Task scheduling in cloud computing using hybrid optimization algorithm

2021 ◽  
Author(s):  
Mohd Sha Alam Khan ◽  
R. Santhosh
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Optimization Algorithm ◽  
Hybrid Optimization ◽  
Hybrid Optimization Algorithm

scholarly journals A Hybrid Optimization Algorithm for Enhanced Web Services with QoS Measures in Cloud Computing.

2021 ◽  
Author(s):  
L Thenmozhi ◽  
N. Chandrakala
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Web Services ◽  
Optimization Algorithm ◽  
Optimization Techniques ◽  
Bald Eagle ◽  
Hybrid Optimization ◽  
Hybrid Optimization Algorithm ◽  
The Web

Abstract In the Environment of Big-Data analytics in world-wide, the cloud web-services were deployed in internet and Intranet domains. Moreover cloud computing possess the privileges and acquired rapid development, faces the trust complexities, privacy concepts and security issues which allows to implement the QoS measures in the optimization techniques in the web services selection. The study focusses on selection of component services and employing the efficient algorithm with end to end Quality of measures. The Data diversification and the service characteristics would decline the accuracy level of the measures. In this study a novel Qos measure web-services algorithm implemented the weight attributes and the subjective attributes. This study employs the novel hybrid-optimization algorithm in gaining the privileges of the search randomised-attributes and the implementation of IWO-invasive-weed algorithm. This study also focusses on the Calculation of Quality-of-service measures on the weights of the web-services attributes. Many researches have placed the Implementation of nature inspired concept for the optimization complexities in Big Data and thus employing Eagle-Perching Algorithm in the efficiency enhancement of cloud web-services. The evolution of BES- Bald Eagle-Search were utilized as the nature inspired approach would drive as the efficient technique for optimisation issues which imitates the bald-eagles behaviour. The results have been demonstrated the comparison of the performance metrics with the existing approaches to evaluate the proposed methodology.

scholarly journals Optimal workflow scheduling in cloud computing based on hybrid bacterial evolutionary and bees mating optimization algorithm

2021 ◽  
Vol 12 (3) ◽  
pp. 4762-4775
Author(s):  
Dinesh Kumar, Dr Sunil Kumar
Keyword(s):  
Cloud Computing ◽  
Optimization Algorithm ◽  
Service Providers ◽  
Computer Hardware ◽  
Hybrid Optimization ◽  
Workflow Scheduling ◽  
Distributed Resources ◽  
Computing Technique ◽  
Hybrid Optimization Algorithm ◽  
And Performance

Distributed computing is the most recent developing pattern in disseminated processing that conveys equipment framework and programming applications as administrations. The clients can devour these administrations dependent on a SLA which characterizes their required QoS parameters. By using the cloud computing technique it is possible to reduce the investment on various resources like computer hardware and software. The application or processes that are hosted and executed using clouds consist of set of tasks and it is considered that this task will form the workflow. Therefore scheduling the task is considered as a major issue as resource usage has to be maximized without affecting the services that are facilitated by the cloud. In order to execute different virtual machine application of the tasks are assigned and it is termed as enterprise arranging. In the scheduling process the inter-dependent tasks are mapped and managed in the distributed resources. For additional improvement, this paper proposes a hybrid optimization algorithm for workflow scheduling (HOWS) in cloud environment. In the proposed algorithm the first contribution is the bees mating optimization (BMO) algorithm used to share physical infrastructure to enable multiple service providers to optimize scheduling. The second contribution in the proposed algorithm is the bacterial evolutionary algorithm used to flexible access of the resources in order to optimize the network resources. By combining the hybrid optimization algorithm provides the better improvement in terms of task scheduling and optimal resource allocation. The result and performance analysis shows that the proposed technique performs very efficient in terms of energy efficiency and scalability without compromising security. The performance is obtained using cloudSim tool

Optimization Design of Drawbead in Drawing Tools of Autobody Cover Panel

2002 ◽  
Vol 124 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Gang Liu ◽  
Zhongqin Lin ◽  
Youxia Bao
Keyword(s):  
Optimization Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Experimental Results ◽  
Hybrid Optimization ◽  
Force Model ◽  
Hybrid Optimization Algorithm ◽  
Design Plan ◽  
Formed Part ◽  
Restraining Force

In the tooling design of autobody cover panels, design of drawbead will affect the distribution of drawing restraining force along mouth of dies and the relative flowing velocity of the blank, and consequently, will affect the distributions of strain and thickness in a formed part. Therefore, reasonable design of drawbead is the key point of cover panels’ forming quality. An optimization design method of drawbead, using one improved hybrid optimization algorithm combined with FEM software, is proposed in this paper. First, we used this method to design the distribution of drawbead restraining force along the mouth of a die, then the actual type and geometrical parameters of drawbead could be obtained according to an improved drawbead restraining force model and the improved hybrid optimization algorithm. This optimization method of drawbead was used in designing drawing tools of an actual autobody cover panel, and an optimized drawbead design plan has been obtained, by which deformation redundancy was increased from 0% under uniform drawbead control to 10%. Plastic strain of all area of formed part was larger than 2% and the minimum flange width was larger than 10 mm. Therefore, not only better formability and high dent resistance were obtained, but also fine cutting contour line and high assembly quality could be obtained. An actual drawing part has been formed using the optimized drawbead, and the experimental results were compared with the simulating results in order to verify the validity of the optimized design plan. Good agreement of thickness on critical areas between experimental results and simulation results proves that the optimization design method of drawbead could be successfully applied in designing actual tools of autobody cover panels.

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