Approximate aggregation techniques for sensor databases

Considine, Jeffrey; Li, F.; Kollios, George; Byers, John W.

doi:10.1109/icde.2004.1320018

Cited by 385 publications

(409 citation statements)

References 24 publications

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“…Node s forwards a sequence of tuples to its parent P s during a round. It numbers these sequentially, e.g., (1,2,3,4,5,6). The highest sequence number is labeled n max = 6.…”

Section: Lazaridis Et Almentioning

confidence: 99%

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Fault Tolerant Evaluation of Continuous Selection Queries over Sensor Data

Lazaridis

Han

Mehrotra

et al. 2009

International Journal of Distributed Sensor Networks

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We consider the problem of evaluating continuous selection queries over sensorgenerated values in the presence of faults. Small sensors are fragile, have finite energy and memory, and communicate over a lossy medium; hence, tuples produced by them may not reach the querying node, resulting in an incomplete and ambiguous answer, as any of the non-reporting sensors may have produced a tuple which was lost. We develop a protocol, FAult Tolerant Evaluation of Continuous Selection Queries (FATE-CSQ), which guarantees a user-requested level of quality in an efficient manner. When many faults occur, this may not be achievable; in that case, we aim for the best possible answer, under the query's time constraints. FATE-CSQ is designed to be resilient to different kinds of failures. Our design decisions are based on an analytical model of different fault tolerance strategies based on feedback and retransmission. Additionally, we evaluate FATE-CSQ and competing protocols with realistic simulation parameters under a variety of conditions, demonstrating its good performance.

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“…Node s forwards a sequence of tuples to its parent P s during a round. It numbers these sequentially, e.g., (1,2,3,4,5,6). The highest sequence number is labeled n max = 6.…”

Section: Lazaridis Et Almentioning

confidence: 99%

“…Limiting the effects of faults has been studied in the past by TAG [15] and SKETCH [6] for aggregate queries. In TAG, a routing tree is formed during the query dissemination phase.…”

mentioning

confidence: 99%

Fault Tolerant Evaluation of Continuous Selection Queries over Sensor Data

Lazaridis

Han

Mehrotra

et al. 2009

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

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“…If the estimated error is acceptable, a node conserves energy by querying the local model. Another popular approach provides approximate answers that trade accuracy for energy efficiency [16]. We calculate the error on demand at query time since pro-actively maintaining local models can be expensive in mobile environments.…”

Section: Related Workmentioning

confidence: 99%

Automated Assessment of Aggregate Query Imprecision in Dynamic Environments

Rajamani

Julien

Payton

2009

Distributed Applications and Interoperable Systems

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Abstract. Queries are widely used for acquiring data distributed in opportunistically formed mobile networks. However, when queries are executed in such dynamic settings, the returned result may not be consistent, i.e., it may not accurately reflect the state of the environment. It can thus be difficult to reason about the meaning of a query's result. Reasoning about imperfections in the result becomes even more complex when in-network aggregation is employed, since only a single aggregate value is returned. We define the semantics of aggregate queries in terms of a qualitative description of consistency and a quantitative measure of imprecision. We provide a protocol that performs in-network aggregation while simultaneously generating quality assessments for the query result. The protocol enables intuitive interpretations of the semantics associated with an aggregate query's execution in a dynamic environment.

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“…All these techniques are complementary to our work, as they provide the necessary network primitives that we need to build our messaging scheme. In [4], a novel framework that uses sketching techniques for compensating for packet loss and node failures during query evaluation is proposed. Complementing our framework in order to take advantage of the work in [4] is an interesting future direction.…”

Section: Related Workmentioning

confidence: 99%

Robust management of outliers in sensor network aggregate queries

Kotidis

Vassalos

Deligiannakis

et al. 2007

Proceedings of the 6th ACM International Workshop on Data Engineering for Wireless and Mobile Access

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Sensor networks are increasingly applied for monitoring diverse environments and applications. Due to their unsupervised nature of operation and inexpensive hardware used, sensor nodes may furnish readings of rather poor quality. We thus need to devise techniques that can withstand "dirty" data during query processing. In this paper we introduce a robust aggregation framework that can detect and isolate spurious measurements from computed aggregate values. Such readings are not injected in the reported aggregate, in order not to obscure the outcome, but are still maintained and returned to the user/application, which may investigate them further and take appropriate decisions. In addition, our framework provides a form of positive feedback to the user by enhancing the result with a set of nodes that contain the most characteristic values out of those included in the aggregation process. We perform an extensive experimental evaluation of our framework using real traces of sensory data and demonstrate its utility to the monitoring of applications.

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Approximate aggregation techniques for sensor databases

Abstract: In

Cited by 385 publications

References 24 publications

Fault Tolerant Evaluation of Continuous Selection Queries over Sensor Data

Fault Tolerant Evaluation of Continuous Selection Queries over Sensor Data

Automated Assessment of Aggregate Query Imprecision in Dynamic Environments

Robust management of outliers in sensor network aggregate queries

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