Planar graph routing on geographical clusters

Frey, Hannes; Görgen, Daniel

doi:10.1016/j.adhoc.2004.08.013

Cited by 20 publications

(31 citation statements)

References 15 publications

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“…As perimeter routing (and other recovery techniques using planarized graphs) requires longer path length in networks with higher node density this problem becomes worse with increasing node densities [12]. Perimeter routing may also take unnecessarily long paths when traversing faces in the ''wrong'' direction.…”

Section: The Euclidian Distance Metricmentioning

confidence: 98%

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Non-Euclidian geographic routing in wireless networks

Carlsson¹,

Eager²

2007

Ad Hoc Networks

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Section: The Euclidian Distance Metricmentioning

confidence: 98%

“…Perimeter routing (and similar recovery methods) generally requires longer path lengths as the node density increases [12]. Thus, the benefits of LBLSP are expected to increase with increasing node densities.…”

Section: Performance Evaluationmentioning

confidence: 99%

Non-Euclidian geographic routing in wireless networks

Carlsson¹,

Eager²

2007

Ad Hoc Networks

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“…This identifier could be globally unique for the cell, perhaps derived from its geographical location, but this is not necessary. Allocating identifiers to cells is beyond the scope of DCAP but is addressed in the literature [19].…”

Section: B Intra-and Extra-cellular Discriminationmentioning

confidence: 99%

A feedback-driven timing synchronisation protocol for cellular sensornets

Tate

Bate

2010

The 7th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (IEEE MASS 2010)

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Abstract-Interaction between sensornet nodes and the physical environment in which they are embedded implies realtime requirements. Application tasks must be executed in the correct place, and in the correct order, for correct application behaviour. Sensornets generally have no global clock, and incur unacceptable cost if traditional synchronisation protocols are implemented. We present a lightweight primitive which generates a periodic sequence of synchronisation events which are coordinated across large sensornets structured into clusters or cells. Two biologically-inspired mechanisms are combined; desynchronisation within cells, and synchronisation between cells. This hierarchical coordination provides a global basis for local application-driven timing decisions at each node.

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“…Greedy routing might get stuck at convex network boundaries or at network voids inside the monitored area where sensor nodes can't be deployed (e.g. a lake inside the monitored area) [4].…”

Section: Related Workmentioning

confidence: 99%

“…In this work we will relate sensing and communication range of sensing covered networks in order to derive a theoretical result about the delivery guarantee of a geographical cluster based routing algorithm which was recently described in [4]. Related geographic routing algorithms, the concept of geographical clusters, and finally the algorithm analyzed in this work will be described in the next Section.…”

Section: Introductionmentioning

confidence: 98%

Geographical Cluster Based Routing in Sensing-Covered Networks

Frey

Görgen

25th IEEE International Conference on Distributed Computing Systems Workshops

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The relationship between coverage and connectivity in sensor networks has been investigated in recent research treating both network parameters in a unified framework. It is known that networks covering a convex area are connected if the communication range of each node is at least twice a unique sensing range used by each node. Furthermore, geographic greedy routing is a viable and effective approach providing guaranteed delivery for this special network class. In this work we will show that the result about network connectivity does not suffer from generalizing the concept of sensing coverage to arbitrary network deployment regions. However, dropping the assumption that the monitored area is convex requires the application of greedy recovery strategies like traversing a locally extracted planar subgraph. A recently proposed variant performs message forwarding along edges of a virtual overlay graph instead of using wireless links for planar graph construction directly. However, there exist connected network configurations where this routing variant may fail. In this work we will proof a theoretical bound which is a sufficient condition for guaranteed delivery of this routing strategy applied in sensing covered networks. By simulation results we show that this bound may also be relaxed from a practical point of view and that geographical cluster based routing achieves a comparable performance compared to other planar graph routing variants based on two-hop neighbor information.

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Planar graph routing on geographical clusters

Cited by 20 publications

References 15 publications

Non-Euclidian geographic routing in wireless networks

Non-Euclidian geographic routing in wireless networks

A feedback-driven timing synchronisation protocol for cellular sensornets

Geographical Cluster Based Routing in Sensing-Covered Networks

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