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Achieving fast operational intelligence in NASA's Deep Space Network through complex event processing

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dc.contributor.author Choi, Joshua S.
dc.contributor.author Verma, Rishi
dc.contributor.author Malhotra, Shan
dc.date.accessioned 2019-05-16T16:59:53Z
dc.date.available 2019-05-16T16:59:53Z
dc.date.issued 2016-05-16
dc.identifier.citation SpaceOps 2016 Conference, Daejeon, Korea, May 16-20, 2016 en_US
dc.identifier.clearanceno 16-1722
dc.identifier.uri http://hdl.handle.net/2014/46098
dc.description.abstract NASA’s Deep Space Network (DSN) is a complex, global project, in which the expertise of human operators remain crucial for its successful operation. To find ways to save costs in operations and to improve its services, a number of modernization efforts are underway in the DSN. One such effort is a research and technology development task at the Jet Propulsion Laboratory that is investigating the use of complex event processing (CEP) for intelligent assessment of situations, trend analysis, and advanced automation. The technology leverages the significant business intelligence (BI) and data science advancements made in the enterprise industries over the last several years. The open source big data processing engine Apache SparkTM and the high-throughput, distributed messaging system Apache Kafka form the core of the DSN Complex Event Processing (DCEP) framework. This paper discusses the system engineering perspective of why achieving efficient, lower-cost operations in the DSN is a challenging problem, how the DCEP system handles the use cases that help realize intelligent operations, and how this solution fits into the overall model of the planned DSN Follow-the- Sun Operations (FtSO). en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2016 en_US
dc.title Achieving fast operational intelligence in NASA's Deep Space Network through complex event processing en_US
dc.type Preprint en_US


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