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Self-Organizing Hierarchical Routing for Scalable Ad Hoc Networking
David B. Johnson
Department of Computer ScienceRice University
Monarch Project
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Introduction
Safari project goals:• Self-organizing, adaptive network hierarchy• Scalable ad hoc network routing (10s of thousands of nodes)• Self-organizing higher layer network services and applications• Integrated with Internet infrastructure where it exists
Safari leverages and tightly integrates two areas of research:• Ad hoc networking• Peer-to-peer networking
Builds an adaptive, proximity-based hierarchy of cells andleverages this for scalable routing and higher layer services
Funded by NSF Special Projects in Networking Research(January 2004)
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Hierarchy Self-Organization
All nodes are equivalent – no specialized nodes assumed:
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Hierarchy Self-Organization
Nodes self-elect to become a buoy:
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Hierarchy Self-Organization
Buoy nodes send limited propagation beacon floods:
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Hierarchy Self-Organization
Other nodes associate with a buoy to form cells:
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Hierarchy Self-Organization
Buoys at one level self-elect to become buoy at next higher level:
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Hierarchy Self-Organization
Forming cells at each higher level too:
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Simulation Example
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Coordinates
A node’s coordinates = associated cell id at each hierarchy level
a
dc
b
eA
CB
A.bA.a
A.c
A.d A.e
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Safari Routing Overview
Destination node coordinates:• Stored and looked up in Distributed Hash Table (DHT) using
embedded peer-to-peer system
Hybrid routing protocol components:• Route to destination cell following beacons (proactive routing)• Incremental local repair in this path (reactive routing)• Route to destination node within final cell (reactive routing)
Routing table at a node:• Remembers information from beacons received:
– Coordinates of buoy sending beacon– Previous hop node from which beacon received– Hop count back to the buoy– Sequence number of most recent beacon from that buoy
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Proactive Inter-cell Routing
Range of beacons from a buoy node:• Nodes in the cell associated with that buoy• Nodes a few hops away, giving them a chance to join that cell• Nodes in the containing cell one level up in the hierarchy
Routing table lookup algorithm:• Nodes outside the cell hear the beacons:
– Reasons described above– Wireless propagation allows nearby nodes to hear too
• Longest common prefix matching (similar to Internet !) :– Compare your own coordinates to each entry in routing table– As soon as packet comes to node with more detailed table
entry, packet starts following lower in routing hierarchy
Packets are routed toward buoys, not through buoys!
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Routing Example
Source node S is sending a packet to destination node D:
S
D
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Routing Example
Follow beacon path toward level 3 cell in which D is located:
S
D
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Routing Example
Follow beacon path toward level 2 cell in which D is located:
S
D
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Routing Example
Follow beacon path toward level 1 cell in which D is located:
S
D
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Reactive Intra-cell Routing
Dynamic Source Routing protocol (DSR):• Discovers routes only as needed, on demand (Route Discovery)• Detects when links being used for routing are broken, on demand
only as they are used (Route Maintenance)• Very low overhead, scalable to mobility and traffic needs• Zero overhead until new route is needed
Using DSR in Safari routing:• DSR originally designed for small or medium sized networks• Safari intended to scale to much larger sizes• Safari uses DSR only within destination fundamental cell• Size of fundamental cells created by Safari balance two things:
– Small enough for very easy efficient reactive routing– Large enough to minimize when nodes move to new cells
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Routing Example
On-demand DSR routing to destination node D:
S
D
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Reactive Inter-cell Route Repair
Beacons are sent only periodically:• Long interval between beacons important for low overhead• The higher the level in hierarchy, the less frequent the beacon• Following beacon reverse path may fail if nodes have moved
Safari local route repair in thebeacon paths:• Limited-hop on-demand
Route Discovery• Flood flows “downhill” with
limited “uphill” allowed• “Altitude” is prefix length
matched, sequence #, hop count • Result reestablishes new path
as if original beacon path Buoy node
Increasing “altitude”with hops away
from buoy
A node hasmoved awayfrom buoy
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Simulation Evaluation
• Simulated using ns-2, includes detailed physical model
• IEEE 802.11 at 2 Mbps, nominal range 250 m
• Studied scale from 50 to 1000 nodes:
– Randomly distributed in space
– Density maintained equivalent to 50 nodes in 10001000 m
• Studied percentage of nodes being mobile from 0% to 100%
– Moving with Random Waypoint model, average 5 m/s
• Data traffic is Constant Bit Rate (CBR):
– Flows with randomly chosen source and destination
– 4 packets/second, 64 bytes/packet
• Metrics shown:
– Packet Delivery Ratio: percentage of packets delivered
– Overhead: individual transmissions of routing packets
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
PDR vs. Number of Nodes
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
PDR vs. Percentage of Mobile Nodes
(1000 nodes total)
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Overhead vs. Number of Nodes
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Overhead vs. Percentage of Mobile Nodes
(1000 nodes total)
Mo bile N etworking Arch itecturesDavid B. Johnson Rice University Monarch ProjectSafari
Conclusion
Safari is highly scalable and provides a basis for services:
• Forms an adaptive, proximity-based hierarchy of cells
• PDR and routing overhead change little with scale or mobility
• Performance studied through both simulation and analysis
Ongoing and future work:
• Further optimization and evaluation of beaconing, cell membership, routing, local repair
• Interconnection to traditional Internet infrastructure
• Higher layer services exploiting the hierarchy and P2P
• Testbed and experimentation