Visibility-Graph-Based Shortest-Path Geographic Routing in Sensor Networks

Abstract

We study the problem of shortest-path geographic routing in a static sensor network. Existing algorithms often make routing decisions based on node information in local neighborhoods. However, it is shown by Kuhn et al. that such a design constraint results in a highly undesirable lower bound for routing performance: if a best route has length c, then in the worst case a route produced by any localized algorithm has length Ω(c 2 ), which can be arbitrarily worse than the optimal. We present VIGOR, a VIsibility-Graph-based rOuting pRotocol that produces routes of length Θ(c). Our design is based on the construction of a much reduced visibility graph, which guides nodes to find near-optimal paths. The per-node protocol overheads in terms of state information and message transmission depend only on the complexity of the field's large topological features, rather than on the network size. Simulation results show that our protocol dramatically outperforms localized protocols such as GPSR and GOAFR+ in both average and worst cases, with reasonable extra overheads.

GOAL: A parsimonious geographic routing protocol for large scale sensor networks

“…al. [8] introduced VIGOR, a geographic routing protocol that guarantees a constant path stretch. VIGOR finds a near optimal routing path by exploiting the visibility graph.…”

“…We adopt the boundary node detection scheme used in VIGOR [8] for implementing the first phase of this process. This boundary node detection scheme, when it is done, allows each boundary node to have the notion of a left and right neighboring boundary node.…”

“…By [8], the shortest path between s and t in the Visibility Graph is bounded by some constant factor of Euclidean distance between s and t as the following:…”

“…al. [8] proposed VIGOR, a geographic protocol that achieves a constant path stretch. In VIGOR, a hole is represented as a polygon, which is used to build a visibility graph, a structure often used in computational geometry to find the shortest path between a source and a destination, given obstacles of polygonal shapes.…”

Deterministic Greedy Routing with Guaranteed Delivery in 3D Wireless Sensor Networks

“…For example, face routing and its alternatives and enhancements [13][14][15][16][17][18][19][20] exploit the fact that a concave void in a 2D planar network is a face with a simple line boundary. Thus, when a packet reaches a local minimum on a boundary, it employs a local deterministic algorithm to search the boundary in either the clockwise or counter-clockwise direction, as shown in Figure 2a, until greedy forwarding is achievable.…”