kemal akkayamobile & wireless computing 1 department of computer science southern illinois...

Mobile & Wireless Computing 1 Kemal Akkaya

Department of Computer ScienceSouthern Illinois University Carbondale

Mobile & Wireless Computing

Routing Protocols for Sensor NetworksHierarchical & Location-based and QoS Protocols

Dr. Kemal AkkayaE-mail: [email protected]


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


Hierarchical Routing


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)


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

Cluster-heads at time t Cluster-heads at time t + d

Dynamic Clustering


LEACH uses First Order Radio ModelTransmit k-bit message a distance d using the radio model

Fig 1: First Order 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:


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


Simulation Results

Energy dissipation System Lifetime

Direct: Direct Transmission to the Sink MTE: Minimum Transmission Energy


Sensor Lifetimes

System life time after 1200 rounds

Live nodes (circled)

Dead nodes (dotted)


What about MTE & Direct Communication?

No of rounds: 180 Alive (circles); Dead (dots)

Direct Communication MTE


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


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


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 iNodes passes token through the chain to

leader from both sidesEach node fuse its data with the restLeader transmit to sink


PEGASIS - Illustration


Comparison


Summary Outperforms LEACH by eliminating clustering overhead Global Information assumed Limited Scale:

Information travels many nodesExcessive 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


Hierarchical PEGASIS


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


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


Routing in GAF

Sink

Representative Node for the subregion

Virtual Grid


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


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.


AA

BB

Connection A requires less energy than Connection A requires less energy than connection B because the power required connection B because the power required to transmit between a pair of nodes to transmit between a pair of nodes increases as the nincreases as the nthth power of the distance power of the distance between them (n>=2).between them (n>=2).

Minimum Energy Communication Minimum Energy Communication Network (MECN)Network (MECN)

L. Li and J.Y. Halpern, “Minimum-Energy Mobile Wireless L. Li and J.Y. Halpern, “Minimum-Energy Mobile Wireless Networks Revisited”. Proc. of IEEE Int. Conf. on Networks Revisited”. Proc. of IEEE Int. Conf. on Communications (ICC’01), Helsinki, Finland, June 2001.Communications (ICC’01), Helsinki, Finland, June 2001.

Uses graph theory:Uses graph theory: Each node knows its exact locationEach node knows its exact location Network is represented by a graph G’, and it is assumed that the Network is represented by a graph G’, and it is assumed that the

resulting graph is connected resulting graph is connected

A sub-graph G of G’ is computed. A sub-graph G of G’ is computed. G connects all nodes with minimum energy cost.G connects all nodes with minimum energy cost.


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


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


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. 663-687, 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


Summary of Protocols for WSN

kemal akkayamobile & wireless computing 1 department of computer science southern illinois...

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