Worst-Case optimal and average-case efficient geometric ad-hoc routing

Kühn, Fabian; Wattenhofer, Rogert; Zollinger, Aaron

doi:10.1145/778415.778447

Cited by 413 publications

(252 citation statements)

References 26 publications

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“…Karp and Kung [10] introduce a hybrid scheme, which combines a greedy routing strategy with face routing. Similar hybrid schemes were subsequently studied by several other researchers [8,15,14,16]. An alternative hybrid augmented greedy scheme is introduced by Carlsson and Eager [3].…”

Section: Prior Related Workmentioning

confidence: 96%

“…In this alternative approach, called geometric routing [2,10,8,15,14,16] or geographic routing [11], the graph G is drawn in a geometric metric space S in the standard way, so that vertices are drawn as points in S and each edge is drawn as the loci of points along the shortest path between its two endpoints. For example, if S is the Euclidean plane, R 2 , then edges would be drawn as straight line segments in this approach.…”

Section: Introductionmentioning

confidence: 99%

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Succinct Greedy Graph Drawing in the Hyperbolic Plane

Eppstein

Goodrich

2009

Graph Drawing

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Abstract. We describe an efficient method for drawing any n-vertex simple graph G in the hyperbolic plane. Our algorithm produces greedy drawings, which support greedy geometric routing, so that a message M between any pair of vertices may be routed geometrically, simply by having each vertex that receives M pass it along to any neighbor that is closer in the hyperbolic metric to the message's eventual destination. More importantly, for networking applications, our algorithm produces succinct drawings, in that each of the vertex positions in one of our embeddings can be represented using O(log n) bits and the calculation of which neighbor to send a message to may be performed efficiently using these representations. These properties are useful, for example, for routing in sensor networks, where storage and bandwidth are limited.

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Section: Prior Related Workmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Succinct Greedy Graph Drawing in the Hyperbolic Plane

Eppstein

Goodrich

2009

Graph Drawing

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“…GPSR [12] by Karp and Kung use perimeter forwarding to get around voids. Similarly, GOAFR [14] combines the greedy routing with the adaptive face routing to provide an asymptotically optimal path to the destination. Geographic distance routing (GEDIR) [20] guarantees loop-free delivery in a collision-free network.…”

Section: State-of-the-artmentioning

confidence: 99%

“…The key difference is that SPEED takes timely delivery into account and is designed to be the first spatiotemporal-aware communication protocol for sensor networks. Moreover, SPEED provides an alternative solution to handle voids other than approaches based on planar graph traversal [12], [14] and limited flooding [5].…”

Section: State-of-the-artmentioning

confidence: 99%

A spatiotemporal communication protocol for wireless sensor networks

Stankovic

Abdelzaher

et al. 2005

IEEE Trans. Parallel Distrib. Syst.

219

197

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Abstract-In this paper, we present a spatiotemporal communication protocol for sensor networks, called SPEED. SPEED is specifically tailored to be a localized algorithm with minimal control overhead. End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and nondeterministic geographic forwarding. SPEED is a highly efficient and scalable protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments, and a real implementation on Berkeley motes are provided to validate the claims.

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“…In the initial stage, these strategies use greedy. When a node has no neighbor closer to the destination, greedy is replaced by one of existing planar graph traversal algorithms [12], [22], [14], [13], [18]. Since the representation of the network is not always a planar graph, this class of strategies uses a distributed planarization algorithm, like those proposed in [21], [7], [11].…”

Section: State Of the Art And Comparisonmentioning

confidence: 99%

Geographic Routing with Early Obstacles Detection and Avoidance in Dense Wireless Sensor Networks

Moraru

Leone

Nikoletseas

et al. 2008

Lecture Notes in Computer Science

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Abstract. Existing geographic routing algorithms for sensor networks are mainly concerned with finding a path toward a destination, without explicitly addressing the impact of obstacles on the routing performance. When the size of the communication voids is increased, they might not scale well with respect to the quality of paths, measured in terms of hop count and path length. This paper introduces a routing algorithm with early obstacle detection and avoidance. The routing decisions are based on path optimality evaluation, made at the node level, gradually over time. We implement our algorithm and evaluate different aspects: message delivery performance, topology control overhead and algorithm convergence time. The simulation findings demonstrate that our algorithm manages to improve significantly and quite fast the path quality while keeping the computational complexity and message overhead low. The algorithm is fully distributed, and uses only limited local network knowledge.

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Worst-Case optimal and average-case efficient geometric ad-hoc routing

Cited by 413 publications

References 26 publications

Succinct Greedy Graph Drawing in the Hyperbolic Plane

Succinct Greedy Graph Drawing in the Hyperbolic Plane

A spatiotemporal communication protocol for wireless sensor networks

Geographic Routing with Early Obstacles Detection and Avoidance in Dense Wireless Sensor Networks

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