Transcript A Survey on Routing Protocols for Wireless Sensor Networks

A Survey on Routing Protocols
for Wireless Sensor Networks
Kemal Akkaya, Mohamed Younis
19th July, 2005
Seo, DongMahn
Contents






Introduction
Data-centric protocols
Hierarchical protocols
Location-based protocols
Network flow and QoS-aware protocols
Conclusion and Open Issues
19th July, 2005
2/33
Introduction (1)

Micro Sensor
micro-electro-mechanical systems (MEMS) , low power
and highly integrated digital electronics
 data processing, communication capabilities
 ambient conditions
 an electric signal
 command center (sink)
 data concentration center (gateway)
 disposable, unattended
 military, civil application, dangerous mission, landmine
 constraints – energy supply, bandwidth

19th July, 2005
3/33
Introduction (2)

Routing in sensor networks

Characteristics





No global addressing scheme
require the flow of sensed data from multiple regions (sources) to a
particular sink
redundancy of data traffic
constraints - transmission power, on-board energy, processing capacity and
storage
classification





data-centric
hierarchical
location-based
network flow
QoS awareness
19th July, 2005
4/33
Introduction (3)

System Architecture and Design Issues
Network Dynamics
 Node Deployment
 Energy Considerations
 Data Delivery Models
 Node Capabilities
 Data Aggregation/Fusion

19th July, 2005
5/33
Introduction (4)

Related Work

I.F. Akyildiz et al., “Wireless sensor networks: a survey”,
Computer Networks, Vol. 38, pp. 393-422, March 2002.





survey of design issues and techniques
physical constraints
protocols proposed in all layers of network stack
No classification of routing protocol
S.Tilak et al., “A Taxonomy of Wireless Microsensor Network
Models”, in ACM Mobile Computing and Communication
Review (MC2R), June 2002.



high level description of typical sensor network architecture
classification of sensor network with considering several architectural
factors
No routing protocol
19th July, 2005
6/33
Data-centric protocols (1)

Flooding and Gossiping
19th July, 2005
7/33
Data-centric protocols (2)

Sensor Protocols for Information via Negotiation
(SPIN)
19th July, 2005
8/33
Data-centric protocols (3)

Directed Diffusion
19th July, 2005
9/33
Data-centric protocols (4)

Energy-aware routing
set of sub-optimal path
 means of a probability function, energy consumption of
each path
 network survivability
 3 phases


Setup phase


Data Communication Phase


localized flooding - to find routes and to create the routing tables)
randomly choosing a node
Route maintenance phase

localized flooding - to keep all the paths alive
19th July, 2005
10/33
Data-centric protocols (5)

Rumor routing
variation of DD
 between event flooding and query flooding
 agent (event flooding), query flooding
 event table
 Simulation result

significant evergy saving
 can handle node’s failure
 only when the number of events is small

19th July, 2005
11/33
Data-centric protocols (6)

Gradient-Based Routing (GBR)
changed version of DD
 height of the node – number of hops
 gradient – difference between a node’s height and that
of is neighbor
 the largest gradient
 data combining entity (to aggregate data)
 three different data spreading techniques

Stochastic Scheme
 Energy-based scheme
 Stream-based scheme

19th July, 2005
12/33
Data-centric protocols (7)

Constrained anisotropic diffusion routing (CADR)
information-driven sensor querying (IDSQ)
 constrained anisotropic diffusion routing (CADR)
 maximizing the information gain
 minimizing the latency and bandwidth
 CADR

evaluation of information/cost/cost objective and routes
 based on local information/cost gradient and end-user
requirements


IDSQ

query node - the most useful information
19th July, 2005
13/33
Data-centric protocols (8)

COUGAR
a huge distributed database
system
 select a leader node
 network-layer independent
solution
 drawbacks

extra overhead
 synchronization
 failure of leader nodes

19th July, 2005
14/33
Data-centric protocols (9)

Active Query forwarding In sensoR nEtworks
(ACQUIRE)
new data-centric mechanism
 a distributed database, complex queries
 one-shot
 respond partially and forward to another sensor
 look-ahead of d hops
 d = 4, mathematical modeling
 no validation of result through simulation

19th July, 2005
15/33
Hierarchical protocols (1)

Low-Energy Adaptive Clustering Hierarchy
(LEACH)
clusters of the sensor nodes
 5% of the total number of all sensor nodes
 choosing header with random number between 0 and 1
 not for large network
 dynamic clustering with extra overhead

19th July, 2005
16/33
Hierarchical protocols (2)

PEGASIS & Hierarchical-PEGASIS

Power-Efficient Gathering in Sensor Information
Systems


chains from sensor nodes
Hierarchical-PEGASIS
chain based binary scheme
 CDMA, spatially separated nodes

19th July, 2005
17/33
Hierarchical protocols (3)

TEEN and APTEEN

Threshold sensitive Energy Efficient sensor Network
Protocol
clustering, hard and soft thresholds, TDMA
 not good for periodic applications


AdaPtive Threshold sensitive Energy Efficient sensor
Network protocol
hybrid network, TDMA (intra), CDMA (inter)
 periodic data collections and reacting to time-critical events
 three query types




historical, to analyze past data values
one-tome, to take a snapshot view of the network
persistent to monitor an event for a period of time
19th July, 2005
18/33
Hierarchical protocols (4)
19th July, 2005
19/33
Hierarchical protocols (5)

Energy-aware routing for cluster-based sensor
networks

3 tier architecture
19th July, 2005
20/33
Hierarchical protocols (6)

Self-organizing protocol
based on taxonomy
 Router node
 Local Markov Loops (LML)
 4 phases

Discovery phase
 Organization phase
 Maintenance phase
 Self-reorganization phase

19th July, 2005
21/33
Location-based protocols (1)

MECN & SMECN

Minimum Energy Communication Network
minimum energy network for wireless networks
 utilizing low power GPS
 2 phases




two-dimensional plane,
sparse graph (enclosure)
find optimal links with
distributed BelmannFord shortest path
algorithm
Small MECN

can transmit to every
other node
19th July, 2005
22/33
Location-based protocols (2)

Geographic Adaptive Fidelity (GAF)
energy-aware location-based routing algorithm
 ad hoc networks, GPS

19th July, 2005
23/33
Location-based protocols (3)

Geographic and Energy Aware Routing (GEAR)
use of geographic information
 to restrict the number of interests in DD
 2 phases

Forwarding packet
towards the target region
 Forwarding the pachkts
within the region

19th July, 2005
24/33
Network flow and QoS-aware
protocols (1)

Maximum lifetime energy routing
network flow approach
 maximize network lifetime
 Minimum Transmitted Energy (MTE) algorithm
 Bellman-Ford shortest path algorithm

19th July, 2005
25/33
Network flow and QoS-aware
protocols (2)

Maximum lifetime data gathering
Maximum Lifetime Data Aggregation (MLDA)
 Lifetime T
 data-gathering schedule S
 Maximum Lifetime Data Routing (MLDR)

19th July, 2005
26/33
Network flow and QoS-aware
protocols (3)

Minimum cost forwarding
minimum cost path
 effect of delay, throughput and energy consumption
from any node to the sink
 2 phases

setup phase
 second phase

19th July, 2005
27/33
Network flow and QoS-aware
protocols (4)

Sequential Assignment Routing (SAR)
the first protocol
 table-driven multi-path approach
 taking QoS metric, energy resource on each path and
priority level of each packet
 fault-tolerance and easy recovery
 overhead of maintaining the tables and states at each
sensor node

19th July, 2005
28/33
Network flow and QoS-aware
protocols (5)
 Energy-Aware QoS Routing Protocol

extended version
of Dijkstra’s
algorithm
19th July, 2005
29/33
Network flow and QoS-aware
protocols (6)

SPEED
soft real-time end-to-end guarantees
 end-to-end delay for the packets
 congestion avoidance
 routing module – Stateless Geographic NonDeterministic forwarding (SNFG)

19th July, 2005
30/33
Conclusion and Open Issues (1)
19th July, 2005
31/33
Conclusion and Open Issues (2)

more issues

Quality of Service (QoS)
video and imaging sensors
 real-time applications

Energy-aware QoS routing
 node mobility
 integration of WSN with wired networks

19th July, 2005
32/33
19th July, 2005
33/33