AI-Based Enhanced Time Cost-Effective Cloud Workflow Scheduling

Abstract Protozoa of the genus Sarcocystis (phylum Apicomplexa, family Sarcocystidae) is one of the most common parasites affecting animals. Interspecies diagnostic of Sarcocystis genus was based on electron microscopy for many years. Because of absence of visible differences between species with reachable magnifications, light microscopy is useless. In many cases serological diagnostic method have lack of sensitivity. A variety of molecular methods have been developed and used to detect and identify Sarcocystis spp. and to assess the genetic diversity among this protozoan from different population/hosts. Nowadays, molecular diagnostic is the common, time/cost effective method used all over the world to interspecies differentiation.

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Cost Effective Genetic Algorithm for Workflow Scheduling in Cloud Under Deadline Constraint

IEEE Access ◽

10.1109/access.2016.2593903 ◽

2016 ◽

Vol 4 ◽

pp. 5065-5082 ◽

Cited By ~ 44

Author(s):

Jasraj Meena ◽

Malay Kumar ◽

Manu Vardhan

Keyword(s):

Genetic Algorithm ◽

Cost Effective ◽

Workflow Scheduling ◽

Deadline Constraint

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Time-Cost Effective Factor of a Midimew Connected Mesh Network

2016 6th International Conference on Information and Communication Technology for The Muslim World (ICT4M) ◽

10.1109/ict4m.2016.061 ◽

2016 ◽

Cited By ~ 2

Author(s):

M.M. Hafizur Rahman ◽

Mohammed N.M. Ali ◽

Rizal Mohd Nor ◽

Tengku Mohd Tengku Sembok ◽

M.A.H. Akhand

Keyword(s):

Cost Effective ◽

Mesh Network ◽

Time Cost ◽

Effective Factor

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Development of a smartphone-based real time cost-effective VOC sensor

Heliyon ◽

10.1016/j.heliyon.2020.e05167 ◽

2020 ◽

Vol 6 (10) ◽

pp. e05167 ◽

Cited By ~ 1

Author(s):

Tanmay Das ◽

Mrittika Mohar

Keyword(s):

Real Time ◽

Cost Effective ◽

Time Cost ◽

Voc Sensor

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Cost Effective and Deadline Constrained Scientific Workflow Scheduling for Commercial Clouds

2015 IEEE 14th International Symposium on Network Computing and Applications ◽

10.1109/nca.2015.33 ◽

2015 ◽

Cited By ~ 8

Author(s):

Vahid Arabnejad ◽

Kris Bubendorfer

Keyword(s):

Cost Effective ◽

Scientific Workflow ◽

Workflow Scheduling

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Cost Effective Heuristic workflow scheduling algorithm in Cloud under Deadline Constraint

Recent Patents on Computer Science ◽

10.2174/2213275912666190822113039 ◽

2019 ◽

Vol 12 ◽

Author(s):

Jasraj Meena ◽

Manu Vardhan

Keyword(s):

Cloud Computing ◽

Scheduling Algorithm ◽

Cost Effective ◽

Scientific Workflow ◽

Scientific Workflows ◽

Workflow Scheduling ◽

Performance Variation ◽

Acquisition Delay ◽

Very High ◽

Deadline Constraint

Cloud computing is used to deliver IT resources over the internet. Due to the popularity of cloud computing, nowadays, most of the scientific workflows are shifted towards this environment. There are lots of algorithms has been proposed in the literature to schedule scientific workflows in the cloud, but their execution cost is very high as well as they are not meeting the user-defined deadline constraint. This paper focuses on satisfying the userdefined deadline of a scientific workflow while minimizing the total execution cost. So, to achieve this, we have proposed a Cost-Effective under Deadline (CEuD) constraint workflow scheduling algorithm. The proposed CEuD algorithm considers all the essential features of Cloud and resolves the major issues such as performance variation, and acquisition delay. We have compared the proposed CEuD algorithm with the existing literature algorithms for scientific workflows (i.e., Montage, Epigenomics, and CyberShake) and getting better results for minimizing the overall execution cost of the workflow while satisfying the user-defined deadline.

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A Psychometric Analysis of the Epworth Sleepiness Scale

Journal of Nursing Measurement ◽

10.1891/106137407783095748 ◽

2007 ◽

Vol 15 (3) ◽

pp. 177-188 ◽

Cited By ~ 11

Author(s):

Karen Heaton ◽

Debra Anderson

Keyword(s):

Factor Analysis ◽

Epworth Sleepiness Scale ◽

Sleep Problems ◽

Cost Effective ◽

Time Cost ◽

Cronbach’S Alpha ◽

Cronbach's Alpha ◽

Two Factors ◽

Effective Instrument ◽

Current Sample

Psychometric performance of the Epworth Sleepiness Scale (ESS) has not been evaluated in groups of workers. This study evaluated its use in a sample of 843 long-haul truckers. Interitem correlations and Cronbach’s alpha were conducted. Correlation of the ESS with the sleep problems subscale of the Trucker Strain Monitor (TSM) was performed. Dimensionality was evaluated using factor analysis. Cronbach’s alpha (.79) was strong. Interitem correlations were significant. A weak but significant correlation between the ESS and TSM sleep problems subscale (r = .18, p = < .001) was shown. Factor analysis yielded two factors that explained 56.2% of scale variance. The ESS performed well in the current sample. It is an inexpensive, time/cost-effective instrument. It should be considered for use in studies of workers in naturalistic settings.

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