Valuable survey on scheduling algorithms in the cloud with various publications

Bansal, Nidhi; Singh, Ajay Kumar

doi:10.1007/s13198-022-01685-3

Cited by 5 publications

(2 citation statements)

References 114 publications

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“…Here the total cost will be solved through the mentioned ( 1 By running Java code in CloudSim, an Excel file of cost factor is automatically saved to a specified drive of the system (user's specific). After the code is implemented on the machine, the code is run, and the execution time is shown in the Netbeans IDE output window [24], [25]. The number of users may vary with the number of incoming requests.…”

Section: Resultsmentioning

confidence: 99%

Healthcare scenario: a new task scheduling algorithm in cloud computing environment

Bansal¹,

Singh²

2023

IJEECS

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<span lang="EN-US">Makespan and cost are the major factors in the current scenario and they generally upgrade the results to optimize the upcoming task processing by implementing the scheduling within the specified cloud platform. A new proposed agenda is being considered for a health care system to make the world healthier. The paper is designed to identify prior work as a health evaluator for the end user and act accordingly. It also satisfies the end user by providing demanded results and can establish trust between the system and the customer within a global era. By analyzing the COVID-pandemic situation in the digital world, things should be implemented in conjunction with healthcare and technology to serve things better. The proposed algorithm works on priority basis by analyzing the current patient condition and then implemented in CloudSim Toolkit. As per the results, the proposed steps are performing 50-70% better in terms of makespan and cost. Notable optimization has been accomplished by the proposed healthcare evaluator.</span>

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Section: Resultsmentioning

confidence: 99%

Healthcare scenario: a new task scheduling algorithm in cloud computing environment

Bansal¹,

Singh²

2023

IJEECS

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“…The selection of a cloud scheduling algorithm is influenced by the nature of the workload, resource limitations, performance objectives, and cost concerns. In complicated cloud environments, the allocation of resources can be balanced and optimized via hybrid approaches that incorporate several scheduling algorithms [8].…”

Section: 3motivationmentioning

confidence: 99%

A meta-heuristic clustered grey wolf optimization algorithm for cloud resource scheduling

2023

IJATEE

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Introduction 1.1Background Cloud computing is an example of distributed computing and is one of the most widespread techniques nowadays. It enables the internet-based sharing of resources such as storage, servers, databases, and numerous application services. With the assistance of service providers, anyone can access these underfunded services [1]. Cloud service providers (CSPs), who run data centers (DCs) with powerful servers and infrastructure, offer these services. Software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) are the three types of cloud service models [2]. *Author for correspondence CSPs supply virtualized computing resources over the internet in the IaaS model. Amazon web services (AWS), microsoft azure, and google cloud platform (GCP) are well-known IaaS providers. PaaS offers a platform for creating, deploying, and managing applications that include infrastructure, development tools, and services. While the cloud provider takes care of the maintenance and the underlying infrastructure, users may concentrate on creating and deploying applications. Heroku, google app engine, and microsoft azure app service are a few PaaS platform examples. Email services like Gmail, productivity suites like Microsoft 365, and customer relationship management tools like Sales-force are examples of SaaS applications. The shared use of virtual resources, especially IaaS, is the main focus of this study.

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A comparative analysis of genetic algorithms on a case study of asymmetric traveling salesman problem

Raj,

Punia,

Kumar

2023

Int J Syst Assur Eng Manag

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Valuable survey on scheduling algorithms in the cloud with various publications

Cited by 5 publications

References 114 publications

Healthcare scenario: a new task scheduling algorithm in cloud computing environment

Healthcare scenario: a new task scheduling algorithm in cloud computing environment

A meta-heuristic clustered grey wolf optimization algorithm for cloud resource scheduling

A comparative analysis of genetic algorithms on a case study of asymmetric traveling salesman problem

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