scholarly journals Mitigating Interference between Scientific Applications in OS-Level Virtualized Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Theodora Adufu ◽  
Yoonhee Kim
Keyword(s):  
Scientific Workflows ◽  
Scientific Applications ◽  
Weighted Mean ◽  
Scientific Application ◽  
Isolation Layer ◽  
Performance Isolation ◽  
Efficient Performance ◽  
Production Environments ◽  
Scheduling Method ◽  
Computing Environments

Recent research and production environments are deploying more container technologies for the execution of HPC applications and for reproducing scientific workflows or computing environments. Research works, however, have not accounted for performance interference when executing corunning applications in containers though the absence of an efficient performance isolation layer cannot guarantee the absence of performance interference among multiple corunning applications which share resources. In this research, we propose an interference-aware scheduling method that mitigates the problem of performance interference based on applications’ I/O and CPU usage profiles. The proposed method estimates the amount of interference between various pairs of applications and coschedules them based on estimated interference. We evaluate the proposed method for both Bag-of-Tasks (BOT) scientific applications and scientific workflows and compare our method to the Weighted Mean Method. Our method improves the performance of the target scientific application by coscheduling applications with the least estimated interference ratios.

scholarly journals Arithmetic Framework to Optimize Packet Forwarding among End Devices in Generic Edge Computing Environments

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 421
Author(s):  
Pedro Juan Roig ◽  
Salvador Alcaraz ◽  
Katja Gilly ◽  
Cristina Bernad ◽  
Carlos Juiz
Keyword(s):  
Edge Computing ◽  
Modular Arithmetic ◽  
Packet Forwarding ◽  
Computing Environment ◽  
Arithmetic Means ◽  
Simple Arithmetic ◽  
Efficient Performance ◽  
Integer Division ◽  
Computing Environments ◽  
Multi Access

Multi-access edge computing implementations are ever increasing in both the number of deployments and the areas of application. In this context, the easiness in the operations of packet forwarding between two end devices being part of a particular edge computing infrastructure may allow for a more efficient performance. In this paper, an arithmetic framework based in a layered approach has been proposed in order to optimize the packet forwarding actions, such as routing and switching, in generic edge computing environments by taking advantage of the properties of integer division and modular arithmetic, thus simplifying the search of the proper next hop to reach the desired destination into simple arithmetic operations, as opposed to having to look into the routing or switching tables. In this sense, the different type of communications within a generic edge computing environment are first studied, and afterwards, three diverse case scenarios have been described according to the arithmetic framework proposed, where all of them have been further verified by using arithmetic means with the help of applying theorems, as well as algebraic means, with the help of searching for behavioral equivalences.

scholarly journals Fault-Tolerant and Data-Intensive Resource Scheduling and Management for Scientific Applications in Cloud Computing

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7238
Author(s):  
Zulfiqar Ahmad ◽  
Ali Imran Jehangiri ◽  
Mohammed Alaa Ala’anzy ◽  
Mohamed Othman ◽  
Arif Iqbal Umar
Keyword(s):  
Cloud Computing ◽  
Fault Tolerant ◽  
Research Work ◽  
Resource Scheduling ◽  
Scientific Workflow ◽  
Scientific Workflows ◽  
Scientific Applications ◽  
Data Intensive ◽  
Computing Paradigm ◽  
Cost Constraints

Cloud computing is a fully fledged, matured and flexible computing paradigm that provides services to scientific and business applications in a subscription-based environment. Scientific applications such as Montage and CyberShake are organized scientific workflows with data and compute-intensive tasks and also have some special characteristics. These characteristics include the tasks of scientific workflows that are executed in terms of integration, disintegration, pipeline, and parallelism, and thus require special attention to task management and data-oriented resource scheduling and management. The tasks executed during pipeline are considered as bottleneck executions, the failure of which result in the wholly futile execution, which requires a fault-tolerant-aware execution. The tasks executed during parallelism require similar instances of cloud resources, and thus, cluster-based execution may upgrade the system performance in terms of make-span and execution cost. Therefore, this research work presents a cluster-based, fault-tolerant and data-intensive (CFD) scheduling for scientific applications in cloud environments. The CFD strategy addresses the data intensiveness of tasks of scientific workflows with cluster-based, fault-tolerant mechanisms. The Montage scientific workflow is considered as a simulation and the results of the CFD strategy were compared with three well-known heuristic scheduling policies: (a) MCT, (b) Max-min, and (c) Min-min. The simulation results showed that the CFD strategy reduced the make-span by 14.28%, 20.37%, and 11.77%, respectively, as compared with the existing three policies. Similarly, the CFD reduces the execution cost by 1.27%, 5.3%, and 2.21%, respectively, as compared with the existing three policies. In case of the CFD strategy, the SLA is not violated with regard to time and cost constraints, whereas it is violated by the existing policies numerous times.

scholarly journals Novel improved fractional operators and their scientific applications

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Abd-Allah Hyder ◽  
M. A. Barakat
Keyword(s):  
Fractional Integral ◽  
Differential Operators ◽  
Fractional Operators ◽  
Scientific Applications ◽  
Scientific Application ◽  
Electrical Circuits ◽  
Engineering Problems ◽  
Convolution Kernels ◽  
Composition Properties ◽  
Parameter Values

AbstractThe motivation of this research is to introduce some new fractional operators called “the improved fractional (IF) operators”. The originality of these fractional operators comes from the fact that they repeat the method on general forms of conformable integration and differentiation rather than on the traditional ones. Hence the convolution kernels correlating with the IF operators are served in conformable abstract forms. This extends the scientific application scope of their fractional calculus. Also, some results are acquired to guarantee that the IF operators have advantages analogous to the familiar fractional integral and differential operators. To unveil the inverse and composition properties of the IF operators, certain function spaces with their characterizations are presented and analyzed. Moreover, it is remarkable that the IF operators generalize some fractional and conformable operators proposed in abundant preceding works. As scientific applications, the resistor–capacitor electrical circuits are analyzed under some IF operators. In the case of constant and periodic sources, this results in novel voltage forms. In addition, the overall influence of the IF operators on voltage behavior is graphically simulated for certain selected fractional and conformable parameter values. From the standpoint of computation, the usage of new IF operators is not limited to electrical circuits; they could also be useful in solving scientific or engineering problems.

scholarly journals The Paleobiology Database application programming interface

Paleobiology ◽  
2015 ◽  
Vol 42 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Shanan E. Peters ◽  
Michael McClennen
Keyword(s):  
Real Time ◽  
Data Model ◽  
Application Programming Interface ◽  
Scientific Workflows ◽  
Scientific Applications ◽  
Database Application ◽  
Occurrence Data ◽  
Analysis Tools ◽  
Application Programming ◽  
Programming Interface

AbstractThe Paleobiology Database (PBDB; https://paleobiodb.org) consists of geographically and temporally explicit, taxonomically identified fossil occurrence data. The taxonomy utilized by the PBDB is not static, but is instead dynamically generated using an algorithm applied to separately managed taxonomic authority and opinion data. The PBDB owes its existence to many individuals, some of whom have entered more than 1.26 million fossil occurrences and over 570,000 taxonomic opinions, and some of whom have developed and maintained supporting infrastructure and analysis tools. Here, we provide an overview of the data model currently used by the PBDB and then briefly describe how this model is exposed via an Application Programming Interface (API). Our objective is to outline how PBDB data can now be accessed within individual scientific workflows, used to develop independently managed educational and scientific applications, and accessed to forge dynamic, near real-time connections to other data resources.

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