1). The TIMSS 1995 “Videotape Classroom Study” was therefore a complement to the earlier studies conducted to learn “more about the instructional and cultural processes that are associated with achievement” (Stigler et al., 1999, p. 1). The TIMSS Videotape Classroom Study is known today as the TIMSS Video Study. From the findings of the TIMSS 1995 Video Study, Stigler and Hiebert (1999) likened teaching to “mountain ranges poking above the surface of the water,” whereby they implied that we might see the mountaintops, but we do not see the hidden parts underneath these mountain ranges (pp. 73-78). By watching the videotaped lessons from Germany, Japan, and the United States again and again, they discovered that “the systems of teaching within each country look similar from lesson to lesson. At least, there are certain recurring features [or patterns] that typify many of the lessons within a country and distinguish the lessons among countries” (pp. 77-78). They also discovered that “teaching is a cultural activity,” so the systems of teaching “must be understood in relation to the cultural beliefs and assumptions that surround them” (pp. 85, 88). From this viewpoint, one of the purposes of this dissertation was to study some cultural aspects of mathematics teaching and relate the results to mathematics teaching and learning in Vietnam. Another research purpose was to carry out a video study in Vietnam to find out the characteristics of Vietnamese mathematics teaching and compare these characteristics with those of other countries. In particular, this dissertation carried out the following research tasks: - Studying the characteristics of teaching and learning in different cultures and relating the results to mathematics teaching and learning in Vietnam - Introducing the TIMSS, the TIMSS Video Study and the advantages of using video study in investigating mathematics teaching and learning - Carrying out the video study in Vietnam to identify the image, scripts and patterns, and the lesson signature of eighth-grade mathematics teaching in Vietnam - Comparing some aspects of mathematics teaching in Vietnam and other countries and identifying the similarities and differences across countries - Studying the demands and challenges of innovating mathematics teaching methods in Vietnam – lessons from the video studies Hopefully, this dissertation will be a useful reference material for pre-service teachers at education universities to understand the nature of teaching and develop their teaching career.
Moderne Kraftfahrzeuge verfügen über eine Vielzahl an Sensoren, welche für einen reibungslosen technischen Betrieb benötigt werden. Hierzu zählen neben fahrzeugspezifischen Sensoren (wie z.B. Motordrehzahl und Fahrzeuggeschwindigkeit) auch umweltspezifische Sensoren (wie z.B. Luftdruck und Umgebungstemperatur). Durch die zunehmende technische Vernetzung wird es möglich, diese Daten der Kraftfahrzeugelektronik aus dem Fahrzeug heraus für die verschiedensten Zwecke zu verwenden.
Die vorliegende Arbeit soll einen Beitrag dazu leisten, diese neue Art an massenhaften Daten im Sinne des Konzepts der „Extended Floating Car Data“ (XFCD) als Geoinformationen nutzbar zu machen und diese für raumzeitliche Visualisierungen (zur visuellen Analyse) anwenden zu können. In diesem Zusammenhang wird speziell die Perspektive des Umwelt- und Verkehrsmonitoring betrachtet, wobei die Anforderungen und Potentiale mit Hilfe von Experteninterviews untersucht werden. Es stellt sich die Frage, welche Daten durch die Kraftfahrzeugelektronik geliefert und wie diese möglichst automatisiert erfasst, verarbeitet, visualisiert und öffentlich bereitgestellt werden können. Neben theoretischen und technischen Grundlagen zur Datenerfassung und -nutzung liegt der Fokus auf den Methoden der kartographischen Visualisierung. Dabei soll der Frage nachgegangenen werden, ob eine technische Implementierung ausschließlich unter Verwendung von Open Source Software möglich ist. Das Ziel der Arbeit bildet ein zweigliedriger Ansatz, welcher zum einen die Visualisierung für ein exemplarisch gewähltes Anwendungsszenario und zum anderen die prototypische Implementierung von der Datenerfassung im Fahrzeug unter Verwendung der gesetzlich vorgeschriebenen „On Board Diagnose“-Schnittstelle und einem Smartphone-gestützten Ablauf bis zur webbasierten Visualisierung umfasst.
Dieser Artikel adressiert zwei bisher nur wenig untersuchte Aspekte der Führungsforschung: Führungsverhalten im öffentlichen Sektor und Faktoren die Führungsverhalten beeinflussen. Mittels einer Fallstudie in der Bundesagentur für Arbeit werden explorativ Hypothesen über Einflussfaktoren des Führungsverhaltens aufgestellt. Die Studie kommt zu der Erkenntnis, dass eine oftmals angenommene Führungslücke im öffentlichen Sektor nicht bestätigt werden kann. Für das ausgeprägte Führungsverhalten, das in der Fallstudie beobachtet wurde, wird als Determinante die besondere Ausgestaltung des Managementsystems der Bundesagentur für Arbeit verantwortlich gemacht. Dazu gehört unter anderem das Performance Management System sowie die Führungskräfteauswahl und -entwicklung. Die Arbeit schließt mit Empfehlungen für weitere Forschungsansätze auf dem Gebiet der Führungsforschung im öffentlichen Sektor.
Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks.
This study aims to further mechanistically understand toxic modes of action after chronic inorganic arsenic exposure. Therefore long-term incubation studies in cultured cells were carried out, to display chronically attained changes, which cannot be observed in the generally applied in vitro short-term incubation studies. Particularly, the cytotoxic, genotoxic and epigenetic effects of an up to 21 days incubation of human urothelial (UROtsa) cells with pico- to nanomolar concentrations of iAsIII and its metabolite thio-DMAV were compared. After 21 days of incubation, cytotoxic effects were strongly enhanced in the case of iAsIII and might partly be due to glutathione depletion and genotoxic effects on the chromosomal level. These results are in strong contrast to cells exposed to thio-DMAV. Thus, cells seemed to be able to adapt to this arsenical, as indicated among others by an increase in the cellular glutathione level. Most interestingly, picomolar concentrations of both iAsIII and thio-DMAV caused global DNA hypomethylation in UROtsa cells, which was quantified in parallel by 5-medC immunostaining and a newly established, reliable, high resolution mass spectrometry (HRMS)-based test system. This is the first time that epigenetic effects are reported for thio-DMAV; iAsIII induced epigenetic effects occur in at least 8000 fold lower concentrations as reported in vitro before. The fact that both arsenicals cause DNA hypomethylation at really low, exposure-relevant concentrations in human urothelial cells suggests that this epigenetic effect might contribute to inorganic arsenic induced carcinogenicity, which for sure has to be further investigated in future studies.
The complementary advantages of high-rate Global Positioning System (GPS) and accelerometer observations for measuring seismic ground motion have been recognised in previous research. Here we propose an approach of tight integration of GPS and accelerometer measurements. The baseline shifts of the accelerometer are introduced as unknown parameters and estimated by a random walk process in the Precise Point Positioning (PPP) solution. To demonstrate the performance of the new strategy, we carried out several experiments using collocated GPS and accelerometer. The experimental results show that the baseline shifts of the accelerometer are automatically corrected, and high precision coseismic information of strong ground motion can be obtained in real-time. Additionally, the convergence and precision of the PPP is improved by the combined solution.
Software maintenance encompasses any changes made to a software system after its initial deployment and is thereby one of the key phases in the typical software-engineering lifecycle. In software maintenance, we primarily need to understand structural and behavioral aspects, which are difficult to obtain, e.g., by code reading. Software analysis is therefore a vital tool for maintaining these systems: It provides - the preferably automated - means to extract and evaluate information from their artifacts such as software structure, runtime behavior, and related processes. However, such analysis typically results in massive raw data, so that even experienced engineers face difficulties directly examining, assessing, and understanding these data. Among other things, they require tools with which to explore the data if no clear question can be formulated beforehand. For this, software analysis and visualization provide its users with powerful interactive means. These enable the automation of tasks and, particularly, the acquisition of valuable and actionable insights into the raw data. For instance, one means for exploring runtime behavior is trace visualization. This thesis aims at extending and improving the tool set for visual software analysis by concentrating on several open challenges in the fields of dynamic and static analysis of software systems. This work develops a series of concepts and tools for the exploratory visualization of the respective data to support users in finding and retrieving information on the system artifacts concerned. This is a difficult task, due to the lack of appropriate visualization metaphors; in particular, the visualization of complex runtime behavior poses various questions and challenges of both a technical and conceptual nature. This work focuses on a set of visualization techniques for visually representing control-flow related aspects of software traces from shared-memory software systems: A trace-visualization concept based on icicle plots aids in understanding both single-threaded as well as multi-threaded runtime behavior on the function level. The concept’s extensibility further allows the visualization and analysis of specific aspects of multi-threading such as synchronization, the correlation of such traces with data from static software analysis, and a comparison between traces. Moreover, complementary techniques for simultaneously analyzing system structures and the evolution of related attributes are proposed. These aim at facilitating long-term planning of software architecture and supporting management decisions in software projects by extensions to the circular-bundle-view technique: An extension to 3-dimensional space allows for the use of additional variables simultaneously; interaction techniques allow for the modification of structures in a visual manner. The concepts and techniques presented here are generic and, as such, can be applied beyond software analysis for the visualization of similarly structured data. The techniques' practicability is demonstrated by several qualitative studies using subject data from industry-scale software systems. The studies provide initial evidence that the techniques' application yields useful insights into the subject data and its interrelationships in several scenarios.
Bolivia is one of the poorest countries in Latin America. This study analyzes whether rural poverty increases the incidence of food insecurity and whether food insecurity perpetuates the condition of poverty among the rural poor in Bolivia. In order to achieve this aim, the risks that households face and the capacity of households to implement coping strategies in order to mitigate vulnerability shocks are identified. We suggest that efforts by households to become food secure may be difficult in rural areas because of poverty and the vulnerability associated with a lack of physical assets, low levels of human capital, poor infrastructure, and poor health; as well as the precarious regional environment aggravating the severity of vulnerability to food insecurity.
In processing and data storage mainly ferromagnetic (FM) materials are being used. Approaching physical limits, new concepts have to be found for faster, smaller switches, for higher data densities and more energy efficiency. Some of the discussed new concepts involve the material classes of correlated oxides and materials with antiferromagnetic coupling. Their applicability depends critically on their switching behavior, i.e., how fast and how energy efficient material properties can be manipulated. This thesis presents investigations of ultrafast non-equilibrium phase transitions on such new materials. In transition metal oxides (TMOs) the coupling of different degrees of freedom and resulting low energy excitation spectrum often result in spectacular changes of macroscopic properties (colossal magneto resistance, superconductivity, metal-to-insulator transitions) often accompanied by nanoscale order of spins, charges, orbital occupation and by lattice distortions, which make these material attractive. Magnetite served as a prototype for functional TMOs showing a metal-to-insulator-transition (MIT) at T = 123 K. By probing the charge and orbital order as well as the structure after an optical excitation we found that the electronic order and the structural distortion, characteristics of the insulating phase in thermal equilibrium, are destroyed within the experimental resolution of 300 fs. The MIT itself occurs on a 1.5 ps timescale. It shows that MITs in functional materials are several thousand times faster than switching processes in semiconductors. Recently ferrimagnetic and antiferromagnetic (AFM) materials have become interesting. It was shown in ferrimagnetic GdFeCo, that the transfer of angular momentum between two opposed FM subsystems with different time constants leads to a switching of the magnetization after laser pulse excitation. In addition it was theoretically predicted that demagnetization dynamics in AFM should occur faster than in FM materials as no net angular momentum has to be transferred out of the spin system. We investigated two different AFM materials in order to learn more about their ultrafast dynamics. In Ho, a metallic AFM below T ≈ 130 K, we found that the AFM Ho can not only be faster but also ten times more energy efficiently destroyed as order in FM comparable metals. In EuTe, an AFM semiconductor below T ≈ 10 K, we compared the loss of magnetization and laser-induced structural distortion in one and the same experiment. Our experiment shows that they are effectively disentangled. An exception is an ultrafast release of lattice dynamics, which we assign to the release of magnetostriction. The results presented here were obtained with time-resolved resonant soft x-ray diffraction at the Femtoslicing source of the Helmholtz-Zentrum Berlin and at the free-electron laser in Stanford (LCLS). In addition the development and setup of a new UHV-diffractometer for these experiments will be reported.
In the field of disk-based parallel database management systems exists a great variety of solutions based on a shared-storage or a shared-nothing architecture. In contrast, main memory-based parallel database management systems are dominated solely by the shared-nothing approach as it preserves the in-memory performance advantage by processing data locally on each server. We argue that this unilateral development is going to cease due to the combination of the following three trends: a) Nowadays network technology features remote direct memory access (RDMA) and narrows the performance gap between accessing main memory inside a server and of a remote server to and even below a single order of magnitude. b) Modern storage systems scale gracefully, are elastic, and provide high-availability. c) A modern storage system such as Stanford's RAMCloud even keeps all data resident in main memory. Exploiting these characteristics in the context of a main-memory parallel database management system is desirable. The advent of RDMA-enabled network technology makes the creation of a parallel main memory DBMS based on a shared-storage approach feasible.
This thesis describes building a columnar database on shared main memory-based storage. The thesis discusses the resulting architecture (Part I), the implications on query processing (Part II), and presents an evaluation of the resulting solution in terms of performance, high-availability, and elasticity (Part III).
In our architecture, we use Stanford's RAMCloud as shared-storage, and the self-designed and developed in-memory AnalyticsDB as relational query processor on top. AnalyticsDB encapsulates data access and operator execution via an interface which allows seamless switching between local and remote main memory, while RAMCloud provides not only storage capacity, but also processing power. Combining both aspects allows pushing-down the execution of database operators into the storage system. We describe how the columnar data processed by AnalyticsDB is mapped to RAMCloud's key-value data model and how the performance advantages of columnar data storage can be preserved.
The combination of fast network technology and the possibility to execute database operators in the storage system opens the discussion for site selection. We construct a system model that allows the estimation of operator execution costs in terms of network transfer, data processed in memory, and wall time. This can be used for database operators that work on one relation at a time - such as a scan or materialize operation - to discuss the site selection problem (data pull vs. operator push). Since a database query translates to the execution of several database operators, it is possible that the optimal site selection varies per operator. For the execution of a database operator that works on two (or more) relations at a time, such as a join, the system model is enriched by additional factors such as the chosen algorithm (e.g. Grace- vs. Distributed Block Nested Loop Join vs. Cyclo-Join), the data partitioning of the respective relations, and their overlapping as well as the allowed resource allocation.
We present an evaluation on a cluster with 60 nodes where all nodes are connected via RDMA-enabled network equipment. We show that query processing performance is about 2.4x slower if everything is done via the data pull operator execution strategy (i.e. RAMCloud is being used only for data access) and about 27% slower if operator execution is also supported inside RAMCloud (in comparison to operating only on main memory inside a server without any network communication at all). The fast-crash recovery feature of RAMCloud can be leveraged to provide high-availability, e.g. a server crash during query execution only delays the query response for about one second. Our solution is elastic in a way that it can adapt to changing workloads a) within seconds, b) without interruption of the ongoing query processing, and c) without manual intervention.
This study examines the course and driving forces of recent vegetation change in the Mongolian steppe. A sediment core covering the last 55years from a small closed-basin lake in central Mongolia was analyzed for its multi-proxy record at annual resolution. Pollen analysis shows that highest abundances of planted Poaceae and highest vegetation diversity occurred during 1977-1992, reflecting agricultural development in the lake area. A decrease in diversity and an increase in Artemisia abundance after 1992 indicate enhanced vegetation degradation in recent times, most probably because of overgrazing and farmland abandonment. Human impact is the main factor for the vegetation degradation within the past decades as revealed by a series of redundancy analyses, while climate change and soil erosion play subordinate roles. High Pediastrum (a green algae) influx, high atomic total organic carbon/total nitrogen (TOC/TN) ratios, abundant coarse detrital grains, and the decrease of C-13(org) and N-15 since about 1977 but particularly after 1992 indicate that abundant terrestrial organic matter and nutrients were transported into the lake and caused lake eutrophication, presumably because of intensified land use. Thus, we infer that the transition to a market economy in Mongolia since the early 1990s not only caused dramatic vegetation degradation but also affected the lake ecosystem through anthropogenic changes in the catchment area.
Flood damage has increased significantly and is expected to rise further in many parts of the world. For assessing potential changes in flood risk, this paper presents an integrated model chain quantifying flood hazards and losses while considering climate and land use changes. In the case study region, risk estimates for the present and the near future illustrate that changes in flood risk by 2030 are relatively low compared to historic periods. While the impact of climate change on the flood hazard and risk by 2030 is slight or negligible, strong urbanisation associated with economic growth contributes to a remarkable increase in flood risk. Therefore, it is recommended to frequently consider land use scenarios and economic developments when assessing future flood risks. Further, an adapted and sustainable risk management is necessary to encounter rising flood losses, in which non-structural measures are becoming more and more important. The case study demonstrates that adaptation by non-structural measures such as stricter land use regulations or enhancement of private precaution is capable of reducing flood risk by around 30 %. Ignoring flood risks, in contrast, always leads to further increasing losses-with our assumptions by 17 %. These findings underline that private precaution and land use regulation could be taken into account as low cost adaptation strategies to global climate change in many flood prone areas. Since such measures reduce flood risk regardless of climate or land use changes, they can also be recommended as no-regret measures.
Virtualized cloud data centers provide on-demand resources, enable agile resource provisioning, and host heterogeneous applications with different resource requirements. These data centers consume enormous amounts of energy, increasing operational expenses, inducing high thermal inside data centers, and raising carbon dioxide emissions. The increase in energy consumption can result from ineffective resource management that causes inefficient resource utilization. This dissertation presents detailed models and novel techniques and algorithms for virtual resource management in cloud data centers. The proposed techniques take into account Service Level Agreements (SLAs) and workload heterogeneity in terms of memory access demand and communication patterns of web applications and High Performance Computing (HPC) applications. To evaluate our proposed techniques, we use simulation and real workload traces of web applications and HPC applications and compare our techniques against the other recently proposed techniques using several performance metrics. The major contributions of this dissertation are the following: proactive resource provisioning technique based on robust optimization to increase the hosts' availability for hosting new VMs while minimizing the idle energy consumption. Additionally, this technique mitigates undesirable changes in the power state of the hosts by which the hosts' reliability can be enhanced in avoiding failure during a power state change. The proposed technique exploits the range-based prediction algorithm for implementing robust optimization, taking into consideration the uncertainty of demand. An adaptive range-based prediction for predicting workload with high fluctuations in the short-term. The range prediction is implemented in two ways: standard deviation and median absolute deviation. The range is changed based on an adaptive confidence window to cope with the workload fluctuations. A robust VM consolidation for efficient energy and performance management to achieve equilibrium between energy and performance trade-offs. Our technique reduces the number of VM migrations compared to recently proposed techniques. This also contributes to a reduction in energy consumption by the network infrastructure. Additionally, our technique reduces SLA violations and the number of power state changes. A generic model for the network of a data center to simulate the communication delay and its impact on VM performance, as well as network energy consumption. In addition, a generic model for a memory-bus of a server, including latency and energy consumption models for different memory frequencies. This allows simulating the memory delay and its influence on VM performance, as well as memory energy consumption. Communication-aware and energy-efficient consolidation for parallel applications to enable the dynamic discovery of communication patterns and reschedule VMs using migration based on the determined communication patterns. A novel dynamic pattern discovery technique is implemented, based on signal processing of network utilization of VMs instead of using the information from the hosts' virtual switches or initiation from VMs. The result shows that our proposed approach reduces the network's average utilization, achieves energy savings due to reducing the number of active switches, and provides better VM performance compared to CPU-based placement. Memory-aware VM consolidation for independent VMs, which exploits the diversity of VMs' memory access to balance memory-bus utilization of hosts. The proposed technique, Memory-bus Load Balancing (MLB), reactively redistributes VMs according to their utilization of a memory-bus using VM migration to improve the performance of the overall system. Furthermore, Dynamic Voltage and Frequency Scaling (DVFS) of the memory and the proposed MLB technique are combined to achieve better energy savings.
The paper is devoted to asymptotic analysis of the Dirichlet problem for a second order partial differential equation containing a small parameter multiplying the highest order derivatives. It corresponds to a small perturbation of a dynamical system having a stationary solution in the domain. We focus on the case where the trajectories of the system go into the domain and the stationary solution is a proper node.