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An Information Model for Geographic Greedy Forwarding in Wireless Ad-Hoc Sensor Networks

An Information Model for Geographic Greedy Forwarding in Wireless Ad-Hoc Sensor Networks. Junchao Ma, Wei Lou Dept. of Computing The HK Polytechnic University. Zhen Jiang Comp. Sci. Dept. West Chester University. Jie Wu Dept. of Computer Sci. & Eng. Florida Atlantic University & NSF.

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An Information Model for Geographic Greedy Forwarding in Wireless Ad-Hoc Sensor Networks

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  1. An Information Model for Geographic Greedy Forwarding in Wireless Ad-Hoc Sensor Networks Junchao Ma, Wei Lou Dept. of Computing The HK Polytechnic University Zhen Jiang Comp. Sci. Dept. West Chester University Jie Wu Dept. of Computer Sci. & Eng. Florida Atlantic University & NSF INFOCOM'08

  2. Outline • Introduction • Our Approaches • Experimental Results • Conclusion • Future Work INFOCOM'08

  3. Goal • An efficient path in wireless ad-hoc sensor networks (WASNs) • Fewer hops and detours • Faster data delivery • More energy conserved destination source INFOCOM'08

  4. Problem • Local minimum phenomenon (void) • Sparse deployment • Physical obstacles • Node failures • Communication jamming • Power exhaustion • Animus interference block void stuck node destination source INFOCOM'08

  5. Idea • Information helps routing to • Predict the ‘void’ ahead • Make a slightturn early to sufficiently avoid being blocked • Non-detour routing, i.e., greedy forwarding without perimeter routing • Make a turn only if necessary • To keep the optimality of a straight forwarding INFOCOM'08

  6. Challenge 1 • Identification of the affected area of a void • Relative to the positions of the source and the destination destination destination source destination source source destination affected area affected area Case 1 Case 2 INFOCOM'08

  7. Challenge 2 • Mutual impact of void areas • Global optimization achieved by neighborhood optimizations • No routing table, flooding, or broadcasting • Routing decision at each intermediate node • Neighbor information collection and distribution destination area of mutual impact source INFOCOM'08

  8. Challenge 3 • Unstructured WASNs • Hard to ensure whether the forwarding still achievable ahead destination ? source INFOCOM'08

  9. Illustration What kind of information and how to conduct a forecast? No global information New York (destination) Information exchanged with next light traffic prediction West Chester (source) light control related to travel destination INFOCOM'08

  10. Related Work • “Dead end” model • No optimization • Boundary model • No global optimization • Hull algorithm, or turning angle model • No consideration of the relative positions INFOCOM'08

  11. Our Approaches • Tradeoff between routing adaptivity and structure regularity • Safety information for such a forwarding • Information based forwarding (SLGF routing) INFOCOM'08

  12. Tradeoff • A forwarding with infrastructure in WASNs • LAR2: • Forwarding to a neighbor that is closer to the destination • We adopt LAR1 • Forwarding limited in the so-called request zone destination destination forwarding candidate LAR 1 LAR 2 request zone current node current node INFOCOM'08

  13. Safety Information • Inspired by the safety model in 2-D mesh networks • An unsafe area contains nodes that definitely causing routing detour. • Constructed by a labeling process via information exchanges among neighbors. INFOCOM'08

  14. Details of the Labeling Process • Unsafe node • A node without any neighbor in the request zone • A node without any safe neighbor in the request zone • Unsafe area • Connected unsafe nodes • Estimated as a rectangle at an unsafe node. • 4 Different types of unsafe status • Due to 4 different types of request zones INFOCOM'08

  15. An Example of Type-I Safety Information INFOCOM'08

  16. SLGF Routing • Four phases conducted in the order • Enforced forwarding • Safe forwarding • Perimeter routing (for making a slight turn) • Retreating (in the opposite direction) INFOCOM'08

  17. Simulation • To verify whether LAR1(-) + Safety Info. (-) + Info. based routing (+) is better than boundary info. based routing. • Forwarding routings • GF (LAR2 + boundary information) • LGF (LAR1) • SLGF (LAR1 + safety information) INFOCOM'08

  18. INFOCOM'08

  19. Result Summary • Cost safety information < boundary information • Routing success GF = LGF = SLGF • Routing path LGF < GF << SLGF INFOCOM'08

  20. Conclusion • Unicast routing but neighborcast information construction • Tradeoff between routing adaptivity and information model cost • Mutual impact of void areas • Better forwarding routing to achieve more straight paths INFOCOM'08

  21. Future Work • New balance point of the tradeoff between routing adaptivity and information model cost • More accurate information • Better forwarding routing to achieve more straight path INFOCOM'08

  22. Questions? Thank you! INFOCOM'08

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