A market-oriented hierarchical scheduling strategy in cloud workflow systems

Zhangjun Wu, Xiao Liu, Zhiwei Ni, Dong Yuan, Yun Yang
<span title="2011-03-15">2011</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qhbautqnvzgwvm3vvdvieylhwq" style="color: black;">Journal of Supercomputing</a> </i> &nbsp;
A cloud workflow system is a type of platform service which facilitates the automation of distributed applications based on the novel cloud infrastructure. One of the most important aspects which differentiate a cloud workflow system from its other counterparts is the marketoriented business model. This is a significant innovation which brings many challenges to conventional workflow scheduling strategies. To investigate such an issue, this paper proposes a market-oriented hierarchical
more &raquo; ... g strategy in cloud workflow systems. Specifically, the service-level scheduling deals with the Task-to-Service assignment where tasks of individual workflow instances are mapped to cloud services in the global cloud markets based on their functional and non-functional QoS requirements; the task-level scheduling deals with the optimisation of the Task-to-VM (virtual machine) assignment in local cloud data centres where the overall running cost of cloud workflow systems will be minimised given the satisfaction of QoS constraints for individual tasks. Based on our hierarchical scheduling strategy, a package based random scheduling algorithm is presented as the candidate service-level scheduling algorithm and three representative metaheuristic based scheduling algorithms including genetic algorithm (GA), ant colony optimisation (ACO) and particle swarm optimisation (PSO) are adapted, implemented and analysed as the candidate task-level scheduling algorithms. The hierarchical scheduling strategy is being implemented in our SwinDeW-C cloud workflow system and demonstrating satisfactory performance. Meanwhile, the experimental results show that the overall performance of ACO based scheduling algorithm is better than others on three basic measurements: the optimisation rate on makespan, the optimisation rate on cost and the CPU time. Introduction Cloud computing is emerging as the latest distributed computing paradigm and attracts increasing interests of researchers in the area of Distributed and Parallel Computing [34], Service Oriented Computing [2] and Software Engineering [38] . Though there is yet no consensus on what is Cloud, but some of its distinctive aspects as proposed by Ian Foster in [18] can be borrowed for an insight: "Cloud computing is a large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualised, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet." Compared with the definitions of conventional computing paradigms such as cluster [30], grid [17] and peer-to-peer (p2p) [45] , "economies" is a noticeable keyword in cloud computing which has been neglected by others. "Economies" denotes that cloud computing adopts market-oriented business model where users are charged for consuming cloud services such as computing, storage and network services like conventional utilities in everyday life (e.g. water, electricity, gas and telephony) [3] . Meanwhile, cloud service providers are obligated to provider satisfactory QoS (quality of service) based on business service contracts. It is evident that cloud computing is becoming the latest driving force to deliver computing as the 5 th utility besides the previous efforts on such as utility based grid computing [35] .
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11227-011-0578-4">doi:10.1007/s11227-011-0578-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6z6gtintavff3chly7npy4qh2i">fatcat:6z6gtintavff3chly7npy4qh2i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808073748/http://foresight.ifmo.ru/ict/shared/files/201312/1_157.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/98/c9/98c96f879e62bc9d246058d349afb49deedb9548.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11227-011-0578-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>