1. E-mail: kemal@cs.siu.edu
Department of Computer Science Southern Illinois University Carbondale Mobile & Wireless Computing Routing Protocols for Sensor Networks Hierarchical & Location-based and QoS Protocols
Dr. Kemal Akkaya
Mobile & Wireless Computing

2. Hierarchical Protocols
When sensor density increases single tier networks cause
Sink overloading
Increased latency
Large energy consumption
Clustered Network allow coverage of large area of interest and additional load without degrading the performance
Hierarchical clustering schemes are the most suitable for wireless sensor networks
Uses Multi - hop communication within a cluster
Performs data aggregation and fusion on data to reduce number of transmitted messages to the sink
Maintain the energy reserves of nodes efficiently
Mobile & Wireless Computing

3. Hierarchical Routing
Mobile & Wireless Computing

4. LEACH
LEACH (Low Energy Adaptive Clustering Hierarchy) is the first hierarchical routing protocol for sensor networks
W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-efficient communication protocol for wireless sensor networks," in the Proceeding of the Hawaii International Conference System Sciences, Hawaii, January 2000.
Self-Organizing, adaptive clustering protocol
Even distribution of energy load among the sensors
Nodes organize themselves into clusters
Cluster-heads communicate data with the base station (sink)
Mobile & Wireless Computing

5. Cluster-heads at time t Cluster-heads at time t + d
LEACH
Dynamic cluster formation - Cluster-heads are not fixed
They rotate at each round randomly
Data-fusion at each cluster– reduces energy dissipation and enhances lifetime
Dynamic Clustering
Cluster-heads at time t
Cluster-heads at time t + d
Mobile & Wireless Computing

6. LEACH uses First Order Radio Model
Transmit k-bit message a distance d using the radio model
ETx-elec = Energy dissipated/bit at Transmitter
ERx-elec = Energy dissipated/bit at Receiver
Єamp = Amplification factor
Energy equation at the Transmitter:
Energy equation at the Receiver:
Fig 1: First Order Radio Model
Mobile & Wireless Computing

7. LEACH Algorithm
Algorithm is broken into rounds, and each rounds consists of following 4 phases:
Advertisement phase
Each node decides whether or not to become cluster-head
Advertises itself as cluster-head
Cluster Set-up phase
Each node decides to which cluster it belongs
Notification to the cluster-head
Schedule Creation
Cluster-head creates a TDMA schedule notifying each node when it can transmit
Data transmission
Each node send data during their allotted time
Mobile & Wireless Computing

8. Simulation Results Energy dissipation System Lifetime
Direct: Direct Transmission to the Sink
MTE: Minimum Transmission Energy
Energy dissipation
System Lifetime
Mobile & Wireless Computing

9. Sensor Lifetimes System life time after 1200 rounds
Live nodes (circled)
Dead nodes (dotted)
Mobile & Wireless Computing

10. What about MTE & Direct Communication?
No of rounds: 180
Alive (circles); Dead (dots)
Direct Communication
MTE
Mobile & Wireless Computing

11. LEACH Summary
Factor of 7 reduction in energy dissipation as compared to Direct Communication
Uniform distribution of energy-usage in the network
Doubles the system lifetime compared to other methods
Nodes die essentially in random fashion, thus maintain the network coverage
Completely distributed, no network knowledge required
Problems:
Nodes use single-hop communication
Not good for large domains
Cluster-head change overhead
Mobile & Wireless Computing

12. PEGASIS Power Efficient GAthering in Sensor Information Systems
Improvement to LEACH
Form chains rather than clusters
S. Lindsey and C. S. Raghavendra, "PEGASIS: Power Efficient GAthering in Sensor Information Systems," in the Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, March 2002.
Token-Passing Chain-Based
Considered Near-Optimal
Nodes die in random
Stationary Nodes and Sink
Every node have a global network map
Data Fusion
Greedy chain construction
Mobile & Wireless Computing

13. Main Procedures
Greedy Algorithm Construct Chain – Start at a node far from sink and gather everyone neighbor by neighbor
Node i (mod N) is the leader in round i
Nodes passes token through the chain to leader from both sides
Each node fuse its data with the rest
Leader transmit to sink
Mobile & Wireless Computing

14. PEGASIS - Illustration
Mobile & Wireless Computing

15. Comparison
Mobile & Wireless Computing

16. Summary Outperforms LEACH by eliminating clustering overhead
Global Information assumed
Limited Scale:
Information travels many nodes
Excessive delay for far nodes
Assumes any node can communicate with sink
Hierarchical PEGASIS
Extension of PEGASIS
Decrease the delay for the packets during transmission to the base station
Simultaneous transmissions of data messages
Avoid collisions and possible signal interference
Signal Coding (e.g. CDMA)
Spatially separated nodes can transmit at the same time
Mobile & Wireless Computing

17. Hierarchical PEGASIS
Mobile & Wireless Computing

18. Location-based Protocols
If the locations of the sensor nodes are known, the routing protocols can use this information to reduce the latency and energy consumption of the sensor network.
Distance between two nodes is calculated using location information
Energy consumption can be estimated
Efficient energy utilization
Location of a node can be determined using
Global Positioning System (GPS)
Ultrasonic Systems using trilateration
Beacons
Although GPS is not envisioned for all types of sensor networks, it can still be used if stationary nodes with large amount of energy are allowed.
Location based protocols assume that each node knows its location in the network
Mobile & Wireless Computing

19. GAF (Geographic Adaptive Fidelity)
GAF designed for both ad hoc and sensor networks
Y. Xu, J. Heidemann, and D. Estrin, "Geography-informed energy conservation for ad hoc routing," in the Proceedings of the 7 th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom’01), Rome, Italy, July 2001.
Forms a virtual grid of the covered area
Each node associates itself with a point in the grid based on its location
Nodes associated with same point in grid are considered equivalent
Some nodes in an area are kept sleeping to conserve energy
Nodes change state from sleeping to active for load balancing
Mobile & Wireless Computing

20. Representative Node for the subregion
Routing in GAF
Virtual
Grid
Sink
Representative Node for the subregion
Mobile & Wireless Computing

21. States in GAF Nodes use GPS to associate itself to the grid
A node remains active for time Ta
Ta of a node in the grid is broadcasted to other equivalent nodes
The sleeping time of a node is adjusted depending on Ta
In the discovery state each node broadcasts discovery messages periodically (Td)
Handles mobility
Three States
Discovery: Determining neighbors
Active: Does routing
Sleep: Turn off radio
Mobile & Wireless Computing

22. GAF Summary Increase the lifetime of the network significantly
Works for MANETs as well
Handles mobility
Also considered to be hierarchical protocol
Each sub-region is a cluster
Representative node is the cluster-head
But does not perform any data aggregation
Not very scalable. As the network size increases distance to the sink increases
Overhead of forming the grid
Only the active nodes sense and report data.
Hence data accuracy is not very high.
Mobile & Wireless Computing

23. Minimum Energy Communication Network (MECN)
L. Li and J.Y. Halpern, “Minimum-Energy Mobile Wireless Networks Revisited”. Proc. of IEEE Int. Conf. on Communications (ICC’01), Helsinki, Finland, June 2001.
Uses graph theory:
Each node knows its exact location
Network is represented by a graph G’, and it is assumed that the resulting graph is connected
A sub-graph G of G’ is computed.
G connects all nodes with minimum energy cost. A B
Connection A requires less energy than connection B because the power required to transmit between a pair of nodes increases as the nth power of the distance between them (n>=2).
Mobile & Wireless Computing

24. QoS Routing In WSN
QoS-aware protocols consider end-to-end delay requirements while setting up paths
End-to-end delay is the most common
Bandwidth
Video or image sensors
Real-time routing in
Disaster management
Fire detection
Tsunami alerts etc.
QoS in WSN is very challenging
Already have constraints such as bandwidth and energy
QoS routing will bring a lot of overhead
QoS in WSN is still in very early stages
May require redefinition of QoS for WSN
Mobile & Wireless Computing

25. SPEED A real-time routing protocol for WSN
T. He et al., “SPEED: A stateless protocol for real-time communication in sensor networks,” in the Proceedings of International Conference on Distributed Computing Systems, Providence, RI, 2003.
Each node maintains info about its neighbors and uses geographic forwarding to find the paths
Tries to ensure a certain speed for each packet in the network
Congestion avoidance
Mobile & Wireless Computing

26. Energy-aware QoS Routing Protocol
K. Akkaya and M. Younis, "Energy-aware routing of time-constrained traffic in wireless sensor networks," in the International Journal of Communication Systems, Vol. 17(6), pp , 2004.
Finds least cost and energy efficient paths that meet the end-to-end delay during connection
Energy reserve, transmission energy
WFQ (Weighted Fair Queuing) packet scheduling model used to support best-effort and real-time traffic
WFQ can provide upper delay bound
Used with constant data rate
Mobile & Wireless Computing

27. Summary of Protocols for WSN
Mobile & Wireless Computing