Energy-Efficient Continuous Isoline Queries in Sensor Networks

Silberstein, Adam; Braynard, R.; Yang, Jun

doi:10.1109/icde.2006.62

Cited by 20 publications

(31 citation statements)

References 9 publications

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“…In this section we explain constraint chaining (CONCH) [19], a technique that monitors constraints between adjacent nodes rather than the absolute values of nodes themselves. Like other recent work in efficient monitoring, CONCH uses a combination of spatial and temporal suppression to reduce network traffic.…”

Section: Constraint Chainingmentioning

confidence: 99%

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Evaluating Efficient Data Collection Algorithms for Environmental Sensor Networks

Evans

Bähr

Martinoli

2013

Springer Tracts in Advanced Robotics

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Although there exists a large body of work on efficient data collection in sensor networks, the vast majority of proposed techniques have not been implemented on real networks or thoroughly studied on real data. As algorithm performance is highly dependent on the characteristics of the data being reported, it is very difficult to make suggestions as to the relative performance of any particular method. In this work we seek to compare and evaluate existing approaches to efficient data gathering in the specific context of environmental monitoring. We examine a choice algorithm that has not, to the best of our knowledge, been thoroughly studied on real data. We detail a number of algorithmic modifications necessary to bring it from theory to reality, and study the algorithm's performance in simulation using extensive traces from real world sensor network deployments.

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Section: Constraint Chainingmentioning

confidence: 99%

“…Their program accounts for the per-message and per-byte sending and receiving costs for the radios used as well as the number of messages required given a particular configuration. Again, the details of this formulation are left to [19].…”

Section: Basic Algorithmmentioning

confidence: 99%

Evaluating Efficient Data Collection Algorithms for Environmental Sensor Networks

Evans

Bähr

Martinoli

2013

Springer Tracts in Advanced Robotics

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“…One such approach is approximation caching [12], [16]. The idea is to let the query node store a cached value along with an update threshold for each sensor; when a sensor notices that its value has surpassed the threshold, it sends an update message to the query node.…”

Section: Related Workmentioning

confidence: 99%

“…The idea is to let the query node store a cached value along with an update threshold for each sensor; when a sensor notices that its value has surpassed the threshold, it sends an update message to the query node. CONCH [16] also provides an efficient Spatio-Temporal Suppression technique in which nearby sensors with small difference in their values are also suppressed from updating. A major problem with approximation caching is the large energy overhead of the update message transmission when many sensor readings do not stay within the update threshold.…”

Section: Related Workmentioning

confidence: 99%

“…Energy efficiency for sensor networks has been an intense area of research in recent years [7], [8], [9], [10], [5], [11], [12], [13], [14], [15], [16], [17], [18]. Among these techniques, various data collection approaches have been proposed such as event detection [19], in-network aggregation [5], [6], distributed compression [13], model-based apporaches [17], [8], and data sampling [10], [18].…”

Section: Related Workmentioning

confidence: 99%

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Region Sampling: Continuous Adaptive Sampling on Sensor Networks

Lin

Arai

Gunopulos

et al. 2008

2008 IEEE 24th International Conference on Data Engineering

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Abstract-Satisfying energy constraints while meeting performance requirements is a primary concern when a sensor network is being deployed. Many recent proposed techniques offer error bounding solutions for aggregate approximation but cannot guarantee energy spending. Inversely, our goal is to bound the energy consumption while minimizing the approximation error. In this paper, we propose an online algorithm, Region Sampling, for computing approximate aggregates while satisfying a pre-defined energy budget. Our algorithm is distinguished by segmenting a sensor network into partitions of non-overlapping regions and performing sampling and local aggregation for each region. The sampling energy cost rate and sampling statistics are collected and analyzed to predict the optimal sampling plan. Comprehensive experiments on real-world data sets indicate that our approach is at a minimum of 10% more accurate compared with the previously proposed solutions.

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Real-Time Data Analytics in Sensor Networks

Palpanas

2012

Managing and Mining Sensor Data

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Abstract. The proliferation of Wireless Sensor Networks (WSNS) in the past decade has provided the bridge between the physical and digital worlds, enabling the monitoring and study of physical phenomena at a granularity and level of detail that was never before possible. In this study, we review the efforts of the research community with respect to two important problems in the context of WSNS: real-time collection of the sensed data, and real-time processing of these data series.

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Energy-Efficient Continuous Isoline Queries in Sensor Networks

Cited by 20 publications

References 9 publications

Evaluating Efficient Data Collection Algorithms for Environmental Sensor Networks

Evaluating Efficient Data Collection Algorithms for Environmental Sensor Networks

Region Sampling: Continuous Adaptive Sampling on Sensor Networks

Real-Time Data Analytics in Sensor Networks

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