Container-Based Fast Service Migration Method for Mobile Edge Computing

Mobile edge computing (MEC) provides users with low-latency, high-bandwidth, and high-reliability services by migrating the computing power of the cloud computing center to the edge of the network. It is thus being considered an effective solution for the contradiction between the limited computing capabilities of Internet of Things (IoT) devices and the rapid development of delay-sensitive real-time applications. In this study, we propose and design a container union file system based on the differencing hard disk and dynamic loading strategy to address the excessively long migration time caused by the bundling transmission of the file system and container images during container-based service migration. The proposed method involves designing a mechanism based on a remote dynamic loading strategy to avoid the downloading of all container images, thereby reducing the long preparation time before which stateless migration can begin. Furthermore, in view of the excessive latency of the edge service during the stateful migration process, a strategy for avoiding the transmission of the underlying file system and container images is designed to optimize the service interruption time and service quality degradation time. Experiments show that the proposed method and strategy can effectively reduce the migration time of container-based services.

Population Genetics and Spawning Time of Lake Taupo Rainbow Trout

<p>The rainbow trout (Oncorhynchus mykiss) of Lake Taupo, New Zealand provide an exceptional opportunity to explore the contemporary adaptation of an introduced aquatic species. Recently it has become evident that their spawning migration time has shifted to later in the season. I investigated the genetic basis of these changes in spawning time by (1) using genetic markers to determine the origins of Taupo trout in California, (2) determining the pattern and extent of spatial population genetic variation throughout the Lake Taupo catchment and in comparison to nearby Lake Tarawera in the Rotorua district, (3) analysing genetic variation at the OtsClock1b spawning time gene in temporal replicates from several sites from Taupo, and (4) comparing contemporary genetic variation at this gene and microsatellite markers to genetic variation from three Taupo tributaries in 1980s. I compared the ability of single nucleotide polymorphism (SNP) and microsatellite markers to determine the origins of Lake Taupo rainbow trout, translocated from California around 120 years ago. Data were collected from 15 microsatellite and 93 SNP markers, using samples from the Lake Taupo population and ten populations throughout California, which included all historically indicated populations of origin. Results revealed that the Lake Taupo population has significantly diverged from Californian populations at both microsatellite and SNP loci. These analyses also showed that the Lake Taupo population was probably derived from several sources in California (the most likely origins being the McCloud River and Lake Almanor), and an indeterminate California coastal population. This conclusion was supported with simulations of founder events, which suggested that the genetic patterns of a single source of introduction would still be detectable 100 years post-founding, but with multiple introductions exact source populations become more difficult to detect. Approximately 50 individuals from 10 locations throughout the catchment were then analysed using 15 microsatellite loci to determine if there was any spatial population genetic differentiation. There was no significant difference in genetic distance between locations within Lake Taupo, although there was a significant difference between these populations and Rotorua and Waipakihi, which are isolated by geographic barriers. Lake Taupo rainbow trout do appear to diverge at markers potentially under selection, though, because genotyping of the poly-Q region of the timing locus OtsClock1b shows significant differentiation between individuals sampled at different times in the Waipa River. Two other sites, however, did not show the same pattern of significant seasonal variation in OtsClock1b allele frequencies. This suggests that genotypes at this locus could be influencing spawning migration time, but that this variation could also be site specific, and therefore have a strong environmental component. Scale samples from the 1980s show no significant divergence at 5 microsatellites and OtsClock1b, indicating that allele frequencies have not changed significantly over the last 20 years at neutral markers or markers under selection. I therefore conclude that while Taupo rainbow trout have diverged from their origins in California, they have only slightly diverged within their new environment, and do not show a consistent pattern of genetic change over time. This information will contribute not only to the management of the Taupo fishery but also to the current understanding of the population genetic structuring of introduced salmonids.</p>

Population Genetics and Spawning Time of Lake Taupo Rainbow Trout

<p>The rainbow trout (Oncorhynchus mykiss) of Lake Taupo, New Zealand provide an exceptional opportunity to explore the contemporary adaptation of an introduced aquatic species. Recently it has become evident that their spawning migration time has shifted to later in the season. I investigated the genetic basis of these changes in spawning time by (1) using genetic markers to determine the origins of Taupo trout in California, (2) determining the pattern and extent of spatial population genetic variation throughout the Lake Taupo catchment and in comparison to nearby Lake Tarawera in the Rotorua district, (3) analysing genetic variation at the OtsClock1b spawning time gene in temporal replicates from several sites from Taupo, and (4) comparing contemporary genetic variation at this gene and microsatellite markers to genetic variation from three Taupo tributaries in 1980s. I compared the ability of single nucleotide polymorphism (SNP) and microsatellite markers to determine the origins of Lake Taupo rainbow trout, translocated from California around 120 years ago. Data were collected from 15 microsatellite and 93 SNP markers, using samples from the Lake Taupo population and ten populations throughout California, which included all historically indicated populations of origin. Results revealed that the Lake Taupo population has significantly diverged from Californian populations at both microsatellite and SNP loci. These analyses also showed that the Lake Taupo population was probably derived from several sources in California (the most likely origins being the McCloud River and Lake Almanor), and an indeterminate California coastal population. This conclusion was supported with simulations of founder events, which suggested that the genetic patterns of a single source of introduction would still be detectable 100 years post-founding, but with multiple introductions exact source populations become more difficult to detect. Approximately 50 individuals from 10 locations throughout the catchment were then analysed using 15 microsatellite loci to determine if there was any spatial population genetic differentiation. There was no significant difference in genetic distance between locations within Lake Taupo, although there was a significant difference between these populations and Rotorua and Waipakihi, which are isolated by geographic barriers. Lake Taupo rainbow trout do appear to diverge at markers potentially under selection, though, because genotyping of the poly-Q region of the timing locus OtsClock1b shows significant differentiation between individuals sampled at different times in the Waipa River. Two other sites, however, did not show the same pattern of significant seasonal variation in OtsClock1b allele frequencies. This suggests that genotypes at this locus could be influencing spawning migration time, but that this variation could also be site specific, and therefore have a strong environmental component. Scale samples from the 1980s show no significant divergence at 5 microsatellites and OtsClock1b, indicating that allele frequencies have not changed significantly over the last 20 years at neutral markers or markers under selection. I therefore conclude that while Taupo rainbow trout have diverged from their origins in California, they have only slightly diverged within their new environment, and do not show a consistent pattern of genetic change over time. This information will contribute not only to the management of the Taupo fishery but also to the current understanding of the population genetic structuring of introduced salmonids.</p>

Effective Utilization of Resources Through Optimal Allocation and Opportunistic Migration of Virtual Machines in Cloud Environment

Cloud computing has become more prominent, and it is used in large data centers. Distribution of well-organized resources (bandwidth, CPU, and memory) is the major problem in the data centers. The genetically enhanced shuffling frog leaping algorithm (GESFLA) framework is proposed to select the optimal virtual machines to schedule the tasks and allocate them in physical machines (PMs). The proposed GESFLA-based resource allocation technique is useful in minimizing the wastage of resource usage and also minimizes the power consumption of the data center. The proposed GESFL algorithm is compared with task-based particle swarm optimization (TBPSO) for efficiency. The experimental results show the excellence of GESFLA over TBPSO in terms of resource usage ratio, migration time, and total execution time. The proposed GESFLA framework reduces the energy consumption of data center up to 79%, migration time by 67%, and CPU utilization is improved by 9% for Planet Lab workload traces. For the random workload, the execution time is minimized by 71%, transfer time is reduced up to 99%, and the CPU consumption is improved by 17% when compared to TBPSO.

Activity of CdTe Quantum-Dot-Tagged Superoxide Dismutase and Its Analysis in Capillary Electrophoresis

Quantum dots (QDs) have a broad range of applications in cell biolabeling, cancer treatment, metastasis imaging, and therapeutic drug monitoring. Despite their wide use, relatively little is known about their influence on other molecules. Interactions between QDs and proteins can influence the properties of both nanoparticles and proteins. The effect of mercaptosuccinic acid-capped CdTe QDs on intercellular copper–zinc superoxide dismutase (SOD1)—one of the main enzymatic antioxidants—was investigated. Incubation of SOD1 with QDs caused an increase in SOD1 activity, unlike in the case of CdCl2, which inhibited SOD1. Moreover, this effect on SOD1 increased with the size and potential of QDs, although the effect became clearly visible in higher concentrations of QDs. The intensity of QD-SOD1 fluorescence, analyzed with the use of capillary electrophoresis with laser-induced fluorescence detection, was dependent on SOD1 concentration. In the case of green QDs, the fluorescence signal decreased with increasing SOD1 concentration. In contrast, the signal strength for Y-QD complexes was not dependent on SOD1 dilutions. The migration time of QDs and their complexes with SOD1 varied depending on the type of QD used. The migration time of G-QD complexes with SOD1 differed slightly. However, in the case of Y-QD complexes with SOD1, the differences in the migration time were not dependent on SOD concentration. This research shows that QDs interact with SOD1 and the influence of QDs on SOD activity is size-dependent. With this knowledge, one might be able to control the activation/inhibition of specific enzymes, such as SOD1.

A Rational Procedure to Increase Selectivity in the Determination of an Elicitor as Salicylic Acid in Polygala Extracts Using Capillary Electrophoresis

Considering the economic potential of secondary metabolites, researches have been focusing several strategies in order to explore and enhance the accumulation of these metabolites in plant matrices in a broad context. One of those strategies is the development of suitable methodologies for the determination of some elicitors, such as salicylic acid (SA). Since literature presents only a few analytical methods for the quantification of SA in plants, this study developed, validated and evaluated these metabolite contents in Polygala species using capillary zone electrophoresis with ultraviolet-visible detection. The background electrolyte (BGE) consisted of 15 mmol L−1 of hydroxymethyl-aminomethane and 30 mmol L−1 of 2-hydroxy-isobutyric acid, pH = 3.9. The BGE was chosen using a rational procedure to increase selectivity and reduce migration time. The method presented rapid performance, migration time less than 0.76 min for salicylic and phthalic acid (internal standard), precision results for peak area were better than 2.9% (intra-day) and 2.8% (inter-day) and the responses for the analytes were linear (range of 1-5 mg L−1), with limits of detection and quantification of 0.2 and 0.6 mg L−1, respectively. The developed method was applied for 39 samples of plant extracts.

FEATURE SELECTION FOR PREDICTING LIVE MIGRATION CHARACTERISTICS OF VIRTUAL MACHINES

Virtual machine migration is widely used in cloud data centers to scale and maintain the stability of cloud services. However, the performance metrics of virtual machine (VM) applications during migration that are set in the Service Level Agreements may deteriorate. Before starting a migration, it is necessary to evaluate the migration characteristics that affect the quality of service. These characteristics are the total migration time and virtual machine downtime, which are random variables that depend on a variety of factors. The prediction is based on the VM monitoring data. In this paper, we select the most suitable factors for forecasting five types of migrations: precopy migration, postcopy migration, and modification of precopy migration such as CPU throttling, data compression, and delta compression of modified memory pages. To do this, we analyzed a dataset that includes data on five types of migrations, approximately 8000 records of each type. Using correlation analysis, the factors that mostly affect the total migration time and the VM downtime are chosen. These characteristics are predicted using machine learning methods such as linear regression and the support vector machine. It is shown that the number of factors can be reduced almost twice with the same quality of the forecast. In general, linear regression provides relatively high accuracy in predicting the total migration time and the duration of virtual machine downtime. At the same time, the observed nonlinearity in the correlations shows that it is advisable to use the support vector machine to improve the quality of the forecast.

Multi Objective Task Scheduling Algorithm in Cloud Computing Using the Hybridization of Particle Swarm Optimization and Cuckoo Search

Rapid growth has been occurred in the IT industry with the emergence of Cloud computing in terms of the resources provisioned to the users in a seamless and flexible way. Task Scheduling is a prodigious challenge in the Cloud Computing. It is difficult to schedule the continuously varying requests to schedule on continuously varying resources. The existing approaches haven’t considered all the metrics while considering only the metrics like makespan and waiting time. In this paper, our focus is to formulate a Multi objective approach which is used to optimally map and load balance the tasks in the cloud by calculating the task priority and VM priority based on the electricity price per unit cost while minimizing the makespan, migration time and the power cost in the datacenters. The proposed algorithm is modeled using the hybridized approach by combining PSO and Cuckoo search algorithms. It is simulated on cloudsim simulator and it is compared against the basic ACO, GA, PSO and CS algorithms and our algorithm is outperformed against these basic algorithms with concerned parameters such as makespan, Migration time and the Total Power cost in the datacenters.

AN OPEN SOURCE MAIL SERVER MIGRATION EXPERIENCE: IREDMAIL

Servers are systems that set up to run for years, but it may be necessary to migrate to a new, better server when they have completed their lifetime or become inadequate. In this study, the open-source iRedMail e-mail server has been successfully migrated to another high-capacity physical server which uses an open-source CentOS operation system. Migration is a process that every step has to be very well planned. However, although planning is well done, unexpected errors may occur. For this reason, it is also essential to choose migration time. The experience gained as a result of the study is a guide for the new ones.