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Andreas Savvides andreas.savvides@yale Office: AKW 212 Tel 432-1275 Course Website

Routing Considerations for Sensor Networks Lecture 12 October 12, 2004 EENG 460a / CPSC 436 / ENAS 960 Networked Embedded Systems & Sensor Networks. Andreas Savvides andreas.savvides@yale.edu Office: AKW 212 Tel 432-1275 Course Website http://www.eng.yale.edu/enalab/courses/eeng460a.

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Andreas Savvides andreas.savvides@yale Office: AKW 212 Tel 432-1275 Course Website

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  1. Routing Considerations for Sensor NetworksLecture 12 October 12, 2004EENG 460a / CPSC 436 / ENAS 960 Networked Embedded Systems &Sensor Networks Andreas Savvides andreas.savvides@yale.edu Office: AKW 212 Tel 432-1275 Course Website http://www.eng.yale.edu/enalab/courses/eeng460a

  2. Announcements • Feng Zhao’s talk tomorrow 4:00pm @ AKW 500 • Student session 3:20 – 4:00pm AKW 500 • Reading for this lecture • Zhao & Guibas Section 3.3 through 3.6 • Reading for next lecture • Directed Diffusion – paper posted on the class website • Today’s presentation IDSQ

  3. Routing Considerations in Sensor Networks • Traditional TCP/IP routing not attractive for sensor networks • Too much overhead and large routing tables • Sensor networks are more ad-hoc • Each node acts as a router • Still different than ad-hoc networks • Proactive routing is too expensive • Some possibility for reactive routing such as • Fish-eye routing, AODV, DSR

  4. Routing Goal • Focus on localized state-less routing • Consider only local neighborhood • Classical separation of address and content does not hold • Care about reaching the nodes rather than a particular address – what can be sensed by a node can most probably be sensed by neighboring nodes • Interested in routing by attributes – data centric • Node’s location • Node’s type of sensors • Range of values in the sensed data • Notion of optimality can vary • QoS routing – latency is important => shortest path • Energy aware routing – longer paths are ok => avoid nodes with less energy

  5. Geographic Routing • Aims to route based on very limited state information • Geographic routing protocols assume • All nodes know their geographic location • Each node knows its 1-hop neighbors • Destination is a node with a given location • Each packet can hold a limited amount of information as to where it has been in the network • Any issues with this? • Needs to maintain information between node IDs and node location (referred to as location service)

  6. Geographic Forwarding Approaches • Greedy distance routing: select the neighbor geographically closest to the destination and forward the data to that neighbor • Compass routing: pick the next node as the one that minimizes the angle to destination • What are the problems with the basic approaches • Greedy distance routing – may get stuck in local minima • Compass routing – may go in loops

  7. Planarization of Routing Graph • To get protocols that guarantee data delivery, make graph planar • Remove some edges from your network graph G • Aim: Keep the same connectivity but make the graph planar • no two edges in G should intersect each other • In the planar subdivision of G each node is assumed to know the circular order of its neighbors • Convex perimeter routing and other face routing protocols use this property

  8. Common Planarization Methods y x y x • Relative Neighborhood Graph (RNG) • The edge xy is introduced if the intersection of circles centered at x and y with radius the distance d(x,y) is free of other nodes • Grabriel Graph • The edge xy is introduced if the diameter xy is free of other nodes • Both graphs RNG and Gabriel graphs can be found with distributed construction

  9. Greedy Perimeter Stateless Routing(GPSR) • Geographic protocol based on the offline construction of planar graphs • RDG, Gabriel, later on RDG suggested • Has 2 main phases forwarding and recovery • Forwarding is greedy • Recovery – uses a right-hand rule to recover from holes. It stops as soon as a node closer to the destination is found

  10. Routing on a Curve • Specify a curve a packet should follow • Analytical description of a curve carried by the packet • Curves may correspond to natural features of the environment where the network is deployed • Can be implemented in a local greedy fashion that requires no global knowledge • Curve specified in parametric form C(t)=(x(t),y(t)) • t – time parameter – could be just relative time • Each node makes use of nodes trajectory information and neighbor positions to decide the next hop for the packet.

  11. Attribute Based Routing & Directed Diffusion • Nodes desire certain information and other nodes have some information. How do they find each other? • Use attribute value pairs to describe the data Attribute value record Information request record type = animal type = animal instance = horse instance = horse location = [89, 154] rect = [0,200,0,200] time = 2:45:23

  12. Directed Diffusion • Each node names data with one or more attributes • Other nodes express interests based on these attributes • Network nodes propagate the interests and results back to the sink • Negative gradients inhibit the propagation of information & positive gradients encourage information propagation • Assumption: the sink will be interested in repeated measurements from a source for a period of time • Paa-Kwesi will give a detailed presentation of directed diffusion next time

  13. Next Lecture • Geographic Hash Tables – Andreas • Directed Diffusion – Paa Kwesi

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