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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Collaborative Streaming: Trust Requirements for Price Sharing |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Page Range | 3498 - 3505 |
| Event Title | 4th Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management |
| Event Type | workshop |
| Event Location | Los Angels, CA, USA |
| Event Start Date | December 10 - 2019 |
| Event End Date | December 10 - 2019 |
| Place of Publication | Washington DC, USA |
| Publisher | IEEE |
| Abstract Text | Stream Processing (SP) is an important Big Data technology enabling continuous querying of data streams. The stream setting offers the opportunity to exploit synergies and, theoretically, share the access and processing costs between multiple different collaborators. But what should be the monetary contribution of each consumer when they do not trust each other and have varying valuations of the differing outcomes? In this article, we present Collaborative Stream Processing (CSP), a model where the costs, which are set exogenously by providers, are shared between multiple consumers, the collaborators. For this, we identify three important requirements for CSP to establish trust between the collaborators and propose a CSP al- gorithm, ENCSPA, adhering to these requirements. Based on the collaborators’ outcome valuations and the costs of the raw data streams, ENCSPA computes the payment for each collaborator. At the same time, ENCSPA ensures that no collaborator has an incentive to manipulate the system by providing misinformation about her/his value, budget, or time limit. We show that ENCSPA can calculate payments in a reasonable amount of time for up to one thousand collaborators. |
| Related URLs |
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| Digital Object Identifier | 10.1109/BigData47090.2019.9005470 |
| Other Identification Number | merlin-id:18780 |
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