Detecting basic topological changes in sensor networks by local aggregation

Jiang, Jixiang; Worboys, Michael

doi:10.1145/1463434.1463440

Cited by 27 publications

(30 citation statements)

References 20 publications

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“…above threshold) and do not approximate. Worboys' work such as [5], [8] employ combinatorial maps and triangulations as the basic elements in describing the qualitative/quantitative change of spatio-temporal fields monitored by geosensors. The paper [13] uses Voronoi cell (VC) to partition the sensors for simple aggregation queries.…”

Section: B Methods Utilizing Spatial Partitionmentioning

confidence: 99%

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Low Cost Region Detection from Distributed Sensor Observations

Zhang

Huang

2010

2010 Eleventh International Conference on Mobile Data Management

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Abstract-The applications of wireless sensor networks often require region representations of the phenomena that the networks monitor for visualization and interaction with spatial databases. However, there is a fundamental gap between the point-based sensor observation of non-regular sensor deployment and the spatio-temporal phenomena represented by regions. This paper proposes to bridge the gap by providing lowcommunication-cost approaches to create regions from the distributed sensors. The solution is based on Spatial Grid partition and the task is distributed among a set of sensors called "cell leaders". We formalize the problem of cell-leader selection with the objective of minimizing sensor communication cost. We propose two heuristic algorithms, i.e., Greedy Lattice Search and Subregion Centroid Approximation. We also propose EnergyAware Local Update model to allow the dynamic re-assignment of cell leaders. The experiments performed on a real sensor observation dataset demonstrated that our heuristic approaches can achieve much better communication cost compared with the baseline methods.

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Section: B Methods Utilizing Spatial Partitionmentioning

confidence: 99%

“…Closely related work includes edge/boundary [10], [11], [3], [1] and contour [4], [15], [19] detection in sensor fields, as well as qualitative/quantitative geosensor field description/monitoring [5], [8]. We classify related work based on whether spatial partition methods are used in their methods.…”

Section: Related Workmentioning

confidence: 99%

Low Cost Region Detection from Distributed Sensor Observations

Zhang

Huang

2010

2010 Eleventh International Conference on Mobile Data Management

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“…However, this model does not discuss the topological change of a moving region. Worboy's group studies topological changes of moving regions in wireless sensor networks, such as region appear, region merge, hole appear, and detects these changes with the help of the sensor devices [8,3]. Their research is application oriented which has not formally defined all possible topological changes, and the method does not discuss how to map sub-components properly between two snapshots.…”

Section: Related Workmentioning

confidence: 99%

“…However, it remains one simple region without splitting into two parts. This kind of change is called topology-preserving change [3]. In this paper, we mainly focus on the discussion of the internal topological changes of a moving region since they are more important in some applications.…”

Section: Moving Regionsmentioning

confidence: 99%

Tracking continuous topological changes of complex moving regions

Liu

Schneider

2011

Proceedings of the 2011 ACM Symposium on Applied Computing

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A moving region whose location and extend change over time can imply topological changes such as region split and hole formation. To study this phenomenon is useful in many applications, e.g. the topology control of wireless sensor networks and emergency handling. It is challenging to detect the topological changes of a moving region since we lack the ability to capture its continuous change of shapes all the time. Moreover, for a complex moving region containing multiple components, it is hard to determine which component before the change corresponds to which component after the change. In this paper, we propose a model to determine topological changes of a complex moving region through snapshots called observations. We introduce a twophase strategy that the first phase partitions the observations into several evaluation units and uniquely maps a unit before the change to exactly one unit after the change; the second phase interprets the topological change by integrating all basic topological changes from evaluation units.

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“…A large amount of existing work on qualitative approaches to characterize topology and topological changes in sensor network exists, e.g., [7]. This paper is distinguished from other related work by using edge sequences for qualitative reasoning.…”

Section: Related Workmentioning

confidence: 99%

Detecting Change in Snapshot Sequences

Shi

Winter

2010

Geographic Information Science

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Abstract. Wireless sensor networks are deployed to monitor dynamic geographic phenomena, or objects, over space and time. This paper presents a new spatiotemporal data model for dynamic areal objects in sensor networks. Our model supports for the first time the analysis of change in sequences of snapshots that are captured by different granularity of observations, and our model allows both incremental and nonincremental changes. This paper focuses on detecting qualitative spatial changes, such as merge and split of areal objects. A decentralized algorithm is developed, such that spatial changes can be efficiently detected by in-network aggregation of decentralized datasets.

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Detecting basic topological changes in sensor networks by local aggregation

Cited by 27 publications

References 20 publications

Low Cost Region Detection from Distributed Sensor Observations

Low Cost Region Detection from Distributed Sensor Observations

Tracking continuous topological changes of complex moving regions

Detecting Change in Snapshot Sequences

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