Execution of real time task on cloud environment

Sahoo, Sampa; Nawaz, Syed Junaid; Mishra, Sambit Kumar; Sahoo, Bibhudatta

doi:10.1109/indicon.2015.7443778

Cited by 22 publications

(6 citation statements)

References 1 publication

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“…By using Greedy-SA algorithm, the result says that the average delay got by Greedy -SA algorithm is consistently stable. In the same way the results on average latency says that, while the quantity of the controllers are continuously expanding under a similar topology in every technique [12].…”

Section: Evaluation and Resultssupporting

confidence: 53%

A Comparison of Algorithms for Controller Replacement in Software Defined Networking

Anitson¹,

Vinod²

2018

IJET

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Software Defined Network (SDN) partitions the control plane and the information plane to decrease the cost and for increasing the capacity for upgrading, and this will be helpful for the network administrators to manage the network services. It’s the location where the controller exists. One of the main issue in Software Defined Networking is the location of the controllers as this could affect network execution and cost. In this paper, we have done an analysis on some algorithms that have been used for minimizing the number of controllers to reduce the latency, delay, etc. while placing a controller with the consideration of communication among the controller and the nodes.

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Section: Evaluation and Resultssupporting

confidence: 53%

A Comparison of Algorithms for Controller Replacement in Software Defined Networking

Anitson¹,

Vinod²

2018

IJET

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“…The study of [41] proposed a real-time task scheduling technique in the cloud environment where the tasks are sort based on their deadlines; if a task misses its deadlines, it is rejected. Another work in [42] proposed a task scheduling algorithm that distributes the load among all virtual machines where it is assign the virtual machines to the tasks according to the power factor.…”

Section: Related Workmentioning

confidence: 99%

Prioritized scheduling technique for healthcare tasks in cloud computing

et al. 2022

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The Internet-of-things (IoT) plays a significant role in healthcare monitoring, where the IoT Cloud integration introduces many new opportunities for real-time remote monitoring of the patient. Task scheduling is one of the major challenges in cloud environment. Solving that problem reduces delay, missed tasks, and failure rate, and increases the guarantee ratio. This paper proposes a new task scheduling and allocation technique: Prioritized Sorted Task-Based Allocation (PSTBA) for healthcare monitoring implemented in IoT cloud-based architecture. The proposed technique selects the best virtual machine to execute the health task considering multiple factors such as; the wait time of the VM and the Expected processing time (EPT) of the task as well as its criticality. An extensive simulation study is conducted using the CloudSim simulator to evaluate the performance of the proposed technique. The proposed technique is compared to the Sorted Task-Based Allocation (STBA) and FCFS techniques and it reduces the delay by 13.7% and 80.2%, the failure rate by 21% and 37.5%, and increases the guarantee ratio by 2.2% and 4.5% compared to STBA and FCFS, respectively. In analyzing the critical health tasks, the proposed PSTBA has also reduced the critical health tasks missed ratio by 15.7% and 50.9% compared to STBA and FCFS, respectively. The simulation results demonstrate that PSTBA is more effective than the STBA and FCFS techniques in terms of delay, missed critical tasks, guarantee ratio, and failure rate.

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“…Few authors have applied modified EDF for the cloud environment. Along with the basic variant, Sahoo et al 19 have proposed three new versions of EDF for scheduling real‐time tasks in a cloud environment. These are the EDF variants of Best‐Fit, First‐Fit, and Worst‐Fit algorithms.…”

Section: Related Workmentioning

confidence: 99%

“…The scheduling design of the system is depicted in Figure 1 19 . When a new task is submitted by a user, it first goes to the ready queue of central scheduler.…”

Section: System Modelmentioning

confidence: 99%

Efficient task scheduling in cloud environment

Rana

Gupta

2022

Int J Communication

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Cloud computing is the provision of on-demand computing resources over the internet and on a pay-as-you-go basis, ranging from software to computation power. Task scheduling and its execution is a fundamental requirement of cloud environment. However, dynamic scheduling of tasks on basis of priority is a challenging area such that the tasks finish before their deadline. Earliest Deadline First (EDF) has been considered in literature for task scheduling to meet the deadlines. However, basic EDF (i.e., which schedules tasks on basis of deadline only)is not suitable for cloud environment. Therefore, this work proposes modified Preemptive EDF (p-EDF) and Non-Preemptive EDF (np-EDF) algorithms considering task priority and cloud provider cost. As both algorithms have their own merits and de-merits, a hybrid EDF is further proposed which makes decision dynamically whether to cause preemption or not, using a Determiner function. The objective of the work is to avoid unnecessary wastage of CPU power and time due to unnecessary preemptions, along with avoiding unnecessary deadline misses such that the high priority task does not wait for the low priority task to end. Simulation results show that the proposed algorithm outperforms other considered benchmark scheme for different performance parameters such as Deadline Miss Count, Preemption Count and average waiting time.

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Execution of real time task on cloud environment

Cited by 22 publications

References 1 publication

A Comparison of Algorithms for Controller Replacement in Software Defined Networking

A Comparison of Algorithms for Controller Replacement in Software Defined Networking

Prioritized scheduling technique for healthcare tasks in cloud computing

Efficient task scheduling in cloud environment

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