Scheduling real time tasks in an energy-efficient way using VMs with discrete compute capacities

Ghose, Manojit; Kaur, Sawinder; Sahu, Aryabartta

doi:10.1007/s00607-019-00738-z

Cited by 10 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Partitioned Balanced Time Scheduling algorithm [7] calculates the suitable number of resources requested per billing slot so that the cost is reduced and a deadline is satisfied. Other dynamic approaches incorporate those presented by [8][9][10][11][12][13][14][15][16][17][18][19][20][21]. The main limitation of these techniques is their task-level optimal scenario, which is a trade-off for their adjustability to unpredicted delays.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Resource Provisioning and Scheduling Algorithm for Scientific Workflows on IaaS Cloud

Rajasekar

Yogesh

2021

SN COMPUT. SCI.

View full text Add to dashboard Cite

Scientific workflow applications are deployed to run extensive volumes of data and to manage comprehensive observations and simulations. They are resource-intensive and time-utilizing applications that profit from processing in distributed environments. Especially, workflow applications can highly support the simple access, scalability, and affordability provided by cloud computing. To attain this, disruptive and well-planned operation of managing the workflow tasks and running the compute pool in a cost-effective mode essential to be evolved. We present an adaptive resource provisioning and scheduling algorithm for scientific workflows on Infrastructure as a Service (IaaS) clouds. Our approach was planned to deal challenges especially to clouds, such as unlimited on-demand access, heterogeneity, performance variation and pay-per-use type (i.e., per minute billing). To correspondingly efficient to these uncertainties of cloud, therefore, our approach was developed with consider these necessary problems to run, and is achievable in making effective solutions that satisfy a user-described deadline and reduce the spending cost of the utilized environment using the service of resource provisioning and scheduling. Finally, experimental results show that it executes a workflow effectively with regard to achieving deadline and minimizing cost than other advanced algorithms.

show abstract

Section: Related Workmentioning

confidence: 99%

Adaptive Resource Provisioning and Scheduling Algorithm for Scientific Workflows on IaaS Cloud

Rajasekar

Yogesh

2021

SN COMPUT. SCI.

View full text Add to dashboard Cite

show abstract

“…Although the cloud service uses the authentication method to protect the user's data information to a certain extent, because the current research on cloud computing service technology is still in its infancy and the technical level is relatively low, the user data is stored in the process of storage. There are still adverse phenomena such as data loss [3]; so, how to protect user data through the use of related measures such as technological development and innovation presents an urgent problem for researchers in the relevant industry to solve.…”

Section: Introductionmentioning

confidence: 99%

A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing

Wang

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In order to improve the communication security of wireless mobile network, a collaborative intrusion detection method based on cloud computing is studied. The mobile terminal and the cloud computing platform are connected by the wireless mobile network. The cloud computing platform authentication server adopts a dual server and multifactor authentication scheme for mobile cloud computing to provide authentication services for mobile terminal users. The web server of the cloud computing platform uses the intrusion node detection protocol of the neighbor classification mechanism to provide a communication security protocol for users; Using the HMM algorithm, the intrusion detection module of the computing platform realizes the intrusion detection of wireless mobile network. Finally, using authentication service, security protocol, and intrusion detection module completes the cooperative detection of mobile network intrusion. The experimental results show that this method can realize the cooperative detection of wireless mobile network intrusion, and the detection accuracy is as high as 98%, which ensures the communication security of wireless mobile network.

show abstract

Workload Scheduling in Fog and Cloud Environments: Emerging Concepts and Research Directions

Stavrinides

Karatza

2022

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Scheduling real time tasks in an energy-efficient way using VMs with discrete compute capacities

Cited by 10 publications

References 30 publications

Adaptive Resource Provisioning and Scheduling Algorithm for Scientific Workflows on IaaS Cloud

Adaptive Resource Provisioning and Scheduling Algorithm for Scientific Workflows on IaaS Cloud

A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing

Workload Scheduling in Fog and Cloud Environments: Emerging Concepts and Research Directions

Contact Info

Product

Resources

About