Objective
Large scale data analytics is the key research domain for future data driven applications as numerous of devices produce huge volumes of data in the form of streams. Analytics services can offer the necessary basis for building intelligent decision making mechanisms to support novel applications. Due to the huge volumes of data, analytics should be based on efficient schemes for querying large scale data partitions. Partitions contain only a piece of data and a dedicated processor manages the incoming queries. The management of continuous queries over data streams is a challenging research issue requiring intelligent methods to derive the final outcome (i.e. query response) in limited time with maximum performance. The management process of continuous queries involves their assignment to specific processors and the processing of the derived responses. We focus on a group of query controllers serving the incoming queries and, thus, becoming the connection of big data systems with the real world. INNOVATE proposes solutions for the management of the controllers behavior. We propose an intelligent decision making process for each controller in three axes: (i) top-down, by realizing a mechanism that assigns queries to the underlying processors; (ii) bottom-up, by proposing decision making mechanisms for returning responses to users/applications on top of early results; (iii) horizontal, by proposing optimization schemes for queries management. We adopt a pool of learning schemes and an ensemble learning model dealing with how and on which processors each query should be assigned. We also propose specific schemes for combining processors responses. Intelligent and optimization techniques are adopted for the controllers group management. Machine learning, Computational Intelligence and optimization are the key adopted technologies that, when combined, provide efficient solutions to a challenging problem like the support of intelligent analytics over big data streams.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences data science big data
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2016
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
G12 8QQ Glasgow
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.