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Distributed Roadmap Aided Routing in Sensor Networks

Distributed Roadmap Aided Routing in Sensor Networks. Speaker: Zizhan Zheng Authors: Zizhan Zheng , Kai-Wei Fan, Prasun Sinha , and Yusu Wang Department of Computer Science & Engineering The Ohio State University. Routing in Sensor Networks. Pairwise communication

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Distributed Roadmap Aided Routing in Sensor Networks

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  1. Distributed Roadmap Aided Routing in Sensor Networks Speaker: ZizhanZheng Authors: ZizhanZheng, Kai-Wei Fan, PrasunSinha, and Yusu Wang Department of Computer Science & Engineering The Ohio State University

  2. Routing in Sensor Networks • Pairwise communication • Pursuer-evader tracking • Battle field monitoring • In-network storage • Goals • Guaranteed packet delivery • Low route stretch • Route stretch: the ratio of the number of hops on the computed route to the number of hops on the shortest route • Low message and storage overhead • Protocols • Geographic routing (GPSR, GSR, GFG, …) • Virtual coordinate based routing (GLDR, ABVCap, …)

  3. Geographic Routing • Performs well in dense deployment • Low overhead • Low stretch • Guarantees delivery • Has large worst case route stretch in the presence of big routing holes • Bypasses hole late and (probably) in the wrong direction • Solution: make the presence of holes known t 26 : 66 s GPSR (red) vs. HBR (blue)

  4. Hole Bypassing Routing (HBR) • Main ideas: • View holes as obstacles • Advertise holes to the network • Setup a shortest path roadmap on each node for route planning • Challenges: • Advertising all the holes to the entire network has high message overhead • Storing a complete roadmap on each node has high storage overhead. • Solutions: hole approximation and controlled advertisement

  5. HBR - Overview • Step 1 – Hole Discovery • Using the technique proposed in [Qing Fang et al. Infocom 2004] • Hole coordinator maintains the hole boundary • Step 2 – Hole Approximation • Approximate each hole by a core – a simpler representative polygon contained within • Done at coordinators • Step 3 – Hole Advertisement • Each coordinator advertises the core to the network • Each node sets up a shortest path roadmap locally using the cores received • Step 4 – Routing • Roadmap based route planning • Greedy forwarding + hole bypassing t v4 v3 y s x <  v0 v1 v2

  6. Hole Approximation • Alpha - approximation • Observation: The size of the core of a convex hole is bounded by v6 v6 v7 v7 v6 v7 v5 v5 v5 v8 v8 v8 v4 v4 v9 v4 w10,1 v3 v9 v9 v0 v0 v12 v12 v2 v3 v1 v3 v10 v1 v11 v11 04 > /3 v1 v0 03 < /3 v10 v10 v2 v2  = /3

  7. Bounded Worst Case Route Stretch • Theorem: If all the routing cores are advertised to the entire network, route stretch is bounded by • Controlled advertisement • The core of hole H is advertised within a circle with the same center as the minimum bounding circle of H and radius R =  pH , a constant factor of the perimeter of H • More work needed

  8. Simulation Settings • Network • 1000 x 1000m2 • 2000 sensor nodes • average node degree: 15 • several big holes • Routing protocols • GPSR (Mobicom 2000) • GLDR (Infocom 2007) • 25 landmarks on average • HBR •  = /2 • big holes are fully advertised

  9. Simulation – Average Stretch • HBR bounds route stretch by • GLDR has relatively stable route stretch Rectangular holes Elliptic holes

  10. Simulation – Transmission Overhead • Y-axis: normalized number of transmissions in routing a packet • The transmission overhead of GLDR is high Rectangular holes Elliptic holes

  11. Conclusion • HBR, a distributed roadmap aided routing protocol is presented • HBR bounds worst case route stretch • HBR can make tradeoff between route stretch and control overhead

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