GPSR: Greedy Perimeter Stateless Routing for Wireless Networks B. Karp, H. T.
Download
Report
Transcript GPSR: Greedy Perimeter Stateless Routing for Wireless Networks B. Karp, H. T.
GPSR: Greedy Perimeter Stateless
Routing for Wireless Networks
B. Karp, H. T. Kung
Borrowed some slides from Richard Yang’s
1
Motivation
A sensor net consists of hundreds or thousands of
nodes
Scalability is the issue
Existing ad hoc net protocols, e.g., DSR, AODV, ZRP,
require nodes to cache e2e route information
Dynamic topology changes
Mobility
Reduce caching overhead
Hierarchical routing is usually based on well defined, rarely
changing administrative boundaries
Geographic routing
• Use location for routing
2
Scalability metrics
Routing protocol msg cost
How many control packets sent?
Per node state
How much storage per node is required?
E2E packet delivery success rate
3
Assumptions
Every node knows its location
Positioning devices like GPS
Localization
A source can get the location of the
destination
802.11 MAC
Link bidirectionality
4
Geographic Routing: Greedy Routing
Closest
to D
S
A
D
- Find neighbors who are the closer to the destination
- Forward the packet to the neighbor closest to the destination
5
Benefits of GF
A node only needs to remember the location
info of one-hop neighbors
Routing decisions can be dynamically made
6
Greedy Forwarding does NOT always work
GF fails
If the network is dense enough that each
interior node has a neighbor in every 2/3
angular sector, GF will always succeed
7
Dealing with Void: Right-Hand Rule
Apply the right-hand rule to traverse the
edges of a void
Pick the next anticlockwise edge
Traditionally used to get out of a maze
8
Right Hand Rule on Convex Subdivision
For convex subdivision, right hand rule is equivalent to
traversing the face with the crossing edges removed.
9
Right-Hand Rule Does Not Work with
Cross Edges
z
u
D
w
x originates a packet to u
Right-hand rule results in the
tour x-u-z-w-u-x
x
10
Remove Crossing Edge
z
u
D
Make
w
the graph planar
Remove
x
(w,z) from the graph
Right-hand rule results in the
tour x-u-z-v-x
11
Make a Graph Planar
Convert a connectivity graph to planar non-
crossing graph by removing “bad” edges
Ensure the original graph will not be
disconnected
Two types of planar graphs:
•
•
Relative Neighborhood Graph (RNG)
Gabriel Graph (GG)
12
Relative Neighborhood Graph
uv can exist if
w u, v, d(u,v) < max[d(u,w),d(v,w)]
Connection
not empty
remove uv
13
Gabriel Graph
An edge (u,v) exists between vertices
u and v if no other vertex
w is present within the circle whose diameter is uv.
w u, v, d2(u,v) < [d2(u,w) + d2(v,w)]
Not empty
remove uv
14
Properties of GG and RNG
RNG is a sub-graph of
RNG
GG
Because RNG removes more
edges
GG
If the original graph is
connected, RNG is also
connected
15
Connectedness of RNG Graph
Key observation
Any edge on the minimum
spanning tree of the original
graph is not removed
Proof by contradiction: Assume
(u,v) is such an edge but removed in RNG
w
u
v
16
Examples
Full graph
GG subset
RNG subset
• 200 nodes
• randomly placed on a 2000 x 2000 meter region
• radio range of 250 m
•Bonus: remove redundant, competing path less collision
17
Greedy Perimeter Stateless Routing (GPSR)
Maintenance
all nodes maintain a single-hop neighbor table
Use RNG or GG to make the graph planar
At source:
mode = greedy
Intermediate node:
if (mode == greedy) {
greedy forwarding;
if (fail) mode = perimeter;
}
if (mode == perimeter) {
if (have left local maxima) mode = greedy;
else (right-hand rule);
}
18
GPSR
greedy fails
Greedy Forwarding
Perimeter Forwarding
have left local maxima
greedy works
greedy fails
19
Implementation Issues
Graph planarization
RNG & GG planarization depend on having the
current location info of a node’s neighbors
Mobility may cause problems
Re-planarize when a node enters or leaves the
radio range
• What if a node only moves in the radio range?
• To avoid this problem, the graph should be re-planarize
for every beacon msg
Also, assumes a circular radio transmission model
In general, it could be harder & more expensive
than it sounds
20
Performance evaluation
Simulation in ns-2
Baseline: DSR (Dynamic Source Routing
Random waypoint model
A node chooses a destination uniformly at random
Choose velocity uniformly at random in the
configurable range – simulated max velocity
20m/s
A node pauses after arriving at a waypoint – 300,
600 & 900 pause times
21
50, 112 & 200 nodes
22 sending nodes & 30 flows
About 20 neighbors for each node – very dense
CBR (2Kbps)
Nominal radio range: 250m (802.11 WaveLan
radio)
Each simulation takes 900 seconds
Take an average of the six different
randomly generated motion patterns
22
Packet Delivery Success Rate
23
Routing Protocol Overhead
24
Related Work
Geographic and Energy Aware Routing
(GEAR), UCLA Tech Report, 2000
Consider remaining energy in addition to
geographic location to avoid quickly draining
energy of the node closest to the destination
Geographic probabilistic routing,
International workshop on wireless ad-hoc
networks, 2005
Determine the packet forwarding probability to
each neighbor based on its location, residual
energy, and link reliability
25
Beacon vector routing, NSDI 2005
Beacons know their locations
Forward a packet towards the beacon
A Scalable Location Service for Geographic Ad Hoc
Routing, MobiCom ’00
Distributed location service
Landmark routing
Paul F. Tsuchiya. Landmark routing: Architecture,
algorithms and issues. Technical Report MTR-87W00174,
MITRE Corporation, September 1987.
Classic work with many follow-ups
26
Questions?
27