Download QoS Guarantee in Wirless Network

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

RapidIO wikipedia , lookup

Peering wikipedia , lookup

Multiprotocol Label Switching wikipedia , lookup

Cracking of wireless networks wikipedia , lookup

Computer network wikipedia , lookup

Backpressure routing wikipedia , lookup

List of wireless community networks by region wikipedia , lookup

CAN bus wikipedia , lookup

IEEE 802.1aq wikipedia , lookup

Airborne Networking wikipedia , lookup

IEEE 1355 wikipedia , lookup

Recursive InterNetwork Architecture (RINA) wikipedia , lookup

Routing wikipedia , lookup

Routing in delay-tolerant networking wikipedia , lookup

Transcript
Wireless, Mobile, Ad-Hoc Network Routing
Mario Gerla, UCLA CSD
FOCUS 99
Outline:
– What is an Ad-Hoc Wireless Network
– The wireless routing challenge
– Review of proposed solutions (Distance Vector, Link State, OnDemand, Location Based)
– Simulation test bed
– Performance results
Cellular vs Multihop
Standard Base-Station Cellular Networks
Instant Infrastructure, Multihop wireless Networks
Ad-Hoc Network Characteristics
• Instantly deployable, reconfigurable
infrastructure
• Node mobility
• Heterogeneous nodes (big/small; fast/slow etc)
• Heterogeneous traffic (voice, image, video, data)
• Limited battery power
• Multihopping ( to save power, overcome
obstacles, enhance spatial spectrum reuse, etc.)
Ad-Hoc Network Applications
• Disaster Recovery (flood, fire, earthquakes etc)
• Law enforcement (crowd control, border patrol
etc)
• Search and rescue in remote areas
• Sport events, festivals
• Ad hoc nomadic, collaborative computing
• Indoor network appliances
• Sensor networks
• Battlefield
Wireless multihop routing challenges
•
•
•
•
•
•
mobility
need to scale to large numbers (1000's)
unreliable radio channel (fading etc)
limited bandwidth
limited power
need to support multimedia (QoS)
Proposed Routing Approaches
• Conventional wired-type schemes (global routing,
proactive):
– Distance Vector; Link State
• Hierarchical (global routing) schemes:
– Fisheye, Hierarchical State Routing
• On - Demand, reactive routing:
– Source routing; backward learning
• Location Assisted routing (Geo-routing):
– DREAM, LAR etc
Conventional wired routing limitations
• Distance Vector (eg, Bellman-Ford):
– routing control O/H linarly increasing with net size
– convergence problems (count to infinity); potential loops
• Link State (eg, OSPF):
– link update flooding O/H caused by frequent topology changes
CONVENTIONAL ROUTING DOES NOT SCALE TO SIZE AND MOBILITY
Distance Vector
0
Routing table at node 5 :
1
Destination Next Hop Distance
0
1
…
2
2
…
3
2
…
3
2
4
5
Link State Routing
• At node 5, based on the
link state packet, topology
table is constructed:
0
1
2
3
4
5
0
1
1
0
0
0
0
1
1
1
1
1
0
0
2
0
1
1
0
1
1
3
0
1
0
1
1
0
4
0
0
1
1
1
1
5
0
0
1
0
1
1
0
{0,2,3}
{1}
1
3
{1,4,5}
2
4
• Dijkstra’s Algorithm can
then be used for the
shortest path
{1,4}
{2,4}
5
{2,3,5}
REMEDY #1: use hierarchical routing to reduce
table size and table update overhead
Proposed hierarchical schemes:
– Fisheye (implicit hierarchy induced by "scope")
– Hierarchical State Routing
– Zone routing (hybrid scheme)
Fisheye State Routing
• Topology based routing
– similar to link state (e.g., OSPF)
• Routing information is periodically exchanged
with neighbors only
– similar to distance vector
• Routing update frequency decreases with
distance to destination
– Higher frequency updates within a close zone and lower frequency
updates to a remote zone
– Highly accurate routing information about the immediate
neighborhood of a node; progressively less detail for areas further
away from the node
Scope of Fisheye
2
8
5
3
1
9
9
4
6
Hop=1
7
13
10
12
11
36
14
21
Hop>2
15
16
17
22
23
20
29
27
25
24
Hop=2
19
18
26
30
35
28
34
32
31
Message Reduction in FSR
LST
0:{1}
1:{0,2,3}
2:{5,1,4}
3:{1,4}
4:{5,2,3}
5:{2,4}
HOP
1
0
1
1
2
2
0
1
3
2
4
5
LST
0:{1}
1:{0,2,3}
2:{5,1,4}
3:{1,4}
4:{5,2,3}
5:{2,4}
LST
0:{1}
1:{0,2,3}
2:{5,1,4}
3:{1,4}
4:{5,2,3}
5:{2,4}
HOP
2
1
2
0
1
2
HOP
2
2
1
1
0
1
Hierarchical State Routing (HSR)
• Main challenge: maintain/update the hierarchical
partitions in the face of mobility
• Solution: distinguish between “physical”
partitions and “logical” grouping
– physical partitions are based on geographical proximity
– logical grouping is based on functional affinity between nodes (e.g.,
tanks of same battalion, students of same class)
• Physical partitions enable reduction of routing
overhead
• Logical groupings enable efficient location
management strategies using Home Agent
concepts
HSR - physical multilevel partitions
3
1
Level = 2
HSR table at node 5:
DestID Path
2
3
1
Level = 1
4
2
6
3
1
Level = 0
(MAC addresses)
8
5
11
7
4
9
10
1
5-1
6
5-1-6
7
5-7
<1-2->
5-1-6
<1-4->
5-7
<3-->
5-7
Hierarchical
addresses
HID(5): <1-1-5>
HID(6): <3-2-6>
HSR - logical partitions and location
management
• Logical (IP like) type address <subnet,host>
– Each subnet corresponds to a particular user group (e.g., tank
battalion in the battlefield, search team in a search and rescue
operation, etc)
– logical subnet spans several physical clusters
– Nodes in same subnet tend to have common mobility characteristic
(i.e., locality)
– logical address is totally distinct from MAC address
HSR - logical partitions and location
management (cont’d)
• Each subnetwork has at least one Home Agent to
manage membership
• Each member of the subnet registers its own
hierarchical address with Home Agent
– periodically/event driven registration; stale addresses are timed out
by Home Agent
• Home Agent hierarchical addresses propagated
via routing tables; or queried at a Name Server
On-Demand Routing Protocols
• Routes are established “on demand” as
requested by the source
• Only the active routes are maintained by each
node
• Channel/Memory overhead is minimized
• Two leading methods for route discovery: source
routing and backward learning (similar to LAN
interconnection routing)
Existing On-Demand Protocols
•
•
•
•
•
•
Dynamic Source Routing (DSR)
Associativity-Based Routing (ABR)
Ad-hoc On-demand Distance Vector (AODV)
Temporarily Ordered Routing Algorithm (TORA)
Zone Routing Protocol (ZRP)
Signal Stability Based Adaptive Routing (SSA)
Dynamic Source Routing (DSR)
• Uses source routing instead of hop-by-hop routing
• No periodic routing update message is sent
• Nodes ignore topology changes not affecting active routes
with packets in the pipe
• The first path discovered is selected as the route
• Two main phases
– Route Discovery
– Route Maintenance
DSR - Route Discovery
• To establish a route, the source floods a Route Request
message with a unique request ID
• Route Reply message containing path information is sent
back to the source either by
– the destination, or
– intermediate nodes that have a route to the destination
• Each node maintains a Route Cache which records routes it
has learned and overheard over time
Performance Evaluation Enviroment
• PARSEC simulation enviroment
–
–
–
–
–
–
–
100 nodes
1000mx1000m square area
transmission range: 100m
channel data rate: 2 Mbps
random mobility model
UDP traffic between randomly selected node pairs
cluster-token MAC layer protocol
• HSR
– 2 level physical partition
– 1 level logical groupings, number of logical subnets varies with
network size
• FSR
– 2 level fisheye scoping
– fisheye radius is 2 hops
DSR - Route Maintenance
• Route maintenance performed only while route is in use
• Monitors the validity of existing routes by passively
listening to acknowledgments of data packets transmitted
to neighboring nodes
• When problem detected, send Route Error packet to
original sender to perform new route discovery
Location-Aided Routing
•
•
•
•
•
Ko and Vaidya (Texas A & M)
Location assisted (requires GPS)
On-demand
No periodic messages
Works similar to DSR except LAR limits the
flooded area of Route Requests using location
information
LAR (cont’d)
• Scheme 1
– The source specifies a request zone which includes the source and the area
where the destination may reside
– Nodes within the request zone propagate Route Requests
• Scheme 2
– The source specifies the distance between itself and the destination
– Nodes forward Route Requests if their distances to the destination is less
than or equal to the distance indicated by the packet
DREAM
• Basagni, et al. (U of Texas, Dallas)
• Location assisted (requires GPS)
• Coordinates of each node are recorded in the
route table instead of route vectors
• Distance Effect: Send location updates to nearby
nodes more frequently
• Location update frequencies are adjusted to
mobility rate
DREAM (cont’d)
• The source partially floods data to nodes that are in the
direction of the destination
• The source specifies possible next hops in the data header
using location information
• Next hop nodes select their own list of next hops and
include the list into data header
• If the source finds no neighbors in the direction of the
destination or has no fresh location information of the
destination, data is flooded to the entire network
GloMoSim Simulation Layers
Application
Data Plane
Control Plane
Application Processing
Application Setup
RTP Wrapper
Transport
IP
Network
Link Layer
MAC Layer
Radio
Channel
Transport Wrapper
IP Wrapper
Packet Store/Forward
Packet Store/Forward
Frame Wrapper
Frame Processing
Propagation Model
RCTP
TCP/UDP Control
RSVP
IP/Mobile IP
VC
Handle
Routing
Flow
Control
Routing
Clustering
Ack/Flow Control
RTS/CTS
CS/Radio Setup
Radio Status/Setup
Mobility
Clustering
Control O/H (Mbits/Cluster)
Control O/H vs. number of nodes
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
25
49
100
225
324
400
Number of nodes
On-demand
DSDV
HSR
FSR
Control O/H vs. Traffic Pairs
Control O/H vs. Mobility (100 pairs)
Average Delay (ms)
Location Based Routing Simulation
(LAR and DREAM)
•
•
•
•
•
50 nodes; 750m X 750 m space
Free space channel propagation model
Radio with capture ability
MAC: IEEE 802.11 DCF
10 UDP data sessions with constant bit rate
Simulation Results
•
Number of data packets transmitted per data packet delivered
Simulation Results (cont’d)
•
Number of control bytes transmitted per data byte delivered
Simulation Results (cont’d)
•
Packet delivery ratio
Conclusions
• Conventional (wired net) routing schemes suffer of O/H,
mobility and scalability limitations
• Hierarchical routing reduces O/H and improves scalability
(at the expense of accuracy).
• On Demand routing eliminates background routing
control O/H. It introduces latency; it does not support
QoS routing
Conclusions (cont’d)
• Location assisted routing can enhance performance in
both on demand (LAR) and table driven (DREAM)
settings; GPS required.
• No routing scheme works best in all situations; selection
must be guided by application scenario
• Open problem: efficient location management and
resource discovery in highly mobile environment