Implementation of IDEA, BATS, ARIMA and queuing model for task scheduling in cloud computing

Gawali, Mahendra Bhatu; Shinde, Subhash K.

doi:10.1109/eco-friendly.2016.7893233

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Let, we evaluate our proposed DCHEFT approach with existing BATS [16] and Heuristic Approach [17], SDMCOA [18] on the given Cybershake Seismogram Synthesis tasks. Evaluation of proposed DCHEFT system is based on two key factors i.e.…”

Section: Resultsmentioning

confidence: 99%

DCHEFT Approach for Task Scheduling to Efficient Resource Allocation in Cloud Computing

Gawali¹,

Shinde²

2017

IJEACS

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Abstract-Task scheduling is an important aspect to improve the utilization of resources in the Cloud Computing. This paper proposes a Divide and Conquer based approach for heterogeneous earliest finish time algorithm. The proposed system works in two phases. In the first phase it assigns the ranks to the incoming tasks with respect to size of it. In the second phase, we properly assign and manage the task to the virtual machine with the consideration of ideal time of respective virtual machine. This helps to get more effective resource utilization in Cloud Computing. The experimental results using Cybershake Scientific Workflow shows that the proposed Divide and Conquer HEFT performs better than HEFT in terms of task's finish time and response time. The result obtained by experimentally demonstrate that the proposed DCHEFT performance superiorly.

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Section: Resultsmentioning

confidence: 99%

DCHEFT Approach for Task Scheduling to Efficient Resource Allocation in Cloud Computing

Gawali¹,

Shinde²

2017

IJEACS

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“…Its main objective was to reduce the time taken for the task completion by the intended application [15,16]. The dynamic nature of cloud computing provides 'model of pay as per service pricing' [17]. But cloud computing also had some problems like allocation of resources and scheduling the tasks to VMs.…”

Section: Review Of Existing Workmentioning

confidence: 99%

Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

Shaheen¹,

kumar²

2023

Intelligent Automation &Amp; Soft Computing

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Cloud computing plays a significant role in Information Technology (IT) industry to deliver scalable resources as a service. One of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task scheduling. The main advantage of this scheduling is to maximize the performance and minimize the time loss. Various researchers examined numerous scheduling methods to achieve Quality of Service (QoS) and to reduce execution time. However, it had disadvantages in terms of low throughput and high response time. Hence, this study aimed to schedule the task efficiently and to eliminate the faults in scheduling the tasks to the Virtual Machines (VMs). For this purpose, the research proposed novel Particle Swarm Optimization-Bandwidth Aware divisible Task (PSO-BATS) scheduling with Multi-Layered Regression Host Employment (MLRHE) to sort out the issues of task scheduling and ease the scheduling operation by load balancing. The proposed efficient scheduling provides benefits to both cloud users and servers. The performance evaluation is undertaken with respect to cost, Performance Improvement Rate (PIR) and makespan which revealed the efficiency of the proposed method. Additionally, comparative analysis is undertaken which confirmed the performance of the introduced system than conventional system for scheduling tasks with high flexibility.

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“…In recent decades, many researchers have broadly investigated queueing systems with vacations and proposed some new approaches, such as matrix analysis [34], [35] and matrix geometry [33], [36]. Meanwhile, the queueing system with vacations has been applied to manufacturing systems [30], [37], polling systems [38] and cloud computing [39], [40] for performance analysis and evaluation. These models of performance analysis and evaluation, especially for cloud computing, cannot be applied to TOC directly because of the characteristics of TOC optical processor, such as having many trits and being dynamically bitwise reconfigurabile and bitwise allocabile.…”

Section: Background and Motivationmentioning

confidence: 99%

Performance Analysis and Evaluation of Ternary Optical Computer Based on a Queueing System With Synchronous Multi-Vacations

et al. 2020

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The ternary optical computer (TOC) has attracted increasing attention from its providers and potential customers because of the advantages of its optical processor, such as low power consumption, numerous trits, parallelism, dynamical reconfigurability and bitwise allocability. The analysis of its performance has become an urgent problem to be solved in recent years. This paper builds a four-stage TOC service model by introducing synchronous multi-vacations and tandem queueing. Here, a vacation refers specifically to an optical processor vacation. Additionally, we propose a processor-divided-equally(PDE) strategy and a task scheduling and optical processor allocation algorithm under this strategy. Assuming that the intervals of task arrival follow a homogeneous Poisson process, we obtain some important performance indicators, such as the mean response time, mean number of tasks, and optical processor utilization under the PDE strategy, which are based on the M/M/1 and M/M/n queueing systems with exhaustive service and synchronous multivacations. The numerical results illustrate that the number of small optical processors has an important effect on the performance of TOC and that high vacation rate can improve the system performance to some extent. INDEX TERMS Synchronous multi-vacations, tandem queueing, exhaustive service, response time, processor-divided-equally strategy.

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Implementation of IDEA, BATS, ARIMA and queuing model for task scheduling in cloud computing

Cited by 6 publications

References 12 publications

DCHEFT Approach for Task Scheduling to Efficient Resource Allocation in Cloud Computing

DCHEFT Approach for Task Scheduling to Efficient Resource Allocation in Cloud Computing

Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

Performance Analysis and Evaluation of Ternary Optical Computer Based on a Queueing System With Synchronous Multi-Vacations

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