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A database in every sensor

Published: 01 November 2011 Publication History

Abstract

We make the case for a sensor network model in which each mote stores sensor data locally, and provides a database query interface to the data. Unlike TinyDB and Cougar, in which a sink node provides a database-like front end for filtering the current sensor values from a data collection network, we propose that each sensor device should run its own database system. We present Antelope, a database management system for resource-constrained sensors. Antelope provides a dynamic database system that enables run-time creation and deletion of databases and indexes. Antelope uses energy-efficient indexing techniques that significantly improve the performance of queries. The energy cost of a query that selects 100 tuples is less than the cost of a single packet transmission. Moving forward, we believe that database techniques will be increasingly important in many emerging applications.

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cover image ACM Conferences
SenSys '11: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
November 2011
452 pages
ISBN:9781450307185
DOI:10.1145/2070942
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 ACM 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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Publication History

Published: 01 November 2011

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Author Tags

  1. antelope
  2. database
  3. energy efficiency
  4. sensor network

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Overall Acceptance Rate 174 of 867 submissions, 20%

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Cited By

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  • (2024)EmbedDB: A High-Performance Database for Resource-Constrained Embedded Systems Too Small for SQLiteProceedings of the 39th ACM/SIGAPP Symposium on Applied Computing10.1145/3605098.3636116(345-346)Online publication date: 8-Apr-2024
  • (2022)SMART-LAMP: A Smartphone-Operated Handheld Device for Real-Time Colorimetric Point-of-Care Diagnosis of Infectious Diseases via Loop-Mediated Isothermal AmplificationBiosensors10.3390/bios1206042412:6(424)Online publication date: 16-Jun-2022
  • (2022)An Intelligent Cluster Verification Model Using WSN to Avoid Close Proximity and Control Outbreak of Pandemic in a Massive CrowdComputer Modeling in Engineering & Sciences10.32604/cmes.2022.020791133:2(327-350)Online publication date: 2022
  • (2022)Performance Evaluation of Embedded Time Series Indexes Using Bitmaps, Partitioning, and TreesSensor Networks10.1007/978-3-031-17718-7_7(125-151)Online publication date: 27-Sep-2022
  • (2021)Adaptive flash sorting for memory-constrained embedded devicesProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3441914(321-326)Online publication date: 22-Mar-2021
  • (2021)Smart environmental data management system into a cattle buildingE3S Web of Conferences10.1051/e3sconf/202123400033234(00033)Online publication date: 2-Feb-2021
  • (2021)An Overview of Constraints of Operating Systems Used in IoT DevicesProceedings of Integrated Intelligence Enable Networks and Computing10.1007/978-981-33-6307-6_86(835-844)Online publication date: 24-Apr-2021
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  • (2020)Linear Hashing Implementations for Flash MemoryEnterprise Information Systems10.1007/978-3-030-40783-4_18(386-405)Online publication date: 20-Feb-2020
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