Kani: a QoS-aware hypervisor-level scheduler for cloud computing environments

Cloud computing environments (CCEs) are expected to deliver their services with qualities in service level agreements. On the other hand, they typically employ virtualization technology to consolidate multiple workloads on the same physical machine, thereby enhancing the overall utilization of physical resources. Most existing virtualization technologies are, however, unaware of their delivered quality of services (QoS). For example, the Xen hypervisor merely focuses on fair sharing of processor resources. We believe that CCEs have got married with traditional virtualization technologies without many traits in common. To bridge the gap between these two technologies, we have designed and implemented Kani, a QoS-aware hypervisor-level scheduler. Kani dynamically monitors the quality of delivered services to quantify the deviation between desired and delivered levels of QoS. Using this information, Kani determines how to allocate processor resources among running VMs so as to meet the expected QoS. Our evaluations of Kani scheduler prototype in Xen show that Kani outperforms the default Xen scheduler namely the Credit scheduler. For example, Kani reduces the average response time to requests to an Apache web server by up to \(93.6\,\%\); improves its throughput by up to \(97.9\,\%\); and mitigates the call setup time of an Asterisk media server by up to \(96.6\,\%\).     

A novel task scheduling approach based on dynamic queues and hybrid meta-heuristic algorithms for cloud computing environment

Task scheduling is one of the most challenging aspects to improve the overall performance of cloud computing and optimize cloud utilization and Quality of Service (QoS). This paper focuses on Task Scheduling optimization using a novel approach based on Dynamic dispatch Queues (TSDQ) and hybrid meta-heuristic algorithms. We propose two hybrid meta-heuristic algorithms, the first one using Fuzzy Logic with Particle Swarm Optimization algorithm (TSDQ-FLPSO), the second one using Simulated Annealing with Particle Swarm Optimization algorithm (TSDQ-SAPSO). Several experiments have been carried out based on an open source simulator (CloudSim) using synthetic and real data sets from real systems. The experimental results demonstrate the effectiveness of the proposed approach and the optimal results is provided using TSDQ-FLPSO compared to TSDQ-SAPSO and other existing scheduling algorithms especially in a high dimensional problem. The TSDQ-FLPSO algorithm shows a great advantage in terms of waiting time, queue length, makespan, cost, resource utilization, degree of imbalance, and load balancing.     

Energy-aware task scheduling in heterogeneous computing environments

Efficient application scheduling is critical for achieving high performance in heterogeneous computing (HC) environments. Because of such importance, there are many researches on this problem and various algorithms have been proposed. Duplication-based algorithms are one kind of well known algorithms to solve scheduling problems, which achieve high performance on minimizing the overall completion time (makespan) of applications. However, they pursuit of the shortest makespan overly by duplicating some tasks redundantly, which leads to a large amount of energy consumption and resource waste. With the growing advocacy for green computing systems, energy conservation has been an important issue and gained a particular interest. An existing technique to reduce energy consumption of an application is dynamic voltage/frequency scaling (DVFS), whose efficiency is affected by the overhead of time and energy caused by voltage scaling. In this paper, we propose a new energy-aware scheduling algorithm with reduced task duplication called Energy-Aware Scheduling by Minimizing Duplication (EAMD), which takes the energy consumption as well as the makespan of an application into consideration. It adopts a subtle energy-aware method to search and delete redundant task copies in the schedules generated by duplication-based algorithms, and it is easier to operate than DVFS, and produces no extra time and energy consumption. This algorithm not only consumes less energy but also maintains good performance in terms of makespan compared with duplication-based algorithms. Two kinds of DAGs, i.e., randomly generated graphs and two real-world application graphs, are tested in our experiments. Experimental results show that EAMD can save up to 15.59 % energy consumption for HLD and HCPFD, two classic duplication-based algorithms. Several factors affecting the performance are also analyzed in the paper.     

Optimal mutation rates in dynamic environments

In this paper, we study the evolution of the mutation rate for simple organisms in dynamic environments. A model based on explicit population dynamics at the gene sequence level, with multiple fitness coding loci tracking a moving fitness peak in a random fitness background, is developed and an analytical expression for the optimal mutation rate is derived. The optimal mutation rate per genome is approximately independent of genome length, something that has been observed in nature. Furthermore, the optimal mutation rate is a function of the absolute, not relative, replication rate of the superior gene sequences. Simulations confirm the theoretical predictions.     

A simultaneous saccharification and fermentation model for dynamic growth environments

Many mathematical models by researchers have been formulated for Saccharomyces cerevisiae which is the common yeast strain used in modern distilleries. A cybernetic model that can account for varying concentrations of glucose, ethanol and organic acids on yeast cell growth dynamics does not exist. A cybernetic model, consisting of 4 reactions and 11 metabolites simulating yeast metabolism, was developed. The effects of variables such as temperature, pH, organic acids, initial inoculum levels and initial glucose concentration were incorporated into the model. Further, substrate and product inhibitions were included. The model simulations over a range of variables agreed with hypothesized trends and to observations from other researchers. Simulations converged to expected results and exhibited continuity in predictions for all ranges of variables simulated. The cybernetic model did not exhibit instability under any conditions simulated.     

Characterizing the balance-dexterity task as a concurrent bipedal task to investigate trunk control during dynamic balance

The purpose of the study was to characterize the Balance-Dexterity Task as a means to investigate a concurrent bipedal lower-extremity task and trunk control during dynamic balance. The task combines aspects of single-limb balance and the lower-extremity dexterity test by asking participants to stand on one limb while compressing an unstable spring with the contralateral limb to an individualized target force. Nineteen non-disabled participants completed the study, and performance measures for the demands of each limb – balance and dexterous force control – as well as kinematic and electromyographic measures of trunk control were collected. Given five practice trials, participants achieved compression forces ranging from 100 to 139 N (mean 121.2 ± 12.3 N), representing 14.4–23.0% of body weight (mean 18.7 ± 2.4%), which were then presented as target forces during test trials. Dexterous force control coefficient of variation and average magnitude of the center of pressure (COP) resultant velocity were associated such that greater variability in force control was accompanied by greater COP velocity (R = 0.598, p = 0.007). Trunk coupling, quantified as the coefficient of determination (R²) of a frontal plane thorax and pelvis angle-angle plot, varied independently of any measure of balance or dexterous force control. The Balance-Dexterity Task is a continuous, dynamic balance task where bipedal coordination and trunk coupling can be concurrently observed and studied.     

A flexible fine-grained dynamic access control approach for cloud computing environment

Cluster Computing - As a pioneering surge of ICT technologies, offering computing resources on-demand, the exceptional evolution of Cloud computing has not gone unnoticed by the IT world. At the...     

Motor control and learning in altered dynamic environments

Dynamic perturbations of reaching movements are an important technique for studying motor learning and adaptation. Adaptation to non-contacting, velocity-dependent inertial Coriolis forces generated by arm movements during passive body rotation is very rapid, and when complete the Coriolis forces are no longer sensed. Adaptation to velocity-dependent forces delivered by a robotic manipulandum takes longer and the perturbations continue to be perceived even when adaptation is complete. These differences reflect adaptive self-calibration of motor control versus learning the behavior of an external object or 'tool'. Velocity-dependent inertial Coriolis forces also arise in everyday behavior during voluntary turn and reach movements but because of anticipatory feedforward motor compensations do not affect movement accuracy despite being larger than the velocity-dependent forces typically used in experimental studies. Progress has been made in understanding: the common features that determine adaptive responses to velocity-dependent perturbations of jaw and limb movements; the transfer of adaptation to mechanical perturbations across different contact sites on a limb; and the parcellation and separate representation of the static and dynamic components of multiforce perturbations.     

Population genetic diversity and fitness in multiple environments

Background  

When a large number of alleles are lost from a population, increases in individual homozygosity may reduce individual fitness through inbreeding depression. Modest losses of allelic diversity may also negatively impact long-term population viability by reducing the capacity of populations to adapt to altered environments. However, it is not clear how much genetic diversity within populations may be lost before populations are put at significant risk. Development of tools to evaluate this relationship would be a valuable contribution to conservation biology. To address these issues, we have created an experimental system that uses laboratory populations of an estuarine crustacean, Americamysis bahia with experimentally manipulated levels of genetic diversity. We created replicate cultures with five distinct levels of genetic diversity and monitored them for 16 weeks in both permissive (ambient seawater) and stressful conditions (diluted seawater). The relationship between molecular genetic diversity at presumptive neutral loci and population vulnerability was assessed by AFLP analysis.     

Adaptive hybrid storage systems leveraging SSDs and HDDs in HPC cloud environments

Cloud computing should inherently support various types of data-intensive workloads with different storage access patterns. This makes a high-performance storage system in the Cloud an important component. Emerging flash device technologies such as solid state drives (SSDs) are a viable choice for building high performance computing (HPC) cloud storage systems to address more fine-grained data access patterns. However, the bit-per-dollar SSD price is still higher than the prices of HDDs. This study proposes an optimized progressive file layout (PFL) method to leverage the advantages of SSDs in a parallel file system such as Lustre so that small file I/O performance can be significantly improved. A PFL can dynamically adjust chunk sizes and stripe patterns according to various I/O traffics. Extensive experimental results show that this approach (i.e. building a hybrid storage system based on a combination of SSDs and HDDs) can actually achieve balanced throughput over mixed I/O workloads consisting of large and small file access patterns.     

Pseudomonas aeruginosa attachment and biofilm development in dynamic environments

Biofilm formation by Pseudomonas aeruginosa is hypothesized to follow a developmental pattern initiated by attachment to a surface followed by microcolony formation and mature biofilm development. Swimming and twitching motility are important for attachment and biofilm development in P. aeruginosa. However, it is clear that many P. aeruginosa strains lacking swimming motility exist as biofilms in the lungs of cystic fibrosis patients. Consequently, we have developed a dynamic attachment assay to identify motility-independent attachment-defective mutants. Using transposon mutagenesis, we identified 14 novel dynamic attachment-deficient (dad) mutants including four mutants specific to dynamic assay conditions (dad specific). Two of the dad-specific mutants contain insertions in genes involved in sensing and responding to external stimuli, implying a significant impact of external factors on the biofilm developmental pathway. Observations of initial attachment and long-term biofilm formation characterized our dad mutants into two distinct classes: biofilm delayed and biofilm impaired. Biofilm-delayed mutants form wild-type biofilms but are delayed at least 24 h compared with the wild type, whereas biofilm-impaired mutants never form wild-type biofilms in our assays. We propose a dynamic model for attachment and biofilm formation in P. aeruginosa including these two classes.     

Noise improves collective decision-making by ants in dynamic environments

Recruitment via pheromone trails by ants is arguably one of the best-studied examples of self-organization in animal societies. Yet it is still unclear if and how trail recruitment allows a colony to adapt to changes in its foraging environment. We study foraging decisions by colonies of the ant Pheidole megacephala under dynamic conditions. Our experiments show that P. megacephala, unlike many other mass recruiting species, can make a collective decision for the better of two food sources even when the environment changes dynamically. We developed a stochastic differential equation model that explains our data qualitatively and quantitatively. Analysing this model reveals that both deterministic and stochastic effects (noise) work together to allow colonies to efficiently track changes in the environment. Our study thus suggests that a certain level of noise is not a disturbance in self-organized decision-making but rather serves an important functional role.     

Stimulus-driven orienting of visuo-spatial attention in complex dynamic environments

In everyday life attention operates within complex and dynamic environments, while laboratory paradigms typically employ simple and stereotyped stimuli. This fMRI study investigated stimulus-driven spatial attention using a virtual-environment video. We explored the influence of bottom-up signals by computing saliency maps of the environment and by introducing attention-grabbing events in the video. We parameterized the efficacy of these signals for the orienting of spatial attention by measuring eye movements and used these parameters to analyze the imaging data. The efficacy of bottom-up signals modulated ongoing activity in dorsal fronto-parietal regions and transient activation of the ventral attention system. Our results demonstrate that the combination of computational, behavioral, and imaging techniques enables studying cognitive functions in ecologically valid contexts. We highlight the central role of the efficacy of stimulus-driven signals in both dorsal and ventral attention systems, with a dissociation of the efficacy of background salience versus distinctive events in the two systems.     

Photosynthetic gas exchange response of poplars to steady-state and dynamic light environments

The steady-state and dynamic photosynthetic response of two poplar species (Populus tremuloides and P. fremontii) to variations in photon flux density (PFD) were observed with a field portable gas exchange system. These poplars were shown to be very shade intolerant with high light saturation (800 to 1300 mol photons m^–2 s^–1) and light compensation (70 to 100 mol m^–2 s^–1) points. Understory poplar leaves showed no physiological acclimation to understory light environments. These plants become photosynthetically induced quickly (10 min). Activation of Rubisco was the primary limitation for induction, with stomatal opening playing only a minor role. Leaves maintained high stomatal conductances and stomata were unresponsive to variations in PFD. Leaves were very efficient at utilizing rapidly fluctuating light environments similar to those naturally occurring in canopies. Post-illumination CO₂ fixation contributed proportionally more to the carbon gain of leaves during short frequent lightflecks than longer less frequent ones. The benefits of a more dynamic understory light environment for the carbon economy of these species are discussed.