Big data interpolation an efficient sampling alternative for sensor data aggregation (Extended Abstract)

Hadassa Daltrophe, Shlomi Dolev, Zvi Lotker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Given a large set of measurement sensor data, in order to identify a simple function that captures the essence of the data gathered by the sensors, we suggest representing the data by (spatial) functions, in particular by polynomials. Given a (sampled) set of values, we interpolate the datapoints to define a polynomial that would represent the data. The interpolation is challenging, since in practice the data can be noisy and even Byzantine, where the Byzantine data represents an adversarial value that is not limited to being close to the correct measured data. We present two solutions, one that extends the Welch-Berlekamp technique in the case of multidimensional data, and copes with discrete noise and Byzantine data, and the other based on Arora and Khot techniques, extending them in the case of multidimensional noisy and Byzantine data.

Original languageEnglish
Title of host publicationAlgorithms for Sensor Systems - 8th International Symposium on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities, ALGOSENSORS 2012, Revised Selected Papers
PublisherSpringer Verlag
Pages66-77
Number of pages12
ISBN (Print)9783642360916
DOIs
StatePublished - 2013
Externally publishedYes
Event8th International Symposium on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities, ALGOSENSORS 2012 - Ljubljana, Slovenia
Duration: 13 Sep 201214 Sep 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7718 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Symposium on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities, ALGOSENSORS 2012
Country/TerritorySlovenia
CityLjubljana
Period13/09/1214/09/12

Bibliographical note

Funding Information:
Partially supported by a Russian Israeli grant from the Israeli Ministry of Science and Technology #85387301-“Algorithmic approaches to energy savings” and the Russian Foundation for Basic Research, the Rita Altura Trust Chair in Computer Sciences, the Lynne and William Frankel Center for Computer Sciences, Israel Science Foundation (grant number 428/11), Cabarnit Cyber Security MAGNET Consortium, Grant from the Institute for Future Defense Technologies Research named for the Medvedi of the Technion, MAFAT, and Israeli Internet Association.

Funding

Partially supported by a Russian Israeli grant from the Israeli Ministry of Science and Technology #85387301-“Algorithmic approaches to energy savings” and the Russian Foundation for Basic Research, the Rita Altura Trust Chair in Computer Sciences, the Lynne and William Frankel Center for Computer Sciences, Israel Science Foundation (grant number 428/11), Cabarnit Cyber Security MAGNET Consortium, Grant from the Institute for Future Defense Technologies Research named for the Medvedi of the Technion, MAFAT, and Israeli Internet Association.

FundersFunder number
Institute for Future Defense Technologies Research
Israeli Internet Association
Lynne and William Frankel Center for Computer Sciences, Israel Science Foundation428/11
Rita Altura Trust
Russian Foundation for Basic Research
Ministry of science and technology, Israel85387301
Technion-Israel Institute of Technology

    Keywords

    • Big Data
    • Data Interpolation
    • Sampling
    • Sensor Data Aggregation
    • Spatial Sensor Inputs

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