Market-Based Workflow Management

Geppert, Andreas; Kradolfer, Markus; Tombros, Dimitrios

doi:10.1142/s0218843098000143

Cited by 23 publications

(5 citation statements)

References 8 publications

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“…is based on Nimrog-G [9] and A Market-Based Workflow Management System [10] which schedules independent tasks and assign deadline of individual task respectively. In this algorithm author solved the task independency problem by considering the tasks with certain dependencies.…”

Section: Cost-based Scheduling Of Scientific Workflow Applications Onmentioning

confidence: 99%

A Journey towards Workflow Scheduling of Cloud Computing

Kumar¹,

Shukla²,

Saxena³

et al. 2015

IJCA

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Cloud computing is a type of grid computing which is a form of distributed computing and distributed computing is a special type of parallel computing. Presently a lot of services are growing under the single umbrella that is known as cloud computing. Cloud computing gain popularity in the several area due its property of everything-as-a-service(XaaS), includes SaaS, PaaS and IaaS. Many problems have been arising when we go for implementation development. Workflow scheduling and appropriate allocation of resources is one of among problems that will decrease the Quality of Service (QoS) of cloud computing. There are many algorithms to automate the workflows in a way to satisfy the Quality of service (QoS) of the user. This paper is the survey of some workflow scheduling algorithms that have been proposed for cloud computing.

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Section: Cost-based Scheduling Of Scientific Workflow Applications Onmentioning

confidence: 99%

A Journey towards Workflow Scheduling of Cloud Computing

Kumar¹,

Shukla²,

Saxena³

et al. 2015

IJCA

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“…The market-driven strategy has been applied into several Grid systems such as Nimrod-G [21] and Gridbus data resource broker [125]. One example of the market-driven workflow scheduling proposed by Geppert et al [57] utilizes market mechanisms during the task assignment. In the system, bids are collected from eligible resource providers for each task.…”

Section: Scheduling Strategymentioning

confidence: 99%

A Taxonomy of Workflow Management Systems for Grid Computing

2005

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With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.

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“…Nimrod-G [5] schedules independent tasks for parameter-sweep applications to meet users' budget. A market-based workflow management system [11] locates an optimal bid based on the budget of the current task in the workflow. More recently, Tsiakkouri et al [29] developed scheduling approaches, LOSS and GAIN, to adjust a schedule which is generated by a time optimized heuristic and a cost optimized heuristic to meet users' budget constraints respectively.…”

Section: Related Workmentioning

confidence: 99%

Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms

Buyya

2006

Scientific Programming

268

206

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Grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models, which are capable of supporting diverse computing services. It facilitates scientific applications to take advantage of computing resources distributed world wide to enhance the capability and performance. Many scientific applications in areas such as bioinformatics and astronomy require workflow processing in which tasks are executed based on their control or data dependencies. Scheduling such interdependent tasks on utility Grid environments need to consider users' QoS requirements. In this paper, we present a genetic algorithm approach to address scheduling optimization problems in workflow applications, based on two QoS constraints, deadline and budget.

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Market-Based Workflow Management

Cited by 23 publications

References 8 publications

A Journey towards Workflow Scheduling of Cloud Computing

A Journey towards Workflow Scheduling of Cloud Computing

A Taxonomy of Workflow Management Systems for Grid Computing

Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms

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