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CE-Storm: Confidential Elastic Processing of Data Streams

Authors:

Nick R. Katsipoulakis,

Eric A. Gratta,

Alexandros Labrinidis,

Panos K. ChrysanthisAuthors Info & Claims

SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

Pages 859 - 864

https://doi.org/10.1145/2723372.2735357

Published: 27 May 2015 Publication History

Abstract

Data Stream Management Systems (DSMS) are crucial for modern high-volume/high-velocity data-driven applications, necessitating a distributed approach to processing them. In addition, data providers often require certain levels of confidentiality for their data, especially in cases of user-generated data, such as those coming out of physical activity/health tracking devices (i.e., our motivating application). This demonstration will showcase Synefo, an infrastructure that enables elastic scaling of DSMS operators, and CryptStream, a framework that provides confidentiality and access controls for data streams while allowing computation on untrusted servers, fused as CE-Storm. We will demonstrate both systems working in tandem and also visualize their behavior over time under different scenarios.

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Cited By

Katsipoulakis NLabrinidis AChrysanthis P(2021)Improving Stream Load Balance through Shedding2021 IEEE 37th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW53142.2021.00028(120-126)Online publication date: Apr-2021
https://doi.org/10.1109/ICDEW53142.2021.00028
Katsipoulakis NLabrinidis AChrysanthis P(2020)SPEAr: Expediting Stream Processing with Accuracy Guarantees2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00100(1105-1116)Online publication date: Apr-2020
https://doi.org/10.1109/ICDE48307.2020.00100
Shein AChrysanthis PLabrinidis A(2019)Processing of Aggregate Continuous Queries in a Distributed EnvironmentReal-Time Business Intelligence and Analytics10.1007/978-3-030-24124-7_4(45-62)Online publication date: 11-Oct-2019
https://doi.org/10.1007/978-3-030-24124-7_4
Show More Cited By

Index Terms

CE-Storm: Confidential Elastic Processing of Data Streams
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
      2. Parallel and distributed DBMSs
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Information & Contributors

Information

Published In

cover image ACM Conferences

SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

May 2015

2110 pages

ISBN:9781450327589

DOI:10.1145/2723372

General Chair:
Timos Sellis
RMIT University, Australia
,
Program Chairs:
Susan B. Davidson
University of Pennsylvania, USA
,
Zack Ives
University of Pennsylvania, USA

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2015

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Funding Sources

National Science Foundation

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SIGMOD/PODS'15

Sponsor:

SIGMOD

SIGMOD/PODS'15: International Conference on Management of Data

May 31 - June 4, 2015

Victoria, Melbourne, Australia

Acceptance Rates

SIGMOD '15 Paper Acceptance Rate 106 of 415 submissions, 26%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Katsipoulakis NLabrinidis AChrysanthis P(2021)Improving Stream Load Balance through Shedding2021 IEEE 37th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW53142.2021.00028(120-126)Online publication date: Apr-2021
https://doi.org/10.1109/ICDEW53142.2021.00028
Katsipoulakis NLabrinidis AChrysanthis P(2020)SPEAr: Expediting Stream Processing with Accuracy Guarantees2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00100(1105-1116)Online publication date: Apr-2020
https://doi.org/10.1109/ICDE48307.2020.00100
Shein AChrysanthis PLabrinidis A(2019)Processing of Aggregate Continuous Queries in a Distributed EnvironmentReal-Time Business Intelligence and Analytics10.1007/978-3-030-24124-7_4(45-62)Online publication date: 11-Oct-2019
https://doi.org/10.1007/978-3-030-24124-7_4
Wu GYun XWang SFu GLi CLiu YLi BWang YZhao Z(2019)Accelerating Real-Time Tracking Applications over Big Data Stream with Constrained SpaceDatabase Systems for Advanced Applications10.1007/978-3-030-18576-3_1(3-18)Online publication date: 24-Apr-2019
https://doi.org/10.1007/978-3-030-18576-3_1
Katsipoulakis NLabrinidis AChrysanthis P(2018)Concept-Driven Load Shedding: Reducing Size and Error of Voluminous and Variable Data Streams2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8622265(418-427)Online publication date: Dec-2018
https://doi.org/10.1109/BigData.2018.8622265
Sun DYan HGao SLiu XBuyya R(2018)Rethinking elastic online scheduling of big data streaming applications over high-velocity continuous data streamsThe Journal of Supercomputing10.1007/s11227-017-2151-274:2(615-636)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s11227-017-2151-2
Wang SWu GLi BJin XFu GLi CZhang J(2018)Improving Large-Scale Fingerprint-Based Queries in Distributed InfrastructureComputational Science – ICCS 201810.1007/978-3-319-93713-7_36(425-433)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-93713-7_36
(2017)Fast-FFAInternational Journal of Bio-Inspired Computation10.1504/IJBIC.2017.08671710:3(205-217)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJBIC.2017.086717
Katsipoulakis NLabrinidis AChrysanthis P(2017)A holistic view of stream partitioning costsProceedings of the VLDB Endowment10.14778/3137628.313763910:11(1286-1297)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.14778/3137628.3137639
Wu GYun XLi CWang SWang YZhang XJia SZhang G(2017)Supporting Real-Time Analytic Queries in Big and Fast Data EnvironmentsDatabase Systems for Advanced Applications10.1007/978-3-319-55699-4_29(477-493)Online publication date: 22-Mar-2017
https://doi.org/10.1007/978-3-319-55699-4_29
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