Yadav, Piyush and ul Hassan, Umair and Hasan, Souleiman and Curry, Edward (2017) The Event Crowd: A Novel Approach for Crowd-Enabled Event Processing. In: Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems. Association for Computing Machinery, New York, pp. 44-53. ISBN 978-1-4503-5065-5

Preview

Download (1MB) | Preview

Abstract

Event processing systems involve the processing of high volume and variety data which has inherent uncertainties like incomplete event streams, imprecise event recognition etc. With the emergence of crowdsourcing platforms, the performance of event processing systems can be enhanced by including 'human-in-the-loop' to leverage their cognitive ability. The resulting crowd-sourced event processing can cater to the problem of event uncertainty and veracity by using humans to verify the results. This paper introduces the first hybrid crowd-enabled event processing engine. The paper proposes a list of five event crowd operators that are domain and language independent and can be used by any event processing framework. These operators encapsulate the complexities to deal with crowd workers and allow developers to define an event-crowd hybrid workflow. The operators are: Annotate, Rank, Verify, Rate, and Match. The paper presents a proof of concept of event crowd operators, schedulers, poolers, aggregators in an event processing system. The paper demonstrates the implementation of these operators and simulates the system with various performance metrics. The experimental evaluation shows that throughput of the system was 7.86 events per second with average latency of 7.16 seconds for 100 crowd workers. Finally, the paper concludes with avenues for future research in crowd-enabled event processing.

Item Type:	Book Section
Additional Information:	This paper was presented at the 11th ACM International Conference on Distributed and Event-based Systems, Barcelona, Spain, June 19 - 23, 2017
Keywords:	Event crowd; event processing; crowdsourcing; human-in-the-loop; event uncertainty;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > School of Business
Item ID:	11994
Identification Number:	https://doi.org/10.1145/3093742.3093922
Depositing User:	Souleiman Hasan
Date Deposited:	05 Dec 2019 14:20
Publisher:	Association for Computing Machinery
Refereed:	Yes
URI:	Publisher Organisation
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads