Section: New Results

Embedded Data Management

Participants : Nicolas Anciaux, Saliha Lallali, Philippe Pucheral, Iulian Sandu Popa [correspondent] .

Embedded keyword indexing: In this work, we revisit the traditional problem of information retrieval queries over large collections of files in an embedded context. A file can be any form of document, picture or data stream, associated with a set of terms. A query can be any form of keyword search using a ranking function (e.g., TF-IDF) identifying the top-k most relevant files. The proposed search engine can be used in sensors to search for relevant objects in their surroundings, in cameras to search pictures by using tags, in personal smart dongles to secure the querying of documents and files hosted in an untrusted Cloud, or in a personal cloud securely managed using a tamper resistant smart object. A search engine is usually based on a (large) inverted index and queries are traditionally evaluated by allocating one container in RAM per document to aggregate its score, making the RAM consumption linear with the size of the document corpus. To tackle this issue, we designed a new form of inverted index which can be accessed in a pure pipeline manner to evaluate search queries without materializing any intermediate result. Successive index partitions are written once in Flash and maintained in the background by timely triggering merge operations while files are inserted or deleted from the index. This work was initially published at VLDB’15 [5] and demonstrated at SIGMOD’15 [38]. It constitutes the main contribution of the PhD thesis of Saliha Lallali defended in January 2016. In 2016, we extended this work to demonstrate at EDBT’16 [22] its applicability to set up a secure distributed search engine for the Personal Cloud. We also complemented this work with (1) a thorough analysis of the RAM consumption linked to the main algorithms implementing the solution, (2) the support of conditional top-k queries in a personal Cloud context that we consider as a killer application domain today and (3) new performance measurements with a real dataset (ENRON), representative of this personal Cloud context. These new contributions have been submitted to Information Systems journal.