QoS-aware optimization of sensor network queries

QoS-aware optimization of sensor network queries The resource-constrained nature of mote-level wireless sensor networks (WSNs) poses challenges for the design of a general-purpose sensor network query processors (SNQPs). Existing SNQPs tend to generate query execution plans (QEPs) that are selected on the basis of a fixed, implicit expectation, for example, that energy consumption should be kept as small as possible. However, in WSN applications, the same query may be subject to several, possibly conflicting, quality-of-service (QoS) expectations concomitantly (for example maximizing data acquisition rates subject to keeping energy consumption low). It is also not uncommon for the QoS expectations to change over the lifetime of a deployment (for example from low to high data acquisition rates). This paper describes optimization algorithms that respond to stated QoS expectations (about acquisition rate, delivery time, energy consumption and lifetime) when making routing, placement, and timing decisions for in-WSN query processing. The paper shows experimentally that QoS-awareness offers significant benefits in responding to, and reconciling, diverse QoS expectations, thereby enabling QoS-aware SNQPs to generate efficient QEPs for a broader range WSN applications than has hitherto been possible. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

QoS-aware optimization of sensor network queries

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2013 by Springer-Verlag Berlin Heidelberg
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-012-0300-z
Publisher site
See Article on Publisher Site

Abstract

The resource-constrained nature of mote-level wireless sensor networks (WSNs) poses challenges for the design of a general-purpose sensor network query processors (SNQPs). Existing SNQPs tend to generate query execution plans (QEPs) that are selected on the basis of a fixed, implicit expectation, for example, that energy consumption should be kept as small as possible. However, in WSN applications, the same query may be subject to several, possibly conflicting, quality-of-service (QoS) expectations concomitantly (for example maximizing data acquisition rates subject to keeping energy consumption low). It is also not uncommon for the QoS expectations to change over the lifetime of a deployment (for example from low to high data acquisition rates). This paper describes optimization algorithms that respond to stated QoS expectations (about acquisition rate, delivery time, energy consumption and lifetime) when making routing, placement, and timing decisions for in-WSN query processing. The paper shows experimentally that QoS-awareness offers significant benefits in responding to, and reconciling, diverse QoS expectations, thereby enabling QoS-aware SNQPs to generate efficient QEPs for a broader range WSN applications than has hitherto been possible.

Journal

The VLDB JournalSpringer Journals

Published: Aug 1, 2013

References

  • STREAM: the stanford stream data manager
    Arasu, A; Babcock, B; Babu, S; Datar, M; Ito, K; Motwani, R; Nishizawa, I; Srivastava, U; Thomas, D; Varma, R; Widom, J
  • A tutorial on geometric programming
    Boyd, S; Kim, S; Vandenberghe, L; Hassibi, A

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