Optimized Execution of Business Processes on Crowdsourcing Platforms

Khazankin, Roman; Satzger, Benjamin; Dustdar, Schahram

doi:10.4108/icst.collaboratecom.2012.250434

Cited by 20 publications

(14 citation statements)

References 11 publications

(11 reference statements)

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“…Several studies have been conducted to determine when and how to publish the tasks on the crowdsourcing platform to complete the workflows with minimum cost and without missing the deadlines. Khazankin et al formulated the problem as a time-constrained optimization problem [30]. Tang et al adopted heuristic strategies to improve Khazankin et al's work [31].…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Fairness of Task Allocation in Crowdsourcing Workflows

Liu

2021

Mathematical Problems in Engineering

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Fairness plays a vital role in crowd computing by attracting its workers. The power of crowd computing stems from a large number of workers potentially available to provide high quality of service and reduce costs. An important challenge in the crowdsourcing market today is the task allocation of crowdsourcing workflows. Requester-centric task allocation algorithms aim to maximize the completion quality of the entire workflow and minimize its total cost, which are discriminatory for workers. The crowdsourcing workflow needs to balance two objectives, namely, fairness and cost. In this study, we propose an alternative greedy approach with four heuristic strategies to address such an issue. In particular, the proposed approach aims to monitor the current status of workflow execution and use heuristic strategies to adjust the parameters of task allocation. We design a two-phase allocation model to accurately match the tasks with workers. The F-Aware allocates each task to the worker that maximizes the fairness and minimizes the cost. We conduct extensive experiments to quantitatively evaluate the proposed algorithms in terms of running time, fairness, and cost by using a customer objective function on the WorkflowSim, a well-known cloud simulation tool. Experimental results based on real-world workflows show that the F-Aware, which is 1% better than the best competitor algorithm, outperforms other optimal solutions in finding the tradeoff between fairness and cost.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Fairness of Task Allocation in Crowdsourcing Workflows

Liu

2021

Mathematical Problems in Engineering

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“…was among the earliest researchers that asked "how does crowdsourcing become an extension of the existing business process" (p. 7). Khazankin et al (2012a) echo the question and complained about "the lack of an integrated way to execute business processes based on a crowdsourcing [platform]" (p. 1). Similarly, Lüttgens et al (2014) have recently emphasised the need to build a dedicated process for crowdsourcing.…”

Section: Crowdsourcing Process and Business Process Crowdsourcingmentioning

confidence: 99%

“…Second, we propose a model for BPC that identifies the critical components that organisations should consider when integrating a crowdsourcing strategy. By adopting a process-centred perspective, the model addresses the current lack of a way to organise business processes based on crowdsourcing (Khazankin et al 2012a;Satzger et al 2011). Third, through the case study approach, the study evaluates the adequateness and utility of the model in two crowdsourcing projects.…”

Section: Introductionmentioning

confidence: 99%

A Process Model for Establishing Business Process Crowdsourcing

Thuan

Antunes

Johnstone

2017

AJIS

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Crowdsourcing can be an organisational strategy to distribute work to Internet users and harness innovation, information, capacities, and variety of business endeavours. As crowdsourcing is different from other business strategies, organisations are often unsure as to how to best structure different crowdsourcing activities and integrate them with other organisational business processes. To manage this problem, we design a process model guiding how to establish business process crowdsourcing. The model consists of seven components covering the main activities of crowdsourcing processes, which are drawn from a knowledge base incorporating diverse knowledge sources in the domain. The built model is evaluated using case studies, suggesting the adequateness and utility of the model.

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“…This integration can be achieved in various ways, next to the one that we describe in this article. For example, Khazankin et al [2012] present an approach to an adaptable execution of business processes on top of a CS platform. Its main peculiarity is the ability to determine optimal task publishing procedures, adapting them to modeled process deadlines and minimizing the reward cost.…”

Section: Process Modeling Approachesmentioning

confidence: 99%

Modeling, Enacting, and Integrating Custom Crowdsourcing Processes

et al. 2015

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Crowdsourcing (CS) is the outsourcing of a unit of work to a crowd of people via an open call for contributions. Thanks to the availability of online CS platforms, such as Amazon Mechanical Turk or CrowdFlower, the practice has experienced a tremendous growth over the past few years and demonstrated its viability in a variety of fields, such as data collection and analysis or human computation. Yet it is also increasingly struggling with the inherent limitations of these platforms: each platform has its own logic of how to crowdsource work (e.g., marketplace or contest), there is only very little support for structured work (work that requires the coordination of multiple tasks), and it is hard to integrate crowdsourced tasks into stateof-the-art business process management (BPM) or information systems. We attack these three shortcomings by (1) developing a flexible CS platform (we call it Crowd Computer, or CC) that allows one to program custom CS logics for individual and structured tasks, (2) devising a BPMN-based modeling language that allows one to program CC intuitively, (3) equipping the language with a dedicated visual editor, and (4) implementing CC on top of standard BPM technology that can easily be integrated into existing software and processes. We demonstrate the effectiveness of the approach with a case study on the crowd-based mining of mashup model patterns.

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Optimized Execution of Business Processes on Crowdsourcing Platforms

Cited by 20 publications

References 11 publications

Fairness of Task Allocation in Crowdsourcing Workflows

Fairness of Task Allocation in Crowdsourcing Workflows

A Process Model for Establishing Business Process Crowdsourcing

Modeling, Enacting, and Integrating Custom Crowdsourcing Processes

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